To help address this challenge, Dynatrace introduced new documentation and best practices for handling sensitive data.

This blog explains why the topic matters, what risks teams are trying to avoid, and how Dynatrace is designed to support privacy-first DEM adoption.

How privacy concerns slow DEM adoption

Across industries, we see the same patterns: Teams want granular and precise visibility to identify meaningful patterns and tailor improvements, while security, privacy, and compliance teams require strong guarantees around sensitive data handling. As a result, DEM adoption can be delayed or remain limited to basic use cases.

This is especially common in regulated environments such as banking and healthcare, where even well-intentioned monitoring can raise questions like:

• Are we collecting more data than necessary?
• Who can access personal data, and under what conditions?
• Are we handling sensitive data appropriately?
• Are we compliant with all our regulatory requirements?

Without clear answers and support, organizations may delay rollout, restrict access too aggressively, or avoid certain capabilities altogether.

Privacy by default in Dynatrace DEM

Dynatrace is designed with privacy-by-design principles:

• User sessions are anonymized out of the box
• Sensitive data can be masked at capture, storage, and read
• Access to sensitive fields is controlled through fine-grained permissions

Privacy settings are configured per frontend (web or mobile) and can be set independently based on each frontend’s risk profile and regulatory context.

Configure Dynatrace DEM for end-to-end compliance

Privacy and compliance should not be blockers to Digital Experience Monitoring, but they do require clear guidance and intentional configuration. Our DEM compliance guide explores two relevant use cases to help organizations identify which configuration options should be considered for their environments:

• Complaint resolution in an e-commerce web app: teams can utilize user tags to quickly identify affected sessions and resolve issues, while access to personal data remains tightly controlled.
• Troubleshooting performance issues in a mobile banking app: teams can gain insights and fix stability or performance issues while fully masking all personally identifying information.

Learn more

To meet data compliance requirements set by industry regulations, organizations must identify specific requirements and outline the steps to protect sensitive data. The new documentation helps organizations to expand or refine their use of Digital Experience Monitoring by demonstrating how to:

• Configure privacy settings for frontends
• Limit data collection
• Control access to sensitive fields
• Support troubleshooting and performance optimization without compromising compliance

The post How to build trust in Digital Experience Monitoring appeared first on Dynatrace news.

The Synthetic experience on the latest Dynatrace platform is complete with the transition of browser monitors. Once activated, Dynatrace runs browser monitors using the newest RUM JavaScript, delivering more accurate simulations and tighter alignment with Real User Monitoring. The updated experience makes Synthetic more powerful and easier to act on, from rich waterfall analysis to trend visualization and automation with execution details stored as events in Grail® and available via Dynatrace Query Language (DQL).

Deeper visibility and smarter analysis with Synthetic on the latest Dynatrace platform

•  Waterfall chart report in the latest Dynatrace experience
  The transition of Synthetic to the 3rd generation of Dynatrace is complete: All Synthetic capabilities, including the Requests waterfall chart powered with data from the latest  RUM JavaScript, are now available directly in the latest Dynatrace experience.
• Explore synthetic events with DQL
  Use DQL to run ad‑hoc queries on synthetic event data to filter, aggregate, and correlate results with other telemetry for advanced troubleshooting and performance optimization.

How to turn on browser monitors and fully benefit from the latest Dynatrace capabilities

Turning on browser monitors fully in the latest Dynatrace is quick and flexible; you can flip it on for your whole environment or opt in per monitor to run a phased rollout.

• Go to Settings > Synthetic Monitoring > New Browser Monitors Experience.
• Set the Scope behavior: Turning on browser monitors at the environment level is the default; individual monitors can override the default so teams can test or migrate gradually.

Enhanced Requests waterfall chart

The new Requests waterfall gives you real troubleshooting power. It moves analysis from vague timing numbers to resource‑level visibility you can act on.

• See every resource that loaded with the page (type, name, and exact load duration in ms), so you can spot the single slow asset that drags down performance and, by extension, the user experience across the whole page.
• Know what triggered each request—the resource initiator (fetch, script, link, XHR, etc.)—to distinguish third‑party scripts, lazy loads, or XHRs that unexpectedly spike load time
• Identify render‑blocking and timing boundaries (start/end times) to separate network latency from rendering or scripting costs. This is critical when deciding whether to optimize CDN, defer scripts, or rework code
• Instantly spot failing resources—errors are flagged directly in the waterfall, so you don’t have to cross‑check multiple views to find missing or broken assets
• Understand retries and execution attempts—if automatic retry on error is turned on, the executions table and waterfall surface retry attempts (with icons), giving you the full story for flaky tests or transient network issues
• Delivered natively in the Latest Dynatrace experience. You get the enhanced Requests waterfall and resource‑level analysis without having to fall back to Synthetic Classic for detailed reporting

In short, the waterfall turns a monitor execution into a forensic timeline, resource by resource, initiator by initiator, so teams can pinpoint root causes faster and prioritize the fixes that deliver the biggest user‑facing improvements

DQL exploration

Browser monitors fully in the latest Dynatrace surfaces Synthetic and RUM events in Grail, so you can query execution details with DQL, turning monitor runs into searchable, automatable telemetry.

Core benefits

• Synthetic events give you execution-level context (monitor‑wide status, availability, and problems) and step‑level details (step duration, screenshots, errors). Use DQL to filter and aggregate executions by location, time frame, or error type for fast root‑cause discovery and trend analysis.

FETCH DT.SYNTHETIC.EVENTS
| FILTER EVENT.TYPE == "BROWSER_MONITOR_EXECUTION"
| LIMIT 10

FETCH DT.SYNTHETIC.EVENTS
| FILTER  EVENT.TYPE == "BROWSER_MONITOR_STEP_EXECUTION"
| FILTER EVENT.ID == "101546320749"
| SORT STEP.SEQUENCE_NUMBER ASC

• User events provide resource-level details for each asset loaded during a browser monitor execution (resource type, name, load duration, initiator, render-blocking status). Query these to isolate all or very specific failing resources and to detect lazy load patterns or third-party script behavior proactively

FETCH  USER.EVENTS 
| FILTER EVENT.ID == "101546320749"
| SORT STEP.SEQUENCE_NUMBER ASC
| FIELDS VIEW.URL.FULL, URL.FULL, PERFORMANCE.INITIATOR_TYPE, HTTP.RESPONSE.STATUS_CODE, 
PERFORMANCE.RESPONSE_END, PERFORMANCE.TRANSFER_SIZE

• Because execution details are available in Grail, you can build automations and workflows that react to synthetic outcomes; for example, alert enrichment, automated rollback, or validation steps in CI/CD, or ticket creation with execution context. A community product idea highlights demand for programmatic access to execution details via API as a practical automation enabler.

Enrichment of Synthetic data with primary Grail tags

To make DQL queries even more powerful, Grail can enrich synthetic events, user events, and the metrics that describe browser‑monitor executions with primary Grail tags. These are a small set of customer‑selected tags that Grail automatically attaches at ingest under the primary_tags.* prefix.

Why this matters for browser monitor telemetry

• Fast, consistent grouping: you can group executions, events, and metrics by business or operational dimensions (for example, primary_tags.team, primary_tags.app, primary_tags.environment) without adding ad‑hoc joins or expensive post‑processing.
• Precise filtering: filter DQL queries and dashboards by primary tags to focus on a particular team’s monitors, a specific application, or a cost center across Synthetic and RUM data in one query.

You can now set primary Grail tags per Synthetic monitor during creation or editing, so each monitor’s executions carry that metadata into Grail for queries and automations.

Take the next steps

Take the next step today: turn on the browser monitor experience in the latest Dynatrace and convert synthetic checks into actionable, searchable signals.

• Enable the browser monitor experience on the latest Dynatrace. Flip the new Browser Monitors Experience on to get the latest RUM JavaScript and enhanced reporting everywhere.
• Analyze with the modern Requests waterfall. Use the improved waterfall (fully in the Latest Dynatrace experience) to investigate executions at the resource level and pinpoint root causes faster.
• Leverage DQL and Grail. Query synthetic and RUM events to deepen analysis, build dashboards, and drive automations that react to real monitor outcomes. Check out this example Notebook in Dynatrace Playground to see DQL applied to Synthetic executions and error analysis.

What’s next

Expect improved access control capabilities to help you precisely limit who can view and act on Synthetic monitors and their results, making it easier to secure and share the right telemetry with the right teams.

The post Improved browser monitor experience: Synthetic on the latest Dynatrace platform appeared first on Dynatrace news.

With crash intelligence from the new Dynatrace RUM experience, practitioners get a dedicated mobile health view that instantly highlights regressions and stability issues, while two ready‑made dashboards surface performance and troubleshooting insights with zero setup. Where traditional tools stop at isolated crash reporting, Dynatrace connects every error and crash signal—across native, hybrid, and cross‑platform apps. The result is a single, intelligent experience that helps teams ship faster, fix issues sooner, and deliver trustworthy mobile apps.

Why mobile troubleshooting has fallen behind

In the web world, metrics like Core Web Vitals provide a common language for performance. In mobile, no such standard exists, despite mobile apps being far more sensitive to performance regressions than desktop applications. There’s an even bigger challenge: while browser‑based issues can be fixed instantly with a quick deployment, mobile bugs require a full app‑store release and rely on users updating their devices; this makes mobile bugs far more difficult and slower to reverse. It also makes proactive observability even more critical for mobile than for web. Furthermore, today’s mobile apps span hundreds of device types and unpredictable network conditions, and frameworks like React Native or Flutter must function reliably across a range of hardware and operating‑system versions. These layers make traditional “crash-only” analytics insufficient.

While a slow app start can cost you a new user before they’ve even reached your home page, a poorly performing view can stall your conversion funnel. And a frozen view can quietly destroy user trust without leaving any clear trace in your logs. Other monitoring tools often treat these problems in isolation: a crash report here, a view-analytics SDK there, an app-start metric captured in another tool… But teams need unified context, not fragmented data on glass.

A dedicated mobile performance experience

The new Dynatrace RUM experience solves this problem by bringing together performance and stability in a coherent picture rooted in real user journeys, not isolated events. This combined visibility is what sets Dynatrace apart. The foundation of the new RUM experience lies in a new performance analysis capability that reflects how mobile apps actually work. Apps are now represented through mobile “views”—the mobile app pages that users interact with as they move through the RUM experience. Dynatrace automatically detects views for native iOS and Android apps, with manual instrumentation available for frameworks like Flutter and React Native. Performance signals for each view tell a story, including, for developers, where the errors or exceptions occurred.

These metrics are stored as Dynatrace Grail®-native data with all relevant dimensions, enabling rich analysis across devices, OS versions, app versions, and frontends. These metrics are fed directly into Experience Vitals, where App Owners and PMs can drill down from a high-level performance view into detailed metrics for each view. Select any specific view to reveal its performance characteristics, error footprint, and context across the user journey.

App health intelligence on the basis of crashes, ANRs, and error context

Crashes have always been a pain point for mobile developers, but ANRs are often worse. Many tools treat ANRs as an afterthought, offering incomplete or inconsistent visibility. Error Inspector, the dedicated app for frontend troubleshooting on the Dynatrace platform, now captures ANRs on both iOS and Android, as well as crash reporting for Android NDK. Error Inspector reports errors as structured user events with precisely defined semantics. Previously, Dynatrace practitioners could add properties to automatically monitored telemetry data, turning previously opaque frontend degradations into immediately diagnosable issues. Similarly, in the new RUM experience, user events triggered by mobile apps are automatically enriched with view context, device details, and session information to identify exactly which users, contexts, and conditions triggered a crash, thereby dramatically accelerating root‑cause identification and troubleshooting.

Server-side processing applies efficient grouping logic to provide a clear, deduplicated view of what’s happening, enabling meaningful dashboarding and reliable future alerting. With Dynatrace Experience Vitals, SREs gain insights into app performance and stability. Insights are elevated to the same first-class status as performance, ensuring teams see both sides of the experience.

Crashes and ANRs flow naturally to Error Inspector, where they’re prioritized by severity—crashes have higher severity than errors, and all ANRs are highlighted. For developers, this means less noise and faster diagnosis. For business leaders, it means clarity on what matters most, making prioritization a breeze.

Introducing React Native symbolication

Cross-platform frameworks create powerful opportunities but introduce complexity when things go wrong. Stack traces often combine JavaScript and native code, leaving teams with unhelpful, obfuscated output like hashes. To solve this, Dynatrace now supports full React Native source map uploading and management, with automatic symbolication of React Native crashes directly in Error Inspector.

Teams can upload symbol files through standard methods and manage them via a new interface. Unlike competing tools, which only partially support hybrid stack symbolication/deobfuscation or require manual post-processing, symbolicated crashes appear automatically in Dynatrace, making debugging dramatically more efficient.

For developers working with React Native, this eliminates the friction of switching tools and patching together build artifacts.

A new mobile health overview

Mobile developers often collaborate with their SRE counterparts on observability teams, who frequently face a simple yet critical question from App Owners and PMs: “Is my mobile app healthy right now?”

The answer to this question is provided by Experience Vitals. The mobile health overview shows whether RUM is enabled on your monitored devices, highlights performance indicators such as app start thresholds, and surfaces stability concerns such as crash and ANR rates. Crashes and errors link directly to Error Inspector, creating a smooth transition from error awareness to analysis.

This focus on clarity allows decision makers to grasp app health at a glance while giving developers frictionless access to the underlying data.

Good insights require the correct setup

To help teams get started faster and avoid misconfiguration, Dynatrace introduces improved instrumentation guides for iOS and Android. These guides add necessary context to ensure new customers receive the exact data they expect. The mobile settings experience has been redesigned to make it clear how UI selections correspond to code snippet changes, aligning it more closely with what teams experience in agentless web flows. This consistency matters, especially for practitioners managing multiple platforms on the enterprise level.

To accelerate adoption and make insights immediately usable, Dynatrace is introducing two ready-made dashboards:

• App start health dashboard, which includes app start analysis and high-level performance trends.
• Mobile health dashboard, designed for investigating crashes and errors, providing stability insights without requiring configuration.

These dashboards incorporate the new metrics, dimensions, and logic introduced across the release, giving teams instant, actionable visibility into their mobile apps. Decision-makers get the reports they need, developers get the views that help them move faster. And everyone benefits from data that’s consistent, contextual, and unified.

Raising the bar for mobile troubleshooting

Most mobile monitoring solutions emphasize either performance or stability, but rarely both in a unified, contextual way. Many tools require heavy manual instrumentation, fragmented SDKs, or separate troubleshooting workflows for native and cross-platform apps. Crash grouping is inconsistent, ANR support varies widely, symbolication often requires external tools, and virtually no other mobile monitoring solution combines all this with a platform that also ties into backend traces and business impact.

Dynatrace delivers something fundamentally and wonderfully different: a single, Grail-powered, full stack view of mobile performance and stability that blends performance metrics, view insights, app-start intelligence, ANR/crash analytics, and hybrid framework support—all in one place, all contextualized by real user journeys and backend traces. This is not just crash reporting. It’s not just performance monitoring. It’s a complete solution for understanding the mobile experience, from the first view to the last tap.

With these enhancements, Dynatrace sets a new standard for mobile observability. Mobile developers gain a more intuitive debugging experience. Product Managers get clear KPIs. App owners receive actionable health insights. And organizations as a whole gain the ability to deliver reliable, performant, and engaging mobile experiences. In a digital world increasingly shaped by mobile interactions, Dynatrace provides the visibility teams need—and the intelligence mobile troubleshooting has been waiting for.

Get started

To instrument your mobile apps and start collecting the full breadth of performance and stability data, please visit our mobile instrumentation documentation. And, if you want to explore how Dynatrace helps you debug crashes, ANRs, and React Native issues with full context, open Error Inspector to see these new capabilities in action.

The post Deep troubleshooting and crash intelligence in the new Dynatrace RUM experience appeared first on Dynatrace news.

Why RUM matters more than ever

As the frontend becomes the primary point of customer engagement, real user monitoring is a critical link between IT performance and business outcomes. The ways users interact with web and mobile apps have evolved, driven by single-page applications (SPAs), asynchronous rendering, and nonlinear navigation. These changes have increased the demand for RUM solutions that can keep pace with modern architectures and deliver actionable insights.

Teams face growing challenges:

• Limited visibility into user journeys across SPAs and mobile applications
• Fragmented analysis between frontend telemetry and backend execution
• Slow troubleshooting when context is missing or spread across tools
• Increased pressure to capture meaningful data while maintaining strict privacy standards

Modern frameworks and libraries introduce new patterns and constraints, making it harder to understand user behavior and optimize experiences using legacy tools. Teams require solutions that not only keep pace with evolving architectures but also empower them to act quickly and confidently on user experience data.

Reinventing RUM for modern application experiences

The new Dynatrace RUM experience was purpose-built to address these challenges and futureproof RUM use cases. By leveraging unified, end-to-end observability with deep business context, Dynatrace introduces a streamlined, modern approach to understanding frontend performance and user behavior. Advanced analytics and intuitive, purpose-built workflows are layered on a foundation that aligns with how today’s teams operate.

With this new RUM experience, teams can:

• Understand modern application behavior with new frontend signals: Gain deeper visibility into how users interact with single-page and mobile applications, leveraging new data models and behavioral signals.
• Improve user experience with out-of-the-box insights and intuitive practitioner workflows: Access immediate, actionable insights through purpose-built apps and dashboards designed for common practitioner tasks.
• Extend insights with advanced analytics and built-in privacy controls: Perform deeper analysis, maintain responsible long-term data retention, and ensure privacy and compliance with flexible data access and built-in controls.

Together, these capabilities empower teams to optimize performance, resolve complaints, analyze user behavior, and accelerate DevOps workflows—collaborating more effectively and acting faster on real user impact.

Understand modern application behavior with new frontend signals

The ability to capture and analyze new frontend signals that reflect how modern applications behave in production gives teams a more accurate view of how users move through single-page and mobile applications—without additional instrumentation.

Industry standards such as Core Web Vitals, along with mobile-specific performance signals coupled with enhancements for troubleshooting: application not responding (ANR) and symbolication, provide a consistent way to assess application health and troubleshoot issues across platforms. The new RUM data model captures events that reflect how modern applications behave in production, including:

• Background requests: Network calls initiated by an application without direct user interaction, typically to fetch or update data in the background to maintain app functionality and user experience.
• User interactions: Events such as clicks, taps, scrolls, or keypresses that reflect how users engage with an application and provide behavioral insights without necessarily invoking a backend request.
• Soft navigation: As modern web applications often don’t perform a full-page load when navigating, soft navigation helps analyze the user’s path through the application from one view to the next.

Improve user experience faster with out-of-the-box insights and intuitive practitioner workflows

The new RUM experience delivers immediate value through redesigned, task-oriented experiences built around common practitioner workflows. Out-of-the-box apps and dashboards make RUM data easier to understand and act on from the start.

Pre-built dashboards surface industry-standard performance metrics such as Core Web Vitals and key mobile signals, giving teams a clear and consistent view of frontend health. Unified dashboards bring frontend and backend data into a single view, making it easier to trace request errors to their underlying exceptions, monitor customer experience over time, and understand how performance issues impact business outcomes.

Purpose-built apps include:

Experience Vitals: Quickly identify which requests or assets are contributing to slowdowns, using redesigned waterfall analysis and industry standards like Core Web Vitals. DevOps teams can define custom alerts and integrate them into existing workflows.

Error Inspector: Group and prioritize errors, presenting critical context in one place. Session details are shown alongside stack traces, making it easier to assess impact and resolve problems quickly. Integration with Jira accelerates issue tracking and accountability.

Users & Sessions: Ground investigations in real user session data. Support teams can quickly find and analyze individual sessions, reducing guesswork and time to resolution. Product owners can identify friction points, validate reported issues, and improve user journeys based on actual behavior.

These capabilities help teams:

• Optimize frontend availability and performance
• Troubleshoot issues faster with clear, end-to-end context
• Resolve customer complaints using real session data

“UWM is deeply committed to site reliability engineering to deliver the best possible client experience. With the new RUM experience, we gain unprecedented, actionable insights into user interactions, empowering our SRE teams to optimize performance.”

Gavin Wallis, Observability Architect, United Wholesale Mortgage

Extend insights with advanced analytics and built-in privacy controls

While out-of-the-box experiences address the most common workflows, some scenarios require a deeper dive. The new RUM experience provides flexible access to all frontend data through a unified data model, enabling teams to explore real user behavior with greater context and precision.

• Custom dashboards and collaborative Notebooks: Correlate frontend behavior with backend performance, analyze experience trends over time, and connect user experience directly to business outcomes such as conversion or revenue impact.
• Dynatrace Query Language (DQL): Explore and connect data, with Dynatrace Intelligence available to help with query generation and data interpretation.
• Privacy and compliance: Built-in privacy and permission controls support responsible data use. Extended data retention (public preview) allows deep investigations, compliance support, and historical trend analysis.

Getting started with the new RUM experience

The new RUM experience is now generally available, with all apps and features available by default on DPS SaaS tenants with version 330 or higher. You can allow data ingestion to the Dynatrace 3rd-generation platform for individual frontends or whole environments. (Classic data capture isn’t impacted.)

Dynatrace RUM setup guides

• For web application setup, follow these steps. If you use automatic injection, the new configuration will be applied within 5 minutes. If you insert the RUM JavaScript manually, you might need to update the snippet, depending on the snippet format you’re using.
• For mobile app setup, follow these steps to set up the new RUM experience.
• For web frontends at the environment level, follow these steps.

The post Unprecedented insights into frontend user experience with Dynatrace Real User Monitoring appeared first on Dynatrace news.

Anomalies are clues that something in your system isn’t behaving as expected. Detecting these early warnings gives SREs and developers a critical window to investigate and resolve the issue before they impact customer experience. But detection alone isn’t enough. You need to identify the root cause so teams can take action before a minor glitch cascades into something more serious that impacts revenue and customer experience.

Dynatrace automatically connects synthetic monitoring, traces, and logs, so you can go from spotting an anomaly to uncovering the exact root cause in under a minute. Without a unified solution, you’d have to sift through logs spread across different systems, which is not only time consuming but can also result in human error. With Dynatrace, you can drill down to the failed test execution and then jump directly into distributed trace and related logs to expose the precise error in code. Instead of just showing data, Dynatrace delivers answers fast.

Let’s take a look at how this works in practice by walking through an example.

From error to answer in a few steps

The Dynatrace platform was built to solve complex challenges, whether they originate in the frontend, backend, or database. Modern applications are distributed systems, where a single user action can trigger a chain of events across dozens of services. To understand this chain, you need to link the beginning (the user’s action) to every subsequent step. Synthetic monitoring and distributed traces are powerful capabilities that provide visibility into this complex chain, but only when automatically connected do they deliver easy insight into end-to-end performance and user experience.

Now, let’s walk through this process step-by-step.

1. Spot the anomaly on the dashboard

Our journey begins on the ready-made synthetic monitoring dashboard. This high-level overview aggregates results from all monitors and locations, making it easy to spot issues—like a sudden spike in HTTP 500 errors in our travel booking system. Each of these errors could negatively impact user experience, so we want to get to the bottom of this quickly before we see a major degradation of service that could lead to lost revenue or brand reputation damage.

A single click on the problematic metric begins the investigation.

2. Isolate the failing monitor

With the context of time and error type carried over, you’re directed to a filtered list of all synthetic monitors that experienced a 500 error in that timeframe. Here, we can instantly see that the Easytravel storeBooking monitor has a low availability of 77.78% and has registered five failed requests.

Clicking “Analyze errors” allows us to drill down further.

3. Analyze the failed execution

This page presents a list of individual test executions over time. On this timeline, you can instantly identify the specific failed run (marked in red) and move from a general problem to a concrete instance of failure. Selecting the failed execution and clicking “View traces” is the final step in our investigation.

4. Uncover the root cause with distributed tracing

With one more click, you’re taken across the automated bridge to the Distributed Tracing Explorer. Dynatrace automatically carries over all the context, showing you the exact end-to-end trace for that specific failure.

Here, the root cause is exposed. The trace shows that Exceptions are captured, also linking directly to the related logs. There, the technical reason and the detailed error message is waiting: an ArrayIndexOutOfBoundsException occurred within the storeBooking service. This tells you precisely what broke in the code and where to look to solve the 500 error spike. Dynatrace consolidates this experience onto a single platform, saving you the time and effort that would have been required to sift through disjointed pieces of data scattered across multiple tools and enabling you to solve the problem before it escalates.

The advantage: actionable answers, not disjointed data

This entire workflow, from a high-level dashboard to a code-level root cause, takes less than a minute! Whether you start from a dashboard or the Problem app, the result is the same: you get a definitive, actionable answer in moments.

The post From anomaly to root cause in under a minute appeared first on Dynatrace news.

Digital experiences define how organizations compete and grow. Even the smallest performance issue can disrupt journeys, stall transactions, or slow innovation. As ecosystems expand across multicloud environments, microservices, and serverless functions, understanding what’s happening beneath the surface and how it affects your end users becomes exponentially harder.

That’s why we’re proud to announce that Dynatrace has been named a Leader in the 2025 Gartner Magic Quadrant for Digital Experience Monitoring for the second year running, and positioned furthest for Completeness of Vision in 2025.

Real-time intelligence beats reactive dashboards

Modern applications don’t fail gracefully; they fail in cascades. A backend service slowdown ripples through APIs, affecting frontend performance, which impacts user sessions and ultimately drives customers away. Traditional monitoring tools show you the symptoms after the damage is done. Today, businesses need real-time intelligence that connects every dot across your entire digital ecosystem.

Digital experience monitoring (DEM) brings the entire user journey into focus, revealing how every click, transaction, and session shapes experience and drives results. When done right, DEM transforms reactive firefighting into proactive optimization.

The Dynatrace difference: AI-powered observability, at scale

Dynatrace delivers comprehensive digital experience monitoring (real user monitoring, session replay, and synthetic monitoring) through our AI-powered observability platform that automatically discovers, maps, and monitors every component of your digital ecosystem, enabling the following key capabilities:

• Real-time user session analysis. Track every user interaction across web, mobile, and API endpoints with real user monitoring, session replay, and AI-powered anomaly detection. Understand not just what happened, but why it happened and what to do about it.
• Automatic root cause analysis. Our Davis® AI engine analyzes billions of dependencies in real time, automatically identifying the precise root cause of performance issues before they escalate into business-impacting outages.
• Proactive experience optimization. Move beyond reactive monitoring to predictive insights. Dynatrace identifies experience degradation patterns, monitors around the clock with synthetics, and recommends optimizations before users feel the effects.
• Unified data model. Break down silos between infrastructure, applications, and user experience data. Our unified approach means faster resolution times and clearer business impact visibility.

Turning digital experience into business impact

Organizations using Dynatrace for digital experience monitoring report seeing:

• 90% reduction in mean time to resolution
• 60% fewer customer irritants
• 65% reduction in customer churn

Flawless digital experiences create momentum that frees teams to innovate, keeps customers loyal, and turns performance into measurable growth.

Read the full Gartner® report

In our opinion, being named a Leader in the 2025 Gartner® Magic Quadrant™ for Digital Experience Monitoring is more than recognition. We believe it’s a celebration of the teams who deliver flawless digital experiences with Dynatrace every day.

We’re proud of this recognition, but we’re even more excited about what’s ahead. With Davis AI at the core of our platform and unified observability powering every insight, we’re helping organizations transform complexity into their greatest competitive advantage.

Huge thanks to our amazing customers, partners, and teams. We believe you’re the real driving force behind this position as a Leader.

Frequently asked questions

What does being a Leader in the Gartner® Magic Quadrant™ mean?

The Gartner Magic Quadrant evaluates vendors based on their Completeness of Vision and Ability to Execute. In our opinion, being positioned as a Leader indicates that Gartner recognizes Dynatrace as having both a strong strategic vision for digital experience monitoring and the proven capability to deliver that vision for customers.

​Where can I access the full Gartner® Magic Quadrant™ report?

You can access the complete 2025 Gartner Magic Quadrant for Digital Experience Monitoring report here. Gartner Magic Quadrant gives enterprise technology shoppers an unbiased assessment of how well competing providers are performing against the Gartner market view and is supplemented by validated user reviews.

What is digital experience monitoring (DEM)?

Digital experience monitoring is a comprehensive approach to tracking, analyzing, and optimizing how users interact with digital applications and services. Unlike traditional monitoring that focuses on individual system components, DEM provides end-to-end visibility into the complete user journey, helping organizations understand and improve customer experiences.

How is DEM different from traditional application monitoring?

Traditional monitoring typically focuses on infrastructure metrics and application performance in isolation. DEM takes a user-centric approach, correlating technical performance with actual user journey and business outcomes. It provides context about how technical issues impact real user experiences and business results.

What makes the Dynatrace approach to DEM unique?

Dynatrace combines full-stack observability with AI-powered analysis through our Davis AI engine. This means automatic discovery of all dependencies, real-time root cause analysis, and proactive identification of issues before they impact users. Our unified data model breaks down silos between teams and provides complete visibility across the entire digital ecosystem.

Can Dynatrace DEM work with cloud-native and microservices architectures?

Yes. Dynatrace is built for cloud-native architectures and automatically adapts to dynamic environments, including Kubernetes, serverless functions, and multi-cloud deployments. Our technology scales automatically as your environment changes, maintaining complete visibility regardless of architectural complexity.

How does Dynatrace help with compliance and security?

In addition to DEM, Dynatrace also provides comprehensive audit trails, data privacy controls, and security monitoring. Our platform helps organizations maintain compliance requirements while ensuring complete visibility into user experiences and system performance.

^{Dynatrace, Davis, and the Dynatrace logo are trademarks of the Dynatrace, Inc. group of companies.}

_________________________

^{Gartner, Magic Quadrant for Digital Experience Monitoring, Padraig Byrne, Pankaj Prasad, DB Cummings, Martin Caren, and Tanmay Bisht, 27 October 2025.}

^{GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.}

^{Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.}

The post Dynatrace® named a Leader in 2025 Gartner® Magic Quadrant™ for Digital Experience Monitoring appeared first on Dynatrace news.

Mobile teams struggle to solve what they can’t see

For many businesses, mobile is now the most critical channel for engaging users. Mobile apps are where purchases happen, accounts are created, and first impressions are made. But it’s also where users are most likely to abandon their journeys if something feels broken, slow, or unintuitive.

All practitioners struggle to understand what actually happened during a user’s session when something goes wrong or when a user behaves in a way that deviates from the expected journey. This can get particularly puzzling when there are no apparent errors or performance blockers hindering a user’s experience. Traditional tools provide fragmentary details: logs, events, crash reports, or aggregated analytics. However, none of these capture the full context. Mobile engineers are unable to reliably reproduce bugs without seeing exact user actions. Support teams can’t respond effectively to vague or incomplete user reports.

Full visibility into mobile user behavior

This is where Session Replay comes in. This capability recreates real user behavior in a video-like playback, so you can visually step through a session just as the user experienced it: taps, swipes, scrolls, page transitions, and all. And now, for the first time, this powerful capability extends beyond the browser and crashes on mobile apps to include full sessions for native mobile apps.

With Dynatrace Session Replay for mobile apps, teams get a complete, contextual view of how users interact with mobile apps in the wild by collecting and visualizing key signals like gestures, views, UI states, and navigation paths. While Session Replay is often seen as a frontend-focused tool, it can significantly help identify, triage, and resolve backend issues by connecting user actions to system behavior. This helps contextualize backend failures, correlate user actions to backend events, and, in a nutshell, identify misalignment between front and backends.

How to make the most of Dynatrace Session Replay for Mobile Apps

Let’s dive into key use cases where Session Replay delivers tangible value across teams:

Faster debugging

Understanding the problem is often impossible with only data from Logs or Real User Monitoring. In some cases, observing the sessions where the error occurs can provide valuable context and lead to a more accurate solution.

Use case: Imagine your team can’t reproduce a performance issue affecting only a small segment of users still using iOS 17. Logs are inconclusive, and RUM data doesn’t tell the whole story.

With Session Replay, you can:

• Watch the exact gestures and actions related to the issue.
• See which page or interaction triggered the problem.
• Identify whether it’s a device-specific issue, a network hiccup, or a UI bug.

Result: Your dev team fixes the issue in hours, not days, without needing to reproduce it manually.

UX optimization and boosting conversion

The best way to understand users is to observe how they engage with your applications. Session Replay allows you to select a sample of mobile sessions based on various criteria. Watching these sessions helps you learn about annoyances and understand patterns in user behavior, which can then be streamlined into a better user experience.

Use case: Your analytics show a drop-off in the final step of your checkout funnel, and you don’t know why. Is it a confusing UI? A broken button? A slow-loading view?

With Session Replay, you can:

• Watch real user sessions to see where they pause, scroll, or back out.
• Identify if users struggle with form validation, payment options, or navigation.
• Spot rage taps or repeated attempts to interact with unresponsive elements.

Result: You optimize the checkout flow, reduce abandonment, and increase conversions—backed by real user behavior.

Improved customer support

Allowing help desk personnel to review the session that prompted a user’s complaint provides common ground for the conversation and helps ensure user satisfaction.

Use case: A user submits a support ticket: “The app didn’t work when I tried to book a ride.” No screenshots, no steps to reproduce, and the issue can’t be replicated.

With Session Replay, your support team can:

• Instantly view the user’s session to see what they saw.
• Understand the context: which screen they were on, what they tapped, and what went wrong.
• Provide a fast, accurate response, or escalate with full context to engineering.

Result: Faster resolution, happier users, and fewer back-and-forth emails.

Data privacy

Dynatrace adheres to world-class standards for data protection. Mobile session data is secured just like any other captured telemetry. However, privacy configurations must still be reviewed by each customer to ensure compliance with internal and legal requirements. Like web applications, Session Replay for mobile applications offers three levels of privacy controls:

• Safest – Masks all editable text fields, labels, images, switches, and web views
• Safe – Masks all editable text fields only
• Custom – By default, behaves like Safest, but allows you to define exactly which elements or views to mask.

See configure custom masking in the preferred documentation below.

Turn on Dynatrace Session Replay for Mobile Apps

Cluster-side activation

Session Replay is now supported for both iOS (including those built in SwiftUI) and Android apps (including those using Jetpack Compose). To get started, you’ll first need to turn it on for each mobile app, as it’s managed separately at the cluster level.

To activate the feature:

1. Navigate to: Frontends → Select a mobile application → Edit → Enablement and cost control
2. Set the Session Replay Mobile toggle to on.

Once turned on, you can define the percentage of sessions to capture. By default, Dynatrace captures 100% of sessions, but you can reduce this based on your data volume and storage needs.

Session Replay for Mobile integrates seamlessly with Session Replay for Crashes. This allows you to:

• Automatically capture 100% of crash sessions
• Sample a configurable percentage of all other sessions

If you’re hosting Dynatrace on-premises, make sure to prepare for increased storage requirements before enabling this feature.

Instrumentation and configuration of a mobile application

Scenarios differ depending on the operating system, so please follow our documentation:

• Configure Session Replay for iOS
• Configure Session Replay for Android

The instrumentation and configuration process is simplified for customers who have already used Session Replay for Crashes or mobile Real User Monitoring.

The post Dynatrace Session Replay for Mobile Apps: see what your users see appeared first on Dynatrace news.

Business Insights is a unique team within Dynatrace that partners with organizations to maximize their value from Digital Experience Monitoring (DEM) and Business Analytics, through our deep product expertise and exclusive technology capabilities. The Business Insights team provides product configuration and best practices, exclusive analytics and analysis to drive improved customer experience, and expertise on demand. Dedicating the necessary time, resources, and focus to deliver excellent end-user experiences can be a challenge. This is why Dynatrace’s largest and most sophisticated customers rely on Business Insights to deliver the strategic value that helps drive improved customer experience and business outcomes, whether that’s:

• Deploying a synthetic monitoring strategy to help a large beverage company achieve 100% age-verification compliance for the first time across 3,000+ properties
• Using our deep expertise in real user analysis to help a global automaker drive a 90% reduction in frontend errors, a 50% reduction in search results load time, and a 58% year-over-year reduction in outages
• Identifying the root cause of a performance issue impacting customers on one of the UK’s largest retail sites, which, when fixed, reduced exit rate by 2%, driving $500k+ of additional monthly revenue
• Working with senior executives and cross-functional teams at one of the world’s largest airlines to implement a holistic Business Observability strategy combining DEM, Business Analytics, and the broader Dynatrace platform to provide an end-to-end view of how infrastructure, services, and front-end applications impact critical business flows and KPIs in real time

Business Insights has long worked closely with Dynatrace customers to help accelerate adoption and value from the Dynatrace Digital Experience Monitoring (DEM) and Business Analytics capabilities; however, customer collaboration could be challenging at times with information scattered across emails and PowerPoint slides, multiple channels of engagement, and analysis disconnected from the Dynatrace platform. The Business Insights app simplifies and enhances the experience and engagement of Business Insights services, making it more seamless and accessible. It’s also the starting point for delivering more advanced AI-driven analysis, like those pioneered in the Opportunity Insights app.

Dynatrace delivers more value than its competitors

The Business Insights app directly addresses these pain points through unified, contextual delivery on the Dynatrace platform that transforms how insights are received, consumed, engaged with, and acted upon.​​​​​​​​​​​​​​​​

Bringing Business Insights into an app on the Dynatrace platform creates an enhanced experience of both the service and the platform through targeted, actionable analysis and recommendations directly in Dynatrace, in the context of the rest of the product, and with the ability to move seamlessly between them.

Timeline view: Your complete analysis history

As a Business Insights customer, keeping track of communications (enablement content, historical analysis, value over time, etc.), bringing new team members up to speed on the service, and summarizing value received over time for key stakeholders could be a challenge, with everything buried in emails. The Business Insights app centralizes all engagement and analysis in a single timeline view, making it easy to review everything the Business Insights team has provided for your organization, including:

• Analysis value moments
• Announcements
• Enablement material

Invites to live sessions such as Tech Talks and Customer Connects.

Each analysis value moment is tagged with helpful metadata, including type (performance, operational, business), product component (web, mobile, synthetic), application/synthetic monitor name, and specific page or event details. Enablement moments help you ramp up on the product more quickly, while announcements make sure you’re always up to date with what’s happening with the DEM and Business Analytics capabilities in the context of what matters to you. This comprehensive view helps new team members quickly understand your digital experience landscape and previous insights, accelerating onboarding for the service and Dynatrace DEM.

Value moment detail: Rich interactive content

Value moments are small and consumable DEM insights and analysis deliverables put together by our analysts for operational, performance, and business use cases to help you understand where to focus. Selecting a value moment from the timeline opens the main view with structured, easy-to-navigate content. Each value moment includes an optional video summary at the top for a quick overview, followed by indexed sections that allow you to jump directly to relevant information. Content links seamlessly to other Dynatrace Apps, Notebooks, and Dashboards for deeper context, eliminating the need to switch between tools. Each value moment also includes a shareable deep link, making bringing additional team members into the conversation simple. The structured, consumable content of value moments and easily navigable content help teams quickly identify focus areas and collaborate on operational decisions and actions.

Collaborative engagement and real-time feedback

The Business Insights app transforms analysis from a one-way delivery into a collaborative experience. Simply select any content within a value moment to leave comments or questions directed to the Business Insights team or your team members. Our team receives immediate notification and responds directly in the comment thread, keeping everyone aligned and in context. You’ll also receive email notifications with direct links when we reply. Threaded discussions and immediate notifications keep teams aligned and engaged with the Business Insights team.

Each value moment also includes a dedicated feedback section, allowing you to quickly indicate value and direct our future analysis and priorities.

Early feedback

The ability to easily provide feedback has been pivotal in quickly refining our interactions with the Insights team and the value we get from the service
– North American gaming company

By centralizing everything in one place, we’re inspiring people to use RUM and freeing them from digging through multiple tools and endless emails to find the context they need.
– UK insurance company

What’s next

The Dynatrace Business Insights app has been built to transform the way you engage with Business Insights and increase the value you receive from the Dynatrace platform, giving you:

• Centralized communication – All analysis, discussions, reports, and material in one searchable location
• Contextual engagement – See analysis in context of your real-time data within the product, with direct links to other apps/notebooks/dashboards
• Increased adoption and team exposure – Easy sharing of value moments with deep links, making insights more accessible across your organization
• Simplified collaboration – Comment directly on specific content to seamless interaction with Business Insights and your internal teams
• Historical access – Timeline view for easy tracking of past interactions, discussions, and analysis
• Self-service access – Anytime access to reports and insights without waiting for emails and calls
• Enhanced service through direct feedback – Simple, built-in mechanisms indicate value and guide future analysis

This first release is just the beginning, not merely a new interface but the foundation for next-generation Business Insights that will allow advanced machine learning and AI capabilities for enhanced analysis.

Get started

The new app is now generally available for Dynatrace Business Insights customers running a Dynatrace SaaS deployment. We’ll progressively roll the app out to existing customers over the coming weeks:

• If you’re interested in being part of the initial wave of adopters, please talk with your Dynatrace analyst or submit this form.
• If you’re not a Business Insights customer and are interested in learning more, please reach out to the Dynatrace Sales team.

___

© 2025 Dynatrace LLC

Dynatrace and the Dynatrace logo, are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners.

The post The Power of Business Insights expertise now directly on the Dynatrace platform appeared first on Dynatrace news.

When users land on your website, the digital experience is everything. A slow-loading page, unexpected layout shifts, or unresponsive interactions can frustrate potential customers—causing higher bounce rates, abandoned carts, and low search engine rankings. To combat these issues, Google introduced Core Web Vitals (CWVs): a set of metrics designed to measure and improve the user experience of websites.

Whether you’re a developer, product owner, or IT operations leader, understanding Core Web Vitals is no longer optional—it’s an essential part of delivering flawless and immersive digital experiences. But despite their importance, understanding and mastering these metrics can be just one more set of signals your team has to manage. To unpack—and demystify—Core Web Vitals, we’ll explore what they are, why they matter, and how you can seamlessly integrate them into your operations for enhanced insights and optimization using Dynatrace.

What are Core Web Vitals?

Core Web Vitals are three specific metrics that Google uses to measure the health and quality of a web page’s user experience (UX):

• Largest Contentful Paint (LCP). LCP measures loading performance. It records how long it takes for the largest visible element on a page—like an image or a block of text—to load. A “good” LCP score is under 2.5 seconds.
• Cumulative Layout Shift (CLS). CLS quantifies visual stability by measuring how often elements on a page unexpectedly shift while it’s loading—e.g., an image loading late and pushing text out of position. A “good” CLS score is 0.1 or less.
• Interaction to Next Paint (INP). Replacing First Input Delay (FID) in 2024, INP measures the overall responsiveness of a webpage, capturing how quickly it reacts to user interactions like clicks or keystrokes. A “good” INP score is under 200 milliseconds.

These metrics provide a foundation for website optimization aimed at creating faster, more stable, and more interactive web experiences.

Why are Core Web Vitals important?

Core Web Vitals aren’t just technical jargon—they directly influence a website’s user experience, business outcomes, and search engine rankings.

• Enhanced user experience. Page load speed is a crucial factor in how users experience a site, with over 50% of users saying they’ll abandon a page that takes more than 3 seconds to load. Core Web Vitals address this by ensuring pages are faster, more stable, and easier to use, contributing to lower bounce rates and better engagement.
• Improved SEO. Since 2021, Google has incorporated Core Web Vitals into its ranking algorithm, rewarding websites that meet these performance benchmarks. A high CWV score improves a website’s position in search results, which can boost organic visibility.
• Business impact. Poor site performance can significantly impact revenue. For example, an improvement of just 0.1 seconds in site speed has been shown to increase conversion rates by up to 8%. Core Web Vitals serve as actionable metrics to help businesses achieve these performance gains.

Why Core Web Vitals should be part of your observability strategy

Core Web Vitals help measure and monitor user experience and front-end performance. They are important metrics, but only one part of the picture on their own. When CWV are integrated into observability—which provides deep insights into the performance, health, and user experience of applications, infrastructure, and the business itself—organizations can understand why their Core Web Vitals measure as they do and how to improve them. Core Web Vitals help organizations improve:

• End-to-end observability. Monitoring Core Web Vitals via an observability platform offers visibility into user experiences across devices, browsers, and locations. Incorporating these metrics into your observability stack ensures no blind spots in performance data from front end to back end.
• Proactive optimization. Instead of reacting to complaints, monitoring CWVs helps teams identify and address issues proactively. For example, if LCP deteriorates due to slow server response, teams can take corrective action before it impacts users.
• Bridging technical and business metrics. Integrating Core Web Vitals into observability dashboards connects technical metrics to business outcomes, such as revenue or customer retention, making them easier to communicate to stakeholders.

Monitoring Core Web Vitals with Dynatrace today

Dynatrace goes beneath the Google Search Console by offering unparalleled insights into Core Web Vitals across both the front and back ends of applications to help you understand the drivers of CWV metrics. Here’s how it stands out:

• Full metrics integration. With zero setup required, Dynatrace incorporates LCP, CLS, and INP into its Real User Monitoring (RUM) and Synthetic Monitoring tools, delivering real-time and actionable insights.
• Anomaly detection. The Dynatrace Davis AI engine identifies the patterns or behavior that deviate from the norm impacting CWVs—whether it’s a slow CDN, inefficient JavaScript, or back-end latency—so teams can resolve them efficiently.
• Custom alerts and dashboards. Teams can define CWVs as key performance indicators (KPIs) and configure automated alerts, ensuring they’re notified of potential performance regressions instantly.

Enhancing support for INP

As mentioned above, Google replaced FID with INP recently. While FID was used to measure the responsiveness of the initial interaction on a page, INP observes all interactions on a page and reports the worst value.

In Dynatrace, customers can dashboard the built-in INP metric across various dimensions, such as front-end applications, browsers, and locations. In addition, a user can assess INP values via the front-end application overview screen, as well as page analysis screens, and filter for pages with the worst INP values to initiate improvements.

Maximizing the value of Core Web Vitals with Dynatrace

Optimizing Core Web Vitals isn’t a one-and-done effort; it’s an ongoing process for maintaining a high-quality user experience. Dynatrace will continue to strengthen support for Core Web Vitals to help teams maximize their value and deliver exceptional digital experiences.

With the latest Dynatrace advancements, the platform will provide more granularity of data captured with OneAgent as well as the analytics power of Grail. These capabilities will enable customers to go even deeper in monitoring, analyzing, and optimizing Google’s Core Web Vitals. This functionality is currently available on a trial basis in the preview program. Here’s a look at what the preview includes.

Seamless integration

Core Web Vitals are integrated into the new Dynatrace DEM apps, allowing users to understand the health across multiple KPIs at a glance and across monitored front-end applications. From the health overview, users can drill down into details about pages and views within their front-end applications to discover and optimize vitals across various dimensions.

Deeper analysis

With the power of DQL and ready-made Dashboards and Notebooks, users can drill deeper into the root cause of an issue related to web vitals. The following examples illustrate such an analysis with a ready-made Notebook for Core Web Vital analysis.

LCP analysis

For LCP, users can not only discover the pages with the slowest LCP but also identify the exact element that triggered the worst LCP values, simplifying the process for a developer or performance engineer to optimize page performance and user experience.

INP analysis

The ready-made Notebook also enables INP analysis. In this case, Dynatrace automatically captures the interaction that led to bad INP values and makes it easy to query across the monitored landscape with DQL. Developers and performance engineers can swiftly discover interactions that lack latency and require optimizations to reach better levels of user experience. With the context of the interaction type, tag name, and latency duration, users have all the context they need to make the right choices.

Take your digital experience to the next level

Core Web Vitals are no longer “nice-to-haves.” They’re essential metrics that define the digital experience of every user who visits your site. By understanding their importance and leveraging tools like Dynatrace, organizations can deliver faster, more stable, and more responsive websites—building trust and loyalty with their users.

Are you ready to take control of your Core Web Vitals? Start optimizing today with Dynatrace and experience the impact on your digital performance firsthand.

…

This blog may contain forward-looking statements about our product plans, upcoming features, and anticipated improvements. These statements are for informational purposes only and are not promises or guarantees. The development, release, and timing of any features or functionality described remain at the sole discretion of Dynatrace LLC and may be modified, delayed, or canceled without notice. We encourage readers to make decisions based on the product’s current capabilities and features.

© 2025 Dynatrace LLC

Dynatrace, Davis, Grail, OneAgent, and the Dynatrace logo are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners.

The post Why Core Web Vitals are crucial for optimizing digital experience appeared first on Dynatrace news.

The improved UI of the new Synthetic app makes managing your synthetic tests and analyzing their results easier and more effective. Exploratory analytics now cover more bespoke scenarios, allowing you to access any element of test results stored in the Dynatrace Grail™ data lakehouse. This allows you to build customized visualizations with Dashboards or perform in-depth analysis with Notebooks.

Traditional insight into HTTP monitor execution details

For nearly two thousand Dynatrace customers, Dynatrace Synthetic HTTP monitors provide insights into the health of monitored endpoints worldwide and around the clock. Customizable notifications about particular problems causing test failures are delivered as soon as the problems are discovered. This allows you to analyze issues and react immediately, ideally before your users are affected.

For more complex cases, where the basic information about an HTTP monitor’s execution failure delivered with a notification is insufficient, Dynatrace provides complete details of the last failed execution of said HTTP monitor. Analyzing the delivered payload (response body), response headers, or even details of requests sent during the monitor’s execution is invaluable when analyzing the failure’s root cause.

But nowadays, with complex and dynamically changing modern IT systems, the last result details might not be enough in some cases. And it was spotted and delivered to us as feedback from our customers within the Product Idea community:

“Currently, for HTTP monitors, only details for the last failed execution per location are shown. Sometimes, when there are several failures before that you weren’t able to track (like during the weekend or night), you have very few details of what failed.”

— DT community user

How the new Synthetic app better supports root cause analysis (RCA)

As always, Dynatrace listens to your feedback! Therefore, with the release of a new version of the Synthetic app supporting HTTP monitors, we’re happy to announce that HTTP monitors’ result details are no longer limited to the last successful and failed executions. Thanks to the power of Grail, those details are available for all executions stored for the entire retention period during which synthetic results are kept.

The new Dynatrace Synthetic app allows you to analyze these results. It now fully supports not only Network Availability Monitors but also HTTP synthetic monitors. The Refreshed Analyze Executions page has been enhanced with a scatter plot chart showing all executions of configured HTTP monitors.

Each dot represents an HTTP monitor execution. Select any execution you’re interested in to display its details, for example, the content response body, its headers, and related metrics. Details of requests sent during each monitor execution are also available. The filtering panel on the left-hand side of the page allows you to focus only on those elements that are critical for your analysis.

Your analysis might require comparing the details of two executions, for example, a current failing execution and a historical one when the test passed. Or perhaps you need to compare two failing executions, as the details of the first failure (for example, what happened overnight) might provide additional input for your analysis. With the new Dynatrace Synthetic application, you can select any two executions for comparison.

The Dynatrace platform supports your analysis

The benefits of HTTP monitors on the latest Dynatrace platform are visible not only within the new Synthetic app. All metrics and events storing information about execution details are available for further exploratory analytics utilizing Dashboards, Notebooks, or Davis^® CoPilot. This provides nearly endless possibilities for building customized reporting tailored exactly to your needs.

“Data in Grail available with DQL look very powerful; the possibility of combining response payload with info on how much time it (monitor’s execution) took looks very useful“

– Tim Buedts, IT Reliability Engineer at Telenet group

Within the new Synthetic app, we provide you with a link to a Notebook you can use for further analysis. The Notebook contains three predefined queries, which you can use to query events stored in HTTP monitor results.

Let’s take a look at the three included queries:

Query 1: Get events with information about all executions of a selected monitor within a given time range

This query, the most basic of the three DQL queries, returns the list of all executions of a given monitor, which is identified by its unique ID (dt.synthetic.monitor.id). The fields clause identifies which fields should be shown as a query result. A filter for the location ID (filter dt.entity.synthetic_location), commented out by default, can be used to narrow down the results to only the executions from the selected location.

fetch dt.synthetic.events
| filter dt.synthetic.monitor.id  == "HTTP_CHECK-75952DA89EB1DB45"
| filter event.type == "http_monitor_execution"
| fields timestamp, result.status.message, result.statistics.duration, result.status.code, dt.entity.synthetic_location, execution.type, event.id 
| sort timestamp desc 
// | filter dt.entity.synthetic_location == "SYNTHETIC_LOCATION-0000000000000001" 

Query 2: Get events with basic information about the results of each step within a selected monitor execution

The main difference with this query is the filter event.type == "http_step_execution" clause. This query returns basic information about all the steps of a single selected execution of the selected HTTP monitor. The execution is selected with the filter filter event.id == 100925201952 //event.id == execution id (Note that we’re using the ID from the latest execution as a default filter.)

fetch dt.synthetic.events
| filter dt.synthetic.monitor.id  == "HTTP_CHECK-75952DA89EB1DB45"
| filter event.type == "http_step_execution"
// | filter dt.entity.synthetic_location == "SYNTHETIC_LOCATION-0000000000000001"
| filter event.id == 100925201952 //event.id == execution id
| sort dt.synthetic.execution.end_timestamp desc
| fields timestamp, result.status.message, result.statistics.duration, result.statistics.connection_time, result.statistics.tls_handshake_time, result.status.code, result.statistics.time_to_first_byte, dt.entity.http_check_step

Query 3: Get events with full details describing a selected HTTP monitor execution

This query fetches data from different event type from dt.synthetic.detailed_events. It can be used to find detailed information about a selected monitor execution, which can be helpful during troubleshooting.

Commented-out clauses can be used to narrow the scope to a particular step of the executed monitor, and the step ID value (dt.synthetic.step.id) can be retrieved, for example, from the results of Query 2.

fetch dt.synthetic.detailed_events
| filter dt.synthetic.monitor.id  == "HTTP_CHECK-DD85DA9C14659614"
| filter event.id == 4184255792508795805 //event.id == execution id
// | filter dt.synthetic.step.id == "HTTP_CHECK_STEP-0000000000000000"

Synthetic results available in Grail also offer additional possibilities from a reporting and visualization perspective, combining various metrics and events on a single dashboard

Look at the example dashboard in Figure 5, built on the results of a synthetic monitor that checks the health of a popular weather service. Apart from metrics indicating availability and service performance, we created a pie chart showing the forecast weather for Gdańsk, Poland. Input data for the chart was extracted from the payload of responses provided by the weather service.

“It is great to see those events also for historical executions. We’d like to use it for our dashboards.”
— Engineer from a leading workforce solutions organization

The Dashboard presented above is an example of combining data retrieved with HTTP monitors execution within the response body (here, the information about the weather) with metrics describing the health of the service used for retrieving that data (in this case, availability and duration reported by HTTP monitor)

Here’s an example DQL query illustrating how to use DQL language to retrieve data from events (containing, among other values, the response body)

fetch dt.synthetic.detailed_events | filter dt.synthetic.monitor.id == "HTTP_CHECK-75952DA89EB1DB45"
| fieldsAdd content = result.statistics.response_body
| parse content, "JSON:query"
| fields timestamp, dt.tenant.uuid, query
| fieldsFlatten query
| fieldsAdd days = query.days[0]
| fieldsFlatten days
| summarize count(), by:{days.conditions}

Content of the response body collected from all executions of the HTTP monitor is collected and parsed as JSON. Then, the number of executions that returned a forecast of a particular weather type (returned in days.condition field) is counted.

Discover what you can do with HTTP monitors on the latest Dynatrace platform

• Create your HTTP monitors with the new Synthetic application.
• Check the results of your new (and existing) HTTP monitors.
• Get familiar with the out-of-the-box synthetic dashboard delivered with the new Synthetic. app! Check out the new dashboard within the Dynatrace Playground environment.
• Use the power of DQL to query synthetic data and report it with Notebooks and Dashboards.
• Share your feedback with us using our Feedback channel in the Dynatrace Community.

The post HTTP monitors on the latest Dynatrace platform extend insights into the health of your API endpoints and simplify test management appeared first on Dynatrace news.

We’re excited to announce that Dynatrace has been named a Leader in the inaugural 2024 Gartner® Magic Quadrant™ for Digital Experience Monitoring. We believe this recognition underscores our dedication to empowering organizations to achieve outstanding digital performance.

Digital experience monitoring enables frontend-to-backend observability

As digital transformation accelerates, the complexities of hybrid and multicloud environments have introduced observability challenges that can make it harder to deliver the exceptional experiences customers expect. Dynatrace digital experience monitoring (DEM) monitors and analyzes the quality of digital experiences for users across digital channels by collecting data from multiple sources. With real user monitoring, Session Replay, and synthetic monitoring natively built into the Dynatrace unified observability platform, organizations gain visibility into the challenges users experience when interacting with your website and mobile applications. Dynatrace helps to quickly understand the impact of these challenges and identify their root cause for faster remediation. This enables teams to optimize digital experience, improve customer satisfaction, and drive business results.

Observability for digital transformation

We believe this acknowledgment highlights our dedication to enabling organizations to achieve seamless digital transformation. We equip our customers with the insights necessary to enhance user experiences and improve operational efficiency. Unlike traditional monitoring services, Dynatrace offers end-to-end observability that delivers precise, real-time data on application performance issues, complete with the context needed for rapid problem resolution and prioritization by business impact. By harnessing the power of three AI techniques—causal, predictive, and generative AI—Dynatrace analyzes billions of data points, providing customers with a unified perspective to drive their digital transformation efforts.

Additional Gartner recognition

For us, being recognized a Leader in Digital Experience Monitoring signifies more than just meeting industry standards; we see it as highlighting our capability to partner with customers to deliver results against their digital strategies, enabling them to proactively manage their digital environments and drive business growth.

This recognition comes in addition to the company’s acknowledgment as a Leader positioned furthest for Vision and highest in Execution in the 2024 Gartner Magic Quadrant for Observability Platforms and its ranking as #1 in the Application Health and Performance Monitoring (4.27/5), Hybrid Infrastructure/Platform Operations (4.25/5), and Business Insights (4.22/5) Use Cases in the 2024 Gartner Critical Capabilities for Observability Platforms Report.

Dynatrace named a Gartner Peer Insights™ Customers’ Choice for Digital Experience Monitoring

In the 2024 Gartner Peer Insights™ Voice of the Customer for Digital Experience Monitoring report, Dynatrace was the only vendor named a Customers’ Choice based on 132 reviews as of February 2024.

Here is what customers say about Dynatrace:

• “Using Dynatrace, we are able to monitor the user’s experience like we have never done before.”
• “Dynatrace is an easy-to-deploy, powerful solution to see your customers’ journey.”
• “Dynatrace DEM provided us with extended monitoring beyond APM.”

At Dynatrace, we’re honored to be recognized as a Customers’ Choice in digital experience monitoring by Gartner. We believe this acknowledgement reflects our continuous effort to innovate and improve, always with the goal of helping our customers deliver better digital experiences. We’re proud of the progress we’ve made together and remain committed to helping organizations navigate an ever-changing landscape.

Download the 2024 Gartner® Magic Quadrant™ for Digital Experience Monitoring for more information. 

__________________________________________________________________________

^{Gartner Disclaimers} 

^{Gartner, Magic Quadrant for Digital Experience Monitoring, Padraig Byrne, Matt Crossley, DB Cummings, Martin Caren, Pankaj Prasad, 21 October 2024}   

^{Gartner, Magic Quadrant for Observability Platforms, Gregg Siegfried, Padraig Byrne, Mrudula Bangera, Matt Crossley, 12 August 2024} 

^{Gartner, Critical Capabilities for Observability Platforms, Gregg Siegfried, Padraig Byrne, Mrudula Bangera, Matt Crossley, 12 August 2024} 

^{Gartner, Voice of the Customer for Digital Experience Monitoring, Peer Contributors, 24 April 2024} 

^{Gartner® Peer Insights™ content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.} 

^{Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.}  

^{GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally. MAGIC QUADRANT and PEER INSIGHTS are registered trademarks of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.} 

The post Dynatrace named a Leader in inaugural 2024 Gartner® Magic Quadrant™ for Digital Experience Monitoring appeared first on Dynatrace news.

When I founded Dynatrace, I aimed to bridge the gap between IT performance and user experience. My goal was to provide IT teams with insights to optimize customer experience by collaborating with business teams, using both business KPIs and IT metrics.

To accomplish this, we traced all digital interactions from device to backend for detailed insights into personalization impacts. Using causal AI, we identified and resolved performance issues automatically. Recently, we’ve expanded our digital experience monitoring to cover the entire customer journey, from conversion to fulfillment.

Shifting to customer-centric IT  

For observability data to be meaningful, it must connect the performance of IT systems to customer experience throughout their journey, across both digital and physical touchpoints. Only then can executives understand whether their software helps to deliver the intended business outcomes.

Dynatrace has been built from the ground up to observe, analyze, and protect customer interactions end-to-end by unifying observability, security, and business data in context. This combination boosts your analytics abilities while also saving costs by consolidating observability, real-time user behavior, and session replay tools within a single platform.

Dynatrace helps executives take the same proactive approach to customer experiences by addressing the following five critical needs:

1. Understand the customer’s business process, including identification of pain points and automation opportunities.
2. Identify where the customer journey can be optimized to improve retention rates.
3. Find ways to boost satisfaction, increase conversions, and accelerate business growth.
4. Automate root-cause and customer impact analysis.
5. Accelerate complaint resolution and establish preventive measures and controls.

Avoid the cost of customer churn by optimizing customer experience

85% of unhappy customers would make the extra effort to go to a company that has better customer service. In 2024, acquiring a new customer costs five to 10 times more than retaining an existing one. Specifically, it can be up to seven times more expensive to attract a new customer compared to keeping one. Additionally, existing customers tend to spend 67% more on average than new customers.

This data speaks to the importance of investing in digital experience and loyalty, which many executives do. However, not many realize the efficiencies they can gain when data from all customer experience processes – observability, customer behavior, and business data – is in a single place, as it is with the Dynatrace Grail data lakehouse. Real-time customer experience remediation identifies and informs the organization about any issues and prevents them in the experience process sooner.

Achieve unparalleled agility and customer satisfaction

As today’s customer experiences span direct access (through web, mobile, and IoT) and indirect access (through APIs, messaging, logistics, and other forms of interactions), customer journeys are omnichannel. This shift highlights the value of observability for a complete and holistic understanding of user journeys. The steps across devices, APIs, server-side service invocations, and information from the inner workings of services can be used to gain a complete understanding of omnichannel user journeys and their associated customer satisfaction and business success.

Dynatrace unifies data from digital and physical touchpoints in a single platform and creates an end-to-end view into the following:

• The performance, reliability, and user experience supported by applications.
• The security, privacy, and regulatory compliance standards of digital services.
• The end-to-end experience for every customer throughout the entire process.

With these insights, you can act on improving the reliability, performance, and user experience of your entire customer journey. This can include live interactions as well as asynchronous interactions across all service touchpoints, whether that’s an order being shipped or a suitcase arriving at the same airport as its owner.

The Dynatrace platform’s granular insights also empower development teams to innovate more effectively so they can deliver faster change, helping executives improve customer experience.

Dynatrace’s advanced digital experience management capabilities, including Session Replay, provide unparalleled visibility into the customer journey. Our customers frequently run team meetings to visually review customer sessions to better understand issues with experiences. Typically, without session replay, if a customer experiences a problem, the IT team logs into an admin account or looks for errors in logs, but often doesn’t find anything wrong. With Session Replay, they can directly replicate what the customer saw and identify the exact problem they are describing. That result can be automatically documented and passed to the development team, providing them with full context of the problem. Session replay sessions are anonymous, having implemented highest standards in the market for privacy management.

User experiences go into many dimensions: business events, dashboards, session replay, synthetic checks which help with performance, reliability, and experience of digital interactions.

A proactive approach to analytics

One of several reasons to observe real user behavior instead of running synthetic tests is that modern applications serve different and individualized content. Personalization, user profiles, pertinent customizations, user permissions, and so forth make almost every web or mobile page unique in their behavior and how they access the backends. Hence, only deep, end-to-end insights can provide the actionable information required to improve experiences and complement common marketing-related analytics tools (e.g. Google or Adobe Analytics).

Analyzing real user behavior with end-to-end context provides value to many use cases, including the following:

• React to issues faster, automate, and quantify the customer impact with the help of Dynatrace AI.
• Optimize business outcomes (revenue/business goals vs. cloud cost and R&D effort) towards inflection points of business goal vs. experience through unified technical, experience, and business data analytics in a single space.
• Improve software delivery by observing customer success on a subset of customers first before going broad (for example, progressive delivery, dark launches, and A/B testing) with Dynatrace support for feature flags and software delivery observability.
• Eliminate finger-pointing as end-to-end visibility connects the data points across departmental needs. Finally, as an executive, you have the means to quickly identify the right team to fix and improve.
• Prioritize investments in new features vs. improvements by better understanding actual customer experiences, utilization, satisfaction, sentiment, and errors. For example, if you have too many rage clicks, you likely want to spend the next sprint on experience improvements vs. new features.
• Automate smarter using actual customer experience metrics, not just server-side data.

All of these use cases go beyond commonly used analytics tools. Dynatrace collects information from the front-end and APIs, backend, and the inner workings of services in full context.

Finally, I hear from executives that while they can leverage Dynatrace to get the best out of their data, they sometimes need additional expertise so that their teams know where to focus and what to act on. This expertise can often come in the form of a Dynatrace partner and our Business Insight team (or both). The Dynatrace Business Insights team are global experts who can help executives get to the platform’s value faster. And by leveraging precise data modeling, the Business Insights team can help executives understand how to strike the balance between optimization of customer experience and investing in new features.

The post Breakthrough insights into customer experiences with Dynatrace to accelerate business growth appeared first on Dynatrace news.

Performance and error optimization is complicated, and the approach to driving improvement has long relied on static recommendations disconnected from a site’s end users and their experiences. While traditional methods can help you understand when your users face poor performance or errors, understanding if and how much these problems impact your business remains largely guesswork. The new Opportunity Insights app (available to subscribers of the Dynatrace Business Insights service) takes an industry-first approach to shift this paradigm: using predictive AI on top of your application’s historical real user data, we identify the primary performance/error metric impacting user experience on each page and quantify the predicted business impact of recommended optimizations. With this information, business and application owners are empowered to make decisions based on their impact on the bottom line.

Performance, errors, and user experience

Dynatrace has long understood the importance of performance as a foundational component of user experience and the impact that page speed and any friction introduced by errors have on user behavior. When a page is slow to load, users are quick to abandon the site; research by Google, Vodafone, and others has repeatedly shown that even small (~100 ms) degradations in page performance can increase abandonment, lost revenue, and lead to persistent changes in user behavior. Additionally, JavaScript or HTTP errors that impact a page’s functionality or overall experience can be even more immediate and lasting, leaving users with the impression that a site’s problems reflect the brand, leading to a longer-lasting negative impression.

Despite this broad, conceptual understanding of the importance and impact of poor performance and errors on end users, it’s difficult for site owners to fully understand and quantify the experience of their unique site on its users. Until now, the best approach was to take generic, static recommendations based on the experience of large internet brands and their user bases, apply them to a site, and hope to see improvement in the business. Sometimes, these recommendations are so far from current performance or cost so much to implement that they seem irrelevant or unattainable. The addition of more and more metrics over time has only made this increasingly complex. As a result, it’s challenging to get business and resources focused on performance and error optimization without supporting data that shows how those optimizations will impact your organization’s financial outcomes.

Site owners and businesses are left asking where they should invest and what exactly they should optimize to balance the best experience for their users with the least amount of effort that will lead to improvements in the business.

Performance and errors in context

What if you could answer the question, “What is the smallest change I can make to this page to maximally reduce user-exit rates and improve conversion rates?”

With Opportunity Insights, Dynatrace uses predictive AI and your site’s real user data to identify opportunities where improvements in performance and errors can make the most significant difference in retaining users and sessions while reducing exit rates and converting more customers.

To provide precise, contextual recommendations for performance and error improvement on a given page, Opportunity Insights does two key things:

• First, it looks at user behavior and performance/error metrics across millions of sessions and identifies which candidate metrics show the most significant impact on user experience and should be considered a metric to improve. Performance metrics to improve can be Visually Complete, Speed Index, or other timing metrics associated with the page load cycle.
• Opportunity Insights then predicts the business impact of improvement in those metrics and suggests a target for the most significant return on effort,” expressed as an increase in retained sessions, conversion percentage, or revenue per month.

From an underlying list of hundreds of opportunities, Opportunity Insights surfaces the Top 3 opportunities that will provide you with the most significant return on effort.

How we do it

Opportunity Insights’ predictive AI is powered by a patent-pending structural causal machine learning model (connecting the cause and effect of performance, errors, and behavior) that is trained on each application’s unique real user session data across millions of sessions to analyze errors, performance metrics, and behavior patterns. It looks at these metrics across key pages to pinpoint where your users are most impacted and which metric directly impacts each page.

With this deep understanding of the intersection of performance, errors, and real user behavior, Opportunity Insights simulates over 650 million possible scenarios of performance improvement per application to surface precise recommendations for optimization that will yield the most significant increase in retained sessions for the least amount of effort. Armed with this prediction, it’s easy to understand the potential payoff of improvements and better prioritize your development efforts.

In evaluating our model’s accuracy in understanding performance/errors and behavior, we use historical real user data and a standard 80-20 train-test split to train our model. It predicts user behavior based on performance/error experience. We’ve tested it across various applications and industries, and it accurately predicts user behavior about 90% of the time. When the suggested metric is optimized, the user-exit rate drops, and the number of additional retained sessions increases as predicted.

We also tested our business impact prediction in real-world scenarios. We used customer applications where our model identified improvement opportunities. After implementing the suggested optimizations, we found that ~20% more users and sessions were retained than predicted, showing that our model’s predictions are conservative.

Early user feedback

Preliminary user feedback validates the ability of the app to help application teams, and owners quickly and easily understand where to optimize and the business impact of optimizations. Here are a few customer highlights:

• The director of e-commerce at a leading budget airline stated, “This is exactly what we need [in our decision-making], connecting application performance and business outcomes.”
• The IT Manager of a leading US insurance company stated, “This aligns with the direction we are taking the company, which is to make decisions based on business impact.”
• A platform monitoring manager from a leading payment company stated, “Honestly, this should be driving where they (the teams) are doing bug fixes and performance improvements.”

Get started

Opportunity Insights is available with the Dynatrace Business Insights service. It was released to a subset of Business Insights customers as a preview in April 2024 and is now generally available with Dynatrace version 1.296.

Download the whitepaper to learn more about the technology underlying Opportunity Insights and how you can quickly understand where to strategically invest development resources so they have the greatest impact on your business.

If you’re already a Business Insights customer and want to learn more, please contact your Insights Team. If you’re not a Business Insights customer but are interested in Opportunity Insights and the value Dynatrace Business Insights can bring your customers and your business, please contact your Dynatrace Account Executive or Customer Success Manager.

The post Dynatrace Opportunity Insights uses AI prediction and real-user data to optimize business outcomes appeared first on Dynatrace news.

Navigate digital infrastructure complexity

In today’s rapidly evolving digital environment, organizations face increasing pressure from customers and competitors to deliver faster, more secure innovations. The complexity of IT infrastructure management continues to grow, and each new application deployment and every change in infrastructure potentially impact user experience.

In some cases, managing your digital infrastructure is like playing Jenga, where the placement of every piece is critical, and the smallest change can destabilize the entire structure. On one hand, the complexity of systems demands precise control; on the other, staying competitive requires frequent updates and rapid service enhancements. This dynamic creates a challenge: keeping the tower stable while continuously adding and removing pieces.

To keep up with current demands, DevOps and platform engineering teams need a solution that can fully embrace and understand complexity, delivering precise answers that enable the creation of trustworthy automation. The effectiveness of this automation relies on the quality of the underlying data. Observability, therefore, has become crucial in DevOps, offering insights into IT infrastructure stability, performance, and user experience. The DevOps Automation Pulse 2023 report notes that 78% of organizations employing observability-driven automation experience faster incident response and resolution times.

Synthetic monitoring enhances observability by enabling proactive testing and monitoring systems to identify potential issues before they quickly impact users. Returning to the Jenga metaphor, synthetic monitoring observes the tower from a distance, from the end user’s perspective, and triggers instability warnings immediately. Incorporating synthetic monitoring and observability-driven automation can greatly streamline the workflow for DevOps teams, allowing for continuous improvements in system reliability and efficiency.

Automation + Synthetic = Perfect match

This is why we integrated Dynatrace Synthetic Monitoring into Workflows. With this enhancement, Dynatrace can respond to any event and execute synthetic monitors within your workflows to assess the impact of events on user experience. Depending on the outcome, workflows can notify your teams by creating a Jira ticket, sending a Slack message, or initiating a remediation process. This enhancement improves reaction time to incidents impacting user experience and simplifies incident management. It reduces the time spent verifying the impact of changes and engages DevOps or platform engineers only when necessary, allowing them to focus on more strategic initiatives.

With the intuitive and easy-to-use web UI of Workflows, you can quickly build automation based on synthetic monitors with just a few steps, thanks to a dedicated Synthetic for Workflows task.

In the first step, you choose which monitors to execute. You have three options:

• Select a fixed list of monitors.
• Provide a list of tags; all monitors with the tags will be selected.
• Provide a list of applications; all monitors associated with those applications will be selected.

You can also provide a list of monitors, tags, or applications in the incoming event and extract the list using an expression, which allows you to build a generic workflow.

Use case: Automated release validation

Integrating Dynatrace Synthetic Monitoring into delivery pipelines is a strategic move that ensures all critical user journeys are validated as early as possible, whether a release involves minor bug fixes, updates to a microservice, or an entire monolithic application.

This integration is particularly valuable in progressive delivery models like canary deployments. In such scenarios, a new version of an application is initially rolled out to a small portion of users. By adding a synthetic user as “user zero,” the risk of negatively impacting real users is significantly reduced.

Combining Synthetic for Workflows with Site Reliability Guardian (which evaluates adherence to availability, performance, or security objectives based on synthetic results) automatically determines whether the given application version should proceed in the delivery pipeline. This integration facilitates the easy construction and implementation of solutions that enhance automatic release validation.

Use case: Digital infrastructure change

The problem is not always in the application. As illustrated by the Jenga game metaphor, even minor changes in complex infrastructure can topple the entire tower. In 2021, Facebook and its other platforms, Instagram and WhatsApp, experienced a major outage. This global outage lasted for several hours and affected billions of users worldwide.

Interestingly, the applications were functioning perfectly; the root cause was a configuration change in the backbone routers.

Incorporating synthetic monitoring directly into deployment pipelines ensures that every infrastructure modification—regardless of scale—is automatically validated against performance and functional criteria.

This integration is particularly valuable within GitOps frameworks, where infrastructure changes are managed through code and deployed automatically. Synthetic monitors can simulate API clients and mimic user behavior, enabling IT teams to evaluate the impact of changes. Such preemptive testing significantly reduces potential downtime and mitigates performance degradation.

Synthetic for Workflows and Site Reliability Guardian can—continuously or on-demand—verify that all infrastructure modifications meet SLOs from the perspectives of users and API clients.

Use case: Custom synthetic scheduling

The traditional approach to scheduling synthetic monitors involves fixed intervals, which don’t always align with the varying operational demands of modern digital environments.

Workflows in Dynatrace provide a powerful mechanism for triggering tasks in response to various platform events. By leveraging Synthetic for Workflow combined with this event-driven architecture, you can achieve a level of customization in scheduling synthetic monitors that goes beyond the capabilities of the built-in synthetic scheduler.

This flexibility is particularly useful in scenarios where operational conditions can change rapidly. For instance, if a peak load period triggers a test failure, Synthetic for Workflow can initiate retries until the load stabilizes. This retry logic can help triage the problem and ensure that monitoring results are accurate and reliable.

Conclusion

By integrating Dynatrace Synthetic Monitoring with Workflows, Dynatrace offers a comprehensive solution for evaluating the impact of infrastructure changes, enhancing release validation, and improving custom scheduling. However, utilizing Synthetic for Workflows extends beyond these use cases, enabling the easy construction of any automation based on synthetic monitors, where assessing the impact on user experience is crucial.

The post Automate digital excellence with Dynatrace Synthetic Monitoring and Workflows appeared first on Dynatrace news.

Current synthetic capabilities

Dynatrace Synthetic Monitoring is a powerful tool that provides insight into the health of your applications around the clock and as they’re perceived by your end users worldwide. As HTTP and browser monitors cover the application level of the ISO /OSI model, successful executions of synthetic tests indicate that availability and performance meet the expected thresholds of your entire technological stack. Combined with Dynatrace OneAgent®, you gain a precise view of the status of your systems at a glance. But is this all you need?

Why browser and HTTP monitors might not be sufficient

In modern IT environments, which are complex and dynamically changing, you often need deeper insights into the Transport or Network layers. Whether necessary as part of deep root-cause analyses of issues faced by your users that impact your business or if you’re an engineer responsible for the infrastructure hosting your applications and network paths. You want to be able to answer questions like these:

• What is responsible for application slowdown? Is it a bug in the codebase, a malfunctioning backend service, an overloaded hosting infrastructure, or perhaps a misconfigured network?
• Are all network devices up and running, and is the network providing reliable and swift access to your systems?
• Do I have reliable and up-to-date info on the health of services that are not HTTPS-based but are still crucial elements of your business-critical systems?
• Are the hosts on which OneAgent can’t be deployed for technical reasons (for example, a legacy OS) or security-related reasons (for example, systems processing financial information and third party vendors) up and running? Are the corresponding services running on those hosts?

“ICMP ping tests in NAM are highly valuable and complement the overall value provided by the Dynatrace platform. They enable effective monitoring for devices where OA (OneAgent) cannot be applied due to technical or policy constraints.”

Robert Jędrzejewski– Senior Project Manager, BNP Paribas Bank Polska Spółka Akcyjna

How Dynatrace addresses these questions

Traditionally, Dynatrace provides powerful Platform extensions, which might answer all the above questions. However, those solutions have certain limitations:

• They are not scalable as a pure synthetic solution powered by an API for quickly defining and maintaining tests. Thus, covering an infrastructure the size of several thousand hosts, which is not unusual in modern enterprises, might be significantly challenging.
• Even though these issues were addressed with Extensions Framework 2.0, Synthetic Monitoring still boasts its own advantages with the combination of NAM and HTTP/Browser tests from the same location as well as higher capacity ActiveGates.

To help you enjoy a new and more powerful solution, we’re launching a tool that facilitates the automatic transformation of your existing extensions based on EF1.0 into NAM test definitions. Our script, available on GitHub, provides details.

Why Dynatrace NAM is the solution you need

Ease of deployment and management

Synthetic NAM monitors are executed from the same private locations used for monitoring your internal applications with HTTP and browser monitors. This guarantees oversight into high availability, as test executions are load-balanced between nodes hosting private locations.

Also, the API can be used to manage tests at scale, the same way you might use APIs to manage all other synthetic tests. This simplifies solution deployment (as it is available for current DT synthetic users) and managing tests covering a massive number of devices or services.

Test customization

Even though ICMP pings are not the most sophisticated tests, certain customization options can help tailor tests to your needs. For example, you may select the number of packets sent during each execution of the test (to mitigate the risk of temporary anomalies in the network that could impact your test result) and packet size (for example, to ensure that the given MTU is defined on the whole network path).

Of course, it is also possible to define the required success rate of ICMP packets for each test execution against a given IP address to determine if a test is successful.

Compared to other solutions I have tested, Dynatrace NAM monitors are the most configurable which is to my liking. We are already using three or more packets within all of my ping tests and see customized packets size as a valuable option for the future.

Observability Lead, Ivy League University

Similarly, you can adjust your TCP port check tests to validate if selected ports are not opened or closed as intended. Sometimes, the desired state of a port is not to accept connections. You might want to use a port to validate if security settings are properly applied and if ports that are supposed to be closed are closed.

Easier test management and integration with infrastructure monitoring tools

A single NAM test can cover one host (for ping) or socket (for TCP port check); however, you can make your life easier by creating single tests covering multiple (up to 1k) hosts at once. Whether you aim to check all addresses from a given IP list with ping tests, you can succeed with a single test! Similarly, a single TCP test can check if connections are accepted on multiple ports of one or more hosts.

But we went one step further here. Dynatrace NAM stands above all other competitive offerings because you can define a single ICMP ping test covering all hosts within a given host group (optionally narrowing down the IP addresses to a given range). The beauty of this solution is that even if the configuration of the host group changes, the configuration of your synthetic test stays up to date with no extra action needed.

Of course, the reporting side is properly adjusted to handle such monitors. For each failed monitor and each problem triggered as a result of such a failure, you can easily identify which requests (IP addresses, sockets) are responsible for the failure and might require appropriate attention.

How NAM tests work

You can use the API or our new web UI (Dynatrace SaaS only) to create NAM tests.

The new Synthetic app covers the configuration and reporting of network availability monitors thanks to the power of Grail™ and the new Dynatrace platform.

NAM monitors are defined in a similar manner to other synthetic monitors. Apart from elements specific to the given type of test, such as:

• IP address and number of packets for ICMP ping
• Port number for TCP port check
• Names to be resolved and DNS server for DNS tests

All other elements (like assigning locations or conditions for triggering alerts) are the same as those used in other Synthetic monitors.

The reporting also looks similar; there are easy-to-understand charts indicating the availability and performance of the whole network availability monitor, as well as metrics providing an overall summary and links to currently opened problems.

For more complex network availability monitors covering multiple requests, you might like to look at the chart presenting the request success rate, which shows a list of all requests in the form of a table or a separate chart reporting executions of separate requests.

NAM is available for Dynatrace Managed users

While the new, Grail-powered Synthetic app is available only in Dynatrace SaaS environments, Dynatrace Managed users can also benefit from NAM. Dynatrace Managed users get:

• A powerful API for creating and managing synthetic tests (the same as for Dynatrace SaaS users).
• A set of metrics allowing query results with Data Explorer and creating advanced reporting using Dynatrace Dashboards.
• Basic reporting, available out of the box, provides insight into values of the most important metrics describing the execution of all monitors and indicating which requests might be a reason for failures or slowdowns.

Next steps

• Get familiar with the new Synthetic app! It currently fully supports NAM monitors, but a preview of HTTP monitors will start soon.
• Find out how Synthetic NAM monitoring affects your billing on DPS and classic.
• Expect an easy way of integrating NAM monitors with network devices monitored within the IO app (coming soon).
• Configure NAM monitors directly from the Discovery and Coverage app (coming soon).

The post Dynatrace extends Synthetic Monitoring capabilities with Network Availability Monitors to validate the availability of infrastructure and services appeared first on Dynatrace news.

When it comes to critical applications and environments, organizations can’t afford to leave any stone unturned, as IT unknowns can have significant consequences. Any gaps, slowdowns, or potential issues can have a significant effect on an organization’s success — or lack thereof.

This is where observability analytics can help. Here’s a look at how it works, what it does, and its role in ensuring reliable operations.

What is observability analytics?

Observability analytics enables users to gain new insights into traditional telemetry data such as logs, metrics, and traces by allowing users to dynamically query any data captured and to deliver actionable insights. By connecting the dots between multiple points of observation, teams can take action to identify any potential issues or insights and understand it all.

With an all-source data approach, organizations can move beyond everyday IT fire drills to examine key performance indicators (KPIs) and service-level agreements (SLAs) to ensure they’re being met. They can identify and analyze trends to determine what short- and long-term futures may look like. And they can create relevant queries based on available data to answer questions and make business decisions.

Breaking down the benefits of observability analytics

Observability analytics offers organizations several benefits, including the following:

Uncovering unknown unknowns

Unknown unknowns are answers without questions. While measuring app response time under different circumstances provides a latency value, for example, it doesn’t tell you why the app is slow, fast, or somewhere in between. These unknowns are often tied to the root cause of IT issues.

Observability analytics can help teams solve for unknown unknowns. By analyzing the big picture of IT operations — including logs, metrics, traces, security reports, and usage data — and combining the output with advanced AI tool sets, organizations can conduct exploratory analytics that go beyond the surface to discover the why behind the what.

Breaking down data silos

Data silos remain a challenge for organizations. According to recent survey data, 79% of knowledge workers said teams in their organization are siloed, and 68% said these silos negatively affect their work. Part of the problem is time wasted searching for data, with workers reporting an average of 11.6 hours lost per week.

If teams can’t find the data they need when they need it, productivity declines. Collaboration is also challenging if teams need to work in tandem but have access to different data sets and applications.

Observability analytics can help identify and break down silos, providing common ground for inter-team efforts.

Democratizing data consumption

Democratizing data consumption means making data available and accessible. While many employees are familiar with IT processes, few are trained data practitioners. Observability platforms make it possible to capture and contextualize data, creating a shared foundation for staff.

Weighing the challenges of observability analytics

Implementing observability analytics comes with potential challenges. Common concerns include managing tool sprawl, creating context, and validating output.

Managing tool sprawl

More observability tools means more data — and more complexity. Consider that the average multicloud environment includes at least 12 different applications and services. To effectively monitor and manage these services, organizations often rely on multiple monitoring tools, each with its own feature set and focus. In some cases, these features overlap. In others, there may be gaps in observability that organizations can’t see.

Part of implementing effective observability, therefore, is minimizing the number of tools required to deliver actionable insight.

Creating context

Data without context is just noise. Best-case scenario: This noise distracts from but doesn’t derail effective analytics, costing companies time. Worst-case scenario: It becomes part of the decision-making process, potentially costing time and money.

Put simply, context is king. If solutions can’t provide context for collected data, they can do more harm than good.

Validating output

Analytical outputs aren’t guaranteed. Consider the recent rise of natural-language input AI tools. While these solutions make it easy for users to ask questions and get answers, these answers are only as accurate as the data available to the AI model. If the data is incomplete or inaccurate, so is the output. As a result, regular validation is critical to ensure accurate results.

Three components of successful observability analytics

Effective observation doesn’t happen automatically. Three components are critical to set the stage for successful observability analytics.

1. Automation

Based on the sheer volume and variety of data available to observability tools, IT automation is critical to ensure efficient operations. While human oversight is required to ensure outputs meet expectations, relying on manual processes to collect and correlate data is no longer feasible. In practice, teams need a combination of infrastructure and operations, digital processes, and automation tools to ensure information is effectively handled at every step of the observability process.

2. Streamlined data collection

Organizations also need tools that enable streamlined data collection. In practice, this means finding and implementing solutions capable of collecting data from multiple sources — such as cloud environments, co-located data centers, and on-site servers — and extracting key insights from this data, regardless of format.

This means observability solutions must be equally proficient at extracting structured usage from cloud services as they are at capturing data from on-premises mainframes.

3. Data lakehouse

Data lakes are a cost-efficient way to store information, while data warehouses provide contextual, high-speed querying capabilities. To make the most of observability analytics, organizations need both.

A data lakehouse such as Dynatrace Grail can combine the best features of lakes and warehouses, allowing them to effectively handle analytical and machine learning workloads.

Common use cases to consider

While observability analysis has no set boundary and can be used in any business application, several use cases are commonplace.

Exploratory analysis. Exploratory analytics enables teams to explore IT environments with observability solutions to discover unknown dependencies, interactions, or outcomes that help identify root causes.

Metrics-based performance thresholds. By observing current processes and outcomes, organizations can map these results onto service-level objectives, SLAs, service-level indicators, and KPIs to establish baselines and outliers. This allows for the creation of performance-based thresholds tied to concrete, observable metrics.

Consider the Dynatrace Carbon Impact app, which provides an overview of your current carbon footprint compared to previous time frames and recommendations to reduce your overall impact. By leveraging observability analytics, organizations can establish a baseline carbon footprint level along with emissions targets and upper limits that trigger a notification event when reached.

Predictive analysis. Complete visibility of IT infrastructure sets the stage for predictive analytics that can help inform key business objectives. For example, observability analytics can provide data on current infrastructure usage and any bottlenecks or performance problems. Equipped with this data, teams are better prepared to anticipate application, bandwidth, and security needs over time, streamlining the infrastructure scaling process.

Taking observability analytics to the next level

With Dynatrace, observability comes standard with built-in solutions. Here are the main functions teams can use to discover new insights:

Data forecasting. With Dynatrace Grail and Davis AI, organizations can predict capacity demands and make proactive changes. Using the Dynatrace Query Language (DQL), they can analyze all data stored within the Dynatrace Grail data lakehouse for any given time series. Davis AI then analyzes the time series and automatically chooses the best prediction model.

Predictive analytics. Davis AI can also help predict the impact of multiple workflows on business operations. This assists with long-term capacity planning and helps IT leaders make short-term decisions that boost operational efficiency.

Exploratory analytics. Using Dynatrace Notebooks, teams can carry out exploratory analytics for observability, security, and business data analysis. With Notebooks, users can collaborate using code, text, and rich media to build and share insights.

With observability analytics powered by Dynatrace, teams are better equipped to discover unknown unknowns, understand their impact, and take action that improves business operations. For more information on observability analytics from Dynatrace, check out our website.

The post How observability analytics helps teams uncover answers appeared first on Dynatrace news.

Customer and employee expectations for seamless, high-quality digital experiences are continually rising. Digital experience monitoring (DEM) is crucial for organizations to meet this demand and succeed in today’s competitive digital economy. By proactively implementing digital experience monitoring best practices and optimizing user experiences, organizations can increase long-term customer satisfaction and loyalty, drive business value, and accelerate innovation.

DEM solutions monitor and analyze the quality of digital experiences for users across digital channels. They collect data from multiple sources through real user monitoring, synthetic monitoring, network monitoring, and application performance monitoring systems. This data provides organizations with end-to-end visibility of the entire user journey across the tech stack. It also enables ITOps to identify performance issues in real time for fast mean time to detect/repair and to continuously optimize performance to improve the overall user experience.

How to improve digital experience monitoring

Implementing a successful DEM strategy can come with challenges. Depending on where an organization is on its journey, these challenges may include the following:

• Digital ecosystems complexity
• Data overload
• Existing IT systems and cloud frameworks integration
• User experience variability
• Business objectives alignment
• Data privacy and security
• Scalability

Addressing these challenges requires a combination of IT process improvements, clearly defined objectives, and organizational alignment.

Here are 10 digital experience monitoring best practices that can improve a DEM solution’s effectiveness and enhance the quality of your organization’s digital offerings.

1. Identify and review key user journeys

Understanding users’ paths when interacting with your applications provides a roadmap of how a customer or employee interacts with your services. To start, define different user journeys within your digital application and create a visual map from start to finish. Was the user able to accomplish their goal?

The map should illustrate every step a user takes as they interact with different pages, forms, and features. It can help understand the flow of user interactions, identify areas for improvement, and drive a user experience strategy that better engages customers to meet their needs. Review and refine key user journeys at set intervals to ensure maps are up to date and relate to clear business goals.

2. Define monitoring goals and user experience metrics

Next, define what aspects of a digital experience you want to monitor and improve — such as website performance, application responsiveness, or user engagement — and prioritize what to measure for each application. This allows ITOps to measure each user journey’s effectiveness and efficiency.

Align business and development teams’ input on what user experience metrics to measure to understand users’ most critical digital experience aspects. Prioritize monitoring efforts to ensure the performance metrics align with your organization’s goals and user expectations.

Common user action metrics (or performance testing metrics) measured and monitored in DEM include the following:

• User action duration. The time taken to complete the page load.
• Time to first byte. The time from browser request to the first byte of information from the server.
• Time to render. The time it takes for a page to load enough that a user can interact.
• Visually complete. The time to fully render content in viewpoint.
• HTML downloaded. The time it takes the user to receive the last byte or transport connection closes, whichever comes first.
• Speed index. How quickly visible parts of the page are rendered.
• Load event start. The time it takes to begin the page’s load event.
• Load event end. The time it takes to complete the page’s load event.

3. Establish baseline performance metrics

Establishing a baseline for key performance indicators (for the metrics listed above and others) enables ITOps to continuously monitor and compare application performance to identify deviations, anomalies, and recurring issues that may impact customer experience (CX). When analyzing the data, consider factors such as time of day, device types, geographic locations, and user demographics.

Document these metrics, including the benchmark values and any insights gained from analysis, to use as a reference for tracking progress and evaluating the effectiveness of optimization efforts over time.

4. Monitor end-to-end transaction paths

Monitor end-to-end transaction paths leveraging distributed tracing to gain visibility into the entire user journey. This includes monitoring components such as web servers, databases, application performance interfaces (APIs), content delivery networks, and third-party integrations. It should also extend from the user experience to the backend for AI-driven root cause analysis with real-time alerts that pinpoint where an issue is occurring and why.

A unified DEM platform with advanced AIOps observability can provide precise, automated insights and the context of each user’s digital journey in real time.

5. Leverage synthetic monitoring

Synthetic monitoring involves simulating user interactions and transactions to proactively monitor your digital services’ performance and availability. Use synthetic monitoring to conduct regular tests and identify potential issues before they impact real users. Synthetic tests and monitoring can be used across development and production environments, as well as for public and private locations, to provide a comprehensive view into performance and availability.

6. Implement real-time monitoring

Implementing real-time monitoring of all transactions out to the end user allows ITOps to detect and respond to performance issues in real time and near real time before they impact the user experience or affect service-level agreements (SLAs). It also tracks performance metrics in real time so ITOps can take corrective and proactive measures to comply with SLAs.

7. Enhance visibility with video-like recordings

Session replays (also called session recordings) show you exactly what the user saw when interacting with your application. Use these recordings to get a more qualitative view of the user experience and better understand negative and positive interactions. Session replays can also help align teams by simplifying communication and increasing collaboration with clear-cut video evidence that both technical and non-technical stakeholders can understand.

8. Extend your team with dedicated expertise

Digital experience monitoring requires specific skills that some organizations may not have in-house. Depending on the resources you have, you can enhance your team with experts who work full time across different businesses. This will ensure you have the right skills, experience, and analytic power to implement the best digital experience monitoring strategy for your organization and goals.

9. Adopt proactive performance optimization

Fostering collaboration between different teams involved in digital experience monitoring requires a product mindset approach that encourages knowledge sharing. Hold regular meetings and troubleshooting sessions to ensure a holistic approach to DEM that considers all aspects of your infrastructure and CX.

10. Establish cross-functional collaboration

Continuously optimizing your digital services’ performance with cross-functional collaboration of all company stakeholders, not just IT, will boost the end user’s experience. Regularly analyze monitoring data, identify performance bottlenecks, and take necessary actions to improve the speed, responsiveness, and overall performance of your applications and services.

Digital experience monitoring with Dynatrace

DEM encompasses various practices to optimize the performance, usability, and reliability of digital services and applications from the end user’s perspective. By following best practices with advanced AIOps and observability, organizations can effectively monitor and optimize digital experiences to meet users’ expectations and drive business success.

DEM is a core solution within the Dynatrace unified observability and security platform, providing AI-driven, automated, frontend-to-backend context into end-user experience. With real user monitoring, synthetic monitoring, and Session Replay natively built within Dynatrace, it empowers development, operations, and business teams with a single source of truth to deliver flawless user experiences and drive business results.

The post 10 digital experience monitoring best practices appeared first on Dynatrace news.

To give your customers a top-quality digital experience, it’s important to make sure your applications are always working properly. Synthetic monitoring, also known as synthetic testing, can help to confirm your applications are performing as intended, and if they’re not, help you quickly figure out what’s going on. Although synthetic monitoring tools have become a crucial part of application performance monitoring, not all solutions cover all types or yield the best results.

As modern cloud architectures are evolving, so too are the ways users can interact with your applications. We’ll get into how the different types of monitoring work, but first, some background.

What is synthetic monitoring?

Synthetic monitoring is an application performance monitoring practice that emulates the paths users might take when engaging with an application. It uses scripts to generate simulated user behavior for different scenarios, geographic locations, device types, and other variables.

After collecting and analyzing this valuable performance data, a synthetic monitoring solution can:

• Give you crucial insight into how well your application is performing
• Automatically keep tabs on application uptime and tell you how your application responds to typical user behavior
• Zero in on specific business transactions — for example, by alerting you to issues users might experience while attempting to complete a purchase or fill out a web form

How does synthetic monitoring work?

In synthetic monitoring, a robot client application that has been installed on a browser, device, or computer transmits a series of automated transactions to your application. These server calls and testing scripts simulate an end user’s clickstream as they navigate through key areas of your application. Typically, they run every 15 minutes, but you can configure them for different frequencies or to run immediately based on a specific action.

Once the robot client receives a response from your application, it reports the results back to the synthetic monitoring system. If the client detects an error during one of its regularly scheduled synthetic tests, the monitoring system will ask it to run that test again. If the follow-up test also results in an error, then the monitoring system will consider the error confirmed and escalate it within the organization as appropriate.

Teams can configure synthetic monitoring tools in various ways according to a company’s requirements. For example, you can set up a robot client on a machine that’s located behind your firewall to confirm that the internal environment is running as you expected, or you can deploy a robot client to a computer outside the firewall to get a sense of how well an application is performing. If you want a more comprehensive view of application availability and performance, you can configure several robot clients on browsers in multiple locations.

Synthetic monitoring vs. real user monitoring

Synthetic monitoring is often compared with another application performance technique known as real user monitoring (RUM). As the name suggests, RUM tracks actions taken by actual users instead of emulating them. Organizations often implement RUM by injecting JavaScript code into a webpage and then collecting performance data in the background as actual users interact with that page.

So, what is synthetic monitoring typically used for, and when might a business decide to use RUM instead? Synthetic monitoring is often helpful to identify short-term performance issues that may impact the user experience while an application is still under development. Early detection helps businesses nip potential performance issues in the bud. This approach is handy for regression testing and production site monitoring, for example. Real user monitoring, by contrast, can help a business understand long-term trends in an application’s performance after it has been deployed.

Why use synthetic monitoring?

If your application doesn’t perform well when your customers try to use it, they will quickly leave in pursuit of a better customer experience. This could play out in a variety of ways. For example:

• High bounce rates. Your website might take too long to load, resulting in a high bounce rate. Or, you might be lagging behind your competitors when it comes to application performance without even knowing it. This will hurt your ability to acquire new customers and grow your market share.
• Difficulty troubleshooting. Even when your organization is aware something is amiss with an application, it may not know where to begin troubleshooting. When it comes to application performance, IT teams can’t always get to the bottom of what’s going on quickly — especially when they’re overextended and juggling several priorities. And while your people are in the dark and searching for answers, your organization could feel an immediate and significant impact on its bottom line.

Emulating user behavior paths in a test environment helps you avoid these issues so you can:

• Monitor system health. Synthetic monitoring can tell you if your website is available, how fast it’s running, if key transactions are functioning as expected, and where a potential slowdown or failure might lie.
• Improve performance. Over time, synthetic monitoring can give you performance benchmarks, highlighting areas for improvement and optimization.
• Prevent issues early. You can also use synthetic monitoring to find and fix potential errors before they affect your users, raising the bar on the user experience. This is particularly useful in continuous integration and continuous deployment (CI/CD) environments.
• Increase resiliency. Synthetic monitoring can also help you prepare for peak traffic periods or anticipate performance requirements in a new region or market.

Synthetic monitoring tools are also useful for making sure you’re honoring service level agreements (SLAs) with your end-users. If an issue comes up involving third-party providers, you will be better equipped to hold them accountable, as well.

Types of synthetic monitoring

Synthetic monitoring usually includes three types: availability monitoring, web performance monitoring, and transaction monitoring.

• Availability monitoring enables an organization to confirm that a site or application is available and responding to requests. Availability monitoring can also use a more granular approach — for example, by checking to make sure specific content is available or that a specific type of API call is successful.
• Web performance monitoring typically looks at specific web metrics such as page load speed and the performance of specific elements on a webpage. It checks web content, errors, and sluggish response times.
• Transaction monitoring attempts to complete specific transactions such as logging in, completing a form, and checkout.

Within the realm of synthetic monitoring, there are also two main categories of synthetic tests:

• Browser tests – a robot client simulates a transaction a user might attempt (such as making a purchase)
• API tests – an organization monitors specific endpoints across each layer of the network and application infrastructure

Within API tests, there are different types of tests, including HTTP, SSL, and DNS. For example, API tests often use HTTP tests to monitor application uptime and responsiveness. Meanwhile, SSL tests confirm if users can securely complete transactions on a site using valid SSL certificates, and DNS tests make sure the site’s DNS resolution and lookup times are within expected parameters. A company might use multiple API tests to monitor whether a specific workflow is working properly from end to end — this type of API monitoring is called a multistep API test.

Challenges of synthetic monitoring

Modern applications are inherently complex. Because users access them from a variety of locations and contexts, synthetic monitoring is often not comprehensive enough to account for all the potential errors or situations that might arise. DevOps teams are accounting for this problem by placing a higher priority on introducing application testing earlier in the software development life cycle. However, synthetic monitoring is still often difficult to properly set up without specialized technical knowledge, and it is time-consuming even for the team members that have the required skill set.

Synthetic tests aren’t very resilient, and they can easily fail when small UI changes are introduced, generating unnecessary alert noise. This means that whenever a minor application element such as a button is changed, the corresponding test must be, too. And lastly, many synthetic monitoring tools lack the context needed to explain why a specific failure happened or what the business implications might be, lengthening time to resolution and making it unnecessarily difficult to prioritize application performance issues.

Benefits of synthetic monitoring

Proactive Monitoring: Synthetic monitoring allows you to proactively spot performance issues and availability problems. By imitating user interactions, it identifies irregularities before they impact real users. This early detection helps prevent potential outages and ensures a smoother user experience.

Global Testing: You can assess your application’s performance in various locations. Synthetic tests run from multiple regions, providing insights into regional variations in performance.

Browser and Device-Specific Testing: Synthetic monitoring lets you evaluate your application’s behavior across different browsers and devices. This helps identify compatibility issues and ensures consistent performance for all users.

Works Inside and Outside the Firewall: Unlike Real User Monitoring (RUM), which relies on actual users, synthetic monitoring can be completely automated and run inside and outside your organization’s network. This flexibility ensures comprehensive coverage.

Automated with Regular Frequency: Synthetic monitoring can run at regular intervals, such as every minute or hour, 24/7. This continuous monitoring ensures timely detection of any performance degradation.

Synthetic monitoring tools

A good synthetic monitoring solution should give your organization complete, 24/7 visibility into your applications. To accomplish this, it should include the following kinds of synthetic monitors:

• Single-URL browser monitors. A single-URL browser monitor simulates the experience a user would have while visiting your application using an up-to-date web browser. When run frequently from public and private locations, a browser monitor can alert you when your application becomes inaccessible or when baseline performance degrades significantly.
• Browser click paths. Browser click paths also simulate a user’s visit, but they monitor specific workflows in your application. An advanced synthetic monitoring solution can let you record the exact sequence of clicks and user actions you want to monitor, then set the browser click path to automatically run at regular intervals.
• HTTP monitors. HTTP monitors are useful for monitoring whether specific API endpoints are available, and they can also perform straightforward HTTP checks to confirm single-resource availability. HTTP monitoring tools should allow you to set up performance thresholds for HTTP monitors, too.

Synthetic monitoring use cases

Financial Services

Online Banking Systems: Synthetic monitoring ensures that online banking platforms remain available and responsive for users.

Payment Gateways: Monitoring payment gateways helps prevent transaction failures and delays.

Trading Platforms: Synthetic tests verify the performance of trading systems, which are critical for financial institutions.

Healthcare Technology

Electronic Health Record (EHR) Systems: Synthetic monitoring ensures EHR systems are accessible and responsive for healthcare professionals.

Patient Portals: Monitoring patient portals helps maintain seamless communication between patients and healthcare providers.

Telehealth Platforms: Synthetic tests validate the reliability of telehealth services, especially during high-demand periods.

General Web Applications

Availability Testing: Proactively detect failures even when there is no user traffic (for example, off business hours).

API Endpoints: Monitor the availability and performance of third-party API endpoints.

How Dynatrace can power your synthetic monitoring

If you’re thinking about better understanding how your applications are performing, you might be wondering what synthetic monitoring tools you need to get started. You’ll want to pick a solution that simulates business-critical journeys through your most important applications across your mobile and web channels. This can give you immediate answers to questions about application availability and the impact it’s having on the user experience. Your synthetic monitoring solution should also be able to help you quickly identify the root cause of any application performance issue so you can resolve it as soon as possible.

Dynatrace Synthetic Monitoring provides all the information you need to know the moment an application’s performance falters. By using all major desktop and mobile browsers to simulate user activity, Dynatrace helps ensure that web, mobile, cloud, and streaming transactions go smoothly for customers around the globe.

This is key for evaluating whether applications meet your SLA requirements, and it can determine whether business outcomes have been impacted. It can also eliminate troubleshooting through AI-driven automation, as well as rank problems in order of importance to the business — significantly reducing the time required for your IT team to identify and address root causes.

To catch those longer-term trends, Dynatrace RUM uniquely captures the full visibility of the customer experience to eliminate user experience blind spots, and Session Replay provides indisputable video evidence of the complete digital experience, so business, development and operations stakeholders can collaborate and agree where to make improvements.

These advanced digital experience monitoring capabilities help you proactively identify and address application performance issues from anywhere in the world. With the right synthetic monitoring solutions in place, your business can go a long way toward ensuring a consistent, satisfying customer experience.

The post What is synthetic monitoring? appeared first on Dynatrace news.

We’re proud to announce that Ally Financial has presented Dynatrace with its Ally Technology Velocity with Quality award. Ally Financial is the home of the nation’s largest all-digital bank and is an industry-leading auto financing business.

This is the second time Ally Financial has presented its Ally Technology Partner Awards. Specifically, the company recognized five third-party suppliers for delivering outstanding service excellence across various criteria that align with Ally’s core values and performance standards. These criteria include operational excellence, security and data privacy, speed to market, and disruptive innovation.

High monitoring costs and limited visibility drive the need for innovation

Ally Financial uses AI-powered observability for monitoring and automating its technology stack, from its cloud and on-premises infrastructure to its applications and customer digital experiences.

But as a company with a mission to “Do It Right” and be a relentless ally for customers and communities, the high-cost monitoring solutions it was using provided only limited insights into end-user experiences. Ally’s goal was to reduce the number of monitoring tools it was using and its annual spend while gaining better, more actionable—and more automatable—insights into systems that affect customer experiences.

Full-stack observability resolved problems, consolidated tools, and reduced costs

Ally became a Dynatrace customer in 2023. Within hours of starting Dynatrace, the team was solving long-standing problems. They quickly adopted full-stack monitoring and real user monitoring (RUM). With the insights they gained, the team expanded into developing workflow automations using log management and analytics powered by the Grail data lakehouse. As a result, Ally is driving a new level of operational efficiency and saving millions in annual licensing costs.

“We partnered with the Dynatrace team to consolidate our observability stack, allowing us to enrich metrics, logs, events, and traces with predictive analytics in a unified fashion across all channels,” said Jason McMunn, Director of System Engineering at Ally Financial. “This resulted in significant savings and much faster ROI. Moreover, we’re able to build automated workflows that help our teams resolve problems, operate more collaboratively and efficiently, deliver software faster, and delight our customers with world-class digital customer experiences.”

For Dynatrace, the Ally award is a cause for end-to-end celebration. “We’re excited Ally Financial has recognized Dynatrace as its Technology Partner of the Year,” said Matthias Dollentz-Scharer, Chief Customer Officer at Dynatrace. “Ally is an agile, modern financial services enterprise that has etched unified observability, AI, and analytics into the core of its cloud strategy. Indeed, by helping their team achieve an end-to-end view of their entire cloud environment—including front-end applications, mobile app experiences, and underlying infrastructure—we are proud to help Ally redefine digital banking.”

The innovation is mutual

The Ally Technology Partner Awards are a way for the company to acknowledge its exceptional partners. “We are proud to honor the vendor partners that play a significant role in our achievements at Ally through the Ally Technology Partner Awards,” said Sathish Muthukrishnan, chief information, data, and digital officer at Ally Financial. “Superior execution, quality, and partnership are showcased by each winner, which we value here at Ally as we aim to provide a best-in-class digital banking experience.”

Earlier this year, Dynatrace presented Ally Financial with its own award as our first Digital Breakout Performer. We present the award to customers who have begun their journey with Dynatrace in the last 12 months and immediately recognize a tremendous return on investment from unified observability, AI, and analytics.

Ally Technical Velocity with Quality award promises more innovation ahead

Receiving the Ally Technical Velocity with Quality award confirms the Dynatrace commitment to delivering customers the tools and technologies they need to make software work perfectly.

Dynatrace is especially proud to support innovators like Ally Financial. “The team at Ally is driving incredible efficiency as they continue to consolidate monitoring tools,” Dollentz-Scharer said. “Ally continues to push the envelope to further monitor their cloud infrastructure costs. I’m thrilled to see what’s in store for Ally Financial.”

The post Dynatrace proud to receive the Ally Technology Velocity with Quality award appeared first on Dynatrace news.

Government agencies aim to meet their citizens’ needs as efficiently and effectively as possible to ensure maximum impact from every tax dollar invested. As part of this mission, there is a drive to digitize services across all areas of government so citizens can meet their own needs faster and with greater convenience.

To address this, state and local governments are adopting multicloud environments to achieve the necessary speed, scale, and agility to keep up with faster digital transformation. While the benefits of multicloud environments are crucial to agency success, they introduce complexity and overwhelming data volumes that are impossible for humans to manage alone.

For example, government agencies use an array of cloud platforms spanning 12 environments on average. This is leading to increased complexity that is felt more acutely in the government sector than in any other industry. Nearly all government technology leaders (97%) reported the complexity of their technology stack has increased in the past 12 months. The same study found that 80% of government agencies are looking to consolidate the tools they use and adopt a unified platform for observability and security.

The importance of critical infrastructure and services

While digital government is necessary, protecting critical infrastructure and services is equally important.

Critical infrastructure and services refer to the systems, facilities, and assets vital for the functioning of society and the economy. These infrastructures are considered essential because their disruption would impact public safety, security, health, or economic stability.

At the city or county level, many components fall under critical infrastructure and services. These components include schools; transportation; energy; water; and communications such as the accuracy, timeliness, and transparency of election reporting. Protecting election reporting as part of critical infrastructure and services contributes to the integrity of elections and the legitimacy of elected officials. It also upholds democratic values and builds citizen trust.

While no one can deny the importance of protecting critical infrastructure and services, the complexity of multicloud environments makes it a pressing challenge. Unified observability is the key to success in resource-constrained local government agencies.

How observability helps IT protect modern environments

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to issues across their multicloud environments. As a result, local government IT teams require greater observability to manage increasingly diverse and complex computing environments.

Observability has become more critical in recent years as cloud-native environments have gotten more complex. Greater complexity contributes to greater difficulty pinpointing root causes for failures or anomalies.

Observability differs from monitoring. In a monitoring scenario, teams typically preconfigure dashboards to alert about performance issues they may expect to see later. However, these dashboards rely on the critical assumption that teams can predict potential problems before they occur.

Cloud-native environments don’t lend themselves well to this type of monitoring. Their dynamic and complex nature obscures foresight of problems that might arise.

In contrast, observability enables teams to understand a system’s internal state by analyzing the data it generates, including logs, metrics, and traces. Full stack observability enables IT teams to identify and respond to evolving issues across the entire technology stack from mainframes to multicloud environments. Every hardware, software, cloud infrastructure component, container, open source tool, and microservice generates records of every activity within modern environments.

Observability driven by AI operations empowers IT to understand what’s happening across all these environments and among the technologies. This capability allows teams can detect and resolve issues to keep systems ¾ including critical infrastructure and services ¾ efficient and reliable, and citizens satisfied.

Application performance monitoring is insufficient without observability

Application performance monitoring (APM) allows IT to ensure system availability, optimize service performance and response times, and improve user experiences at the scale of modern computing. In today’s highly connected digital world, APM has rapidly expanded to encompass a broad range of technologies and use cases.

Mobile apps, websites, and business applications are typical use cases for APM. However, with today’s modern architectures, use cases expand to the services, processes, hosts, logs, networks, and end-users that access these applications (including an agency’s citizens and employees).

IT teams use APM tools to view and address the many variables that can impact an application’s performance. Causes can run the gamut, from coding errors and database slowdowns to hosting or network performance issues. Even a conflict with the operating system or the specific device used to access the app can degrade an application’s performance.

Without the combination of observability and APM tools, teams struggle to resolve the numerous problems that can arise. This increases the likelihood of constituents becoming frustrated by the poor experience and abandoning the website or app altogether. Incorporating observability into traditional monitoring approaches is essential for deeply understanding a modern multicloud system and remediating complex problems swiftly.

Maintaining secure government applications

Critical infrastructure and services are a potential target for cyberattacks, terrorism, or state-sponsored threats. Protecting these systems is integral to ensuring national security. A resilient infrastructure can withstand shocks, recover quickly, and maintain essential services during emergencies such as natural disasters or cyber-incidents.

Both in-house developers and agency-purchased software leverage third-party code libraries that contribute to security vulnerabilities. The practices that develop modern applications can introduce gaps in observability and security on exploitable vulnerabilities in the runtime stack. The critical Log4Shell vulnerability is a recent example.

Traditional perimeter defenses often lack precision as they require manual configuration. At the same time, they cannot protect against unanticipated attacks. Reliably detecting malicious activity requires full-stack visibility. Runtime Application Protection continuously protects applications by detecting and blocking attacks on application layer vulnerabilities, such as injection attacks.

When Log4Shell emerged in Dec 2021, security teams faced tremendous pressure to identify if they were affected and remediate. In the aftermath, some organizations reassigned developers and turned agency codebases upside down to look for and patch Log4Shell. However, these efforts were manual and time-consuming. A few minutes after Log4Shell was published, the Dynatrace Application Security Module identified its presence in production environments worldwide. Dynatrace customers instantly knew exactly where they were affected, prioritized the systems that required immediate attention, and didn’t waste time in war rooms or chasing false positives.

With such high stakes, it is vital that city and county governments can quickly identify vulnerabilities while continuously monitoring the security environment in critical infrastructure and services.

Enhance critical infrastructure and services with Dynatrace

Safeguarding critical infrastructure and services is not just an IT responsibility. It is a collective effort involving continuous vigilance and solutions that help people manage an increasingly complex IT environment. By doing so, agencies can ensure their communities’ safety, prosperity, and resilience.

Today’s multicloud environments offer many benefits yet also introduce complexity and overwhelming data volumes that are impossible for humans to manage alone. Given constraints in funding and hiring IT staff, state and local governments require a modern platform built to operate efficiently while effectively protecting critical infrastructure and services.

The post Protecting critical infrastructure and services: Ensure efficient, accurate information delivery this election year appeared first on Dynatrace news.

As the world becomes increasingly interconnected with the proliferation of IoT devices and a surge in applications, digital transactions, and data creation, mobile monitoring — monitoring mobile applications — grows ever more critical. To navigate this complex landscape, organizations require a comprehensive approach to observability that enables a holistic view of applications. Such a view is essential for ensuring a seamless user experience and enabling organizations to achieve their business objectives.

With the recent retirement announcement of Microsoft Visual Studio App Center, users seeking alternative options can turn to the Dynatrace unified observability and security platform. Dynatrace observability, security, and data analytics capabilities empower users to derive greater insights and benefits from their monitoring data, ensuring they stay ahead in their mobile monitoring environments while offering similar feature parity to Visual Studio App Center.

Benefits of an integrated observability platform for mobile monitoring

For Microsoft Visual Studio App Center users, migrating to Dynatrace for a mobile monitoring solution provides an all-in-one, integrated approach, delivering the context, visibility, and answers needed to solve complex problems across all the technologies involved in mobile app development while ensuring a seamless user experience. Mobile monitoring with the Dynatrace observability and security platform provides the following key benefits.

• Enhances business insight and efficiency with real-time data
  Organizations can focus on what is important with deep insights on user sessions, top devices, OS versions, and behavioral analytics for iOS, Android, and hybrid apps. Dynatrace enhances operational efficiency and helps drive business results, ensuring the precise information mobile app developers need to deliver effective user experiences.
• Reduces blind spots with complete visibility from front to back end
  With an observability platform, organizations are not limited to only the backend performance or the front-end user experience data because the entire picture is delivered in one place. With this holistic view, mobile developers can not only see what users are doing by looking at individual user actions, full user sessions, and errors, but also see how the experience flows to the back end through web requests, called services, and more. As a result, developers avoid the blind spots that may arise from disconnected data or tools, and most importantly can quickly learn why something happened.
• Helps fix issues faster with answer-driven root cause analysis to release higher quality applications with confidence
  The end-to-end mobile app observability from Dynatrace automatically provides developers with the root cause of problems impacting their mobile users so they can quickly address them, rather than waste time diagnosing what needs to be done.
• Prevents negative customer experiences with robust crash analytics
  Mobile app crashes are one of the biggest pain points for mobile users and developers, with crashes known to cause 71% of app uninstalls. Dynatrace mobile RUM provides advanced crash analytics that show how many real users are affected by a crash across dimensions such as app version, OS version, device, jail-broken status, and more. These analytics help mobile developers quickly diagnose and fix mobile app crashes. In addition, Session Replay enables developers to immediately reproduce crashes and view exactly what actions a user took.
• Enables teams to collaborate effectively with a single source of truth
  When mobile monitoring is an integrated part of a larger unified observability and security platform strategy, it fosters more effective collaboration because everyone has access to the same data. With Dynatrace, mobile developers, mobile application owners, and mobile DevOps practitioners can work together better and more efficiently to deliver enhanced mobile app experiences.

End-to-end mobile observability with Dynatrace

Dynatrace Mobile RUM is built into the Dynatrace platform to provide complete mobile monitoring for mobile developers and app teams to optimize applications and improve customer engagement and retention. With industry-leading AI at the core of the platform to drive advanced crash analytics, continuous topology mapping, root cause analysis, and quantifiable business impact, Dynatrace simplifies mobile monitoring so mobile app teams can deliver the high-quality performance and user experiences mobile users expect today.

Check out the three-part mobile monitoring video series to learn more about Dynatrace mobile app monitoring.

• Part 1: Instrumentation for the Developer
• Part 2: Value for Mobile Application Owners
• Part 3: Value for Mobile DevOps Practitioners

For existing Microsoft Visual Studio App Center customers that need support migrating to the Dynatrace mobile monitoring solution, click here for more information.

The post Transitioning from Visual Studio App Center: Key benefits of an observability platform for mobile monitoring appeared first on Dynatrace news.

Recent platform enhancements in the latest Dynatrace, including business events powered by Grail™, make accessing the goldmine of business data flowing through your IT systems easier than ever. One of the more popular use cases is monitoring business processes, the structured steps that produce a product or service designed to fulfill organizational objectives. By treating processes as assets with measurable key performance indicators (KPIs), business process monitoring helps IT and business teams align toward shared business goals. This collaboration increases process efficiency and improves customer satisfaction by identifying opportunities for process improvement and detecting process anomalies in real time.

Business process monitoring leverages business events, a new data type designed to support the real-time accuracy and long-term granularity demands common to business use cases. Business events can come from many sources, including OneAgent®, external business systems, RUM sessions, or log files. Of particular note, OneAgent can now extract business data from in-flight application payload, prioritized to ensure the lossless precision that business use cases demand. OneAgent business events require no code changes, just a simple configuration to define capture rules. Business events are automatically enriched with Smartscape® topology context, connecting them to their source systems and applications for effective BizOps collaboration.

The Business Flow app

Business Flow, built with AppEngine, simplifies the configuration, monitoring, and analysis of business processes. Business Flow uses business events to define and track each process step or milestone. Correlation IDs—an order number, transaction ID, or any unique identifier—connect steps to create an end-to-end business flow that can span hours, days, weeks, or longer.

Business Flow reports four KPIs:

• Flows completed
• Business exceptions or process errors
• Average process completion time
• A configurable business performance indicator such as revenue, extracted from a business event.

Let’s examine a few practical business process monitoring examples.

Order fulfillment

In this example, an e-commerce company wants to track its order fulfillment business process. Important metrics include end-to-end measures of delay in tracking an order fulfillment service level goal and delay between each step to highlight anomalies and identify opportunities for process improvement. While the process includes many steps, the company started by tracking three milestone steps: order placed, order shipped, and order delivered.

Getting started is simple.

• Define a business event for each milestone step. The event source determines the configuration steps; see our business analytics documentation for details.
• In Business Flow, choose a configured business event to represent each step.
• Choose an attribute from a business event (for example, order_amount) to represent the business flow KPI.
• Choose an attribute common to each business event (for example, order_id) as the correlation ID.

  

Real-time business process monitoring helps IT and business teams track process performance, detect process anomalies, and optimize process inefficiencies to ensure customer satisfaction and business outcomes.

Business process conversion funnels

In our e-commerce example, there’s an implied expectation that every order placed will be delivered; only a process anomaly would result in a lost package, and process efficiency might focus on improving fulfillment time. Some business processes behave like conversion funnels, with expected attrition at each step. A loan application process is an example; not all customers who apply for a loan will commit, and delays in the approval process might result in increased abandons. It’s easy to switch the business process display from the tree view to a funnel view.

To get started with Business Flow, add the app from Dynatrace Hub and follow the setup guide.

Use DQL to monitor business processes

Business Flow is built with AppEngine, designed to simplify business process monitoring, in part by masking the underlying queries. For most use cases, it’s the best starting point for process observability. There are also cases where dashboards or alert integrations are important, often as complements to using the Business Flow app. The following example examines the DQL used to build a custom dashboard for a major French B2B food company to monitor five critical steps in a production line. We provide a Notebook for you to follow along in your Dynatrace tenant; you can download the Notebook from GitHub and upload it to your tenant. The Notebook includes static business event data to help you examine the DQL shown in the following examples.

The Dynatrace Query Language (DQL) we use to monitor the production line process generates a tabular report detailing the progress of individual orders in five distinct steps.

The DQL for the five-step production process is relatively simple, using order_ID within the summarize command to correlate all five steps.

Next, we can consider the case of a major online gaming company; their goal is to minimize the time between a win notification and the corresponding payout to keep the player engaged. Their use case is more complex due to different correlation IDs. Despite the differing IDs, we can use a simple DQL query to measure the delay between a win notification and the associated online payment. With this simple process monitoring solution, the company can manage its commercial commitment to keep the payment delay below a predefined threshold.

For this use case, the DQL request needs two successive summarize commands:

• The first summarize command uses runID to correlate bizevents 2 and 3 in a record.
• The second summarize command correlates the record with bizevent 1 based on the betID

Service level objectives (SLOs) and workflow automation for business processes

Monitoring the payment process provides real-time insights into performance and anomalies. The next step is to formalize the goals by defining a service level objective (SLO) and an error budget policy. We’ll add the SLO function to the mix, with the goal of 99% compliance to an eight-minute service level.

We can add the following SLO calculation to our previous query to measure compliance:

To configure your first Site Reliability Guardian, add the app from your tenant and follow the Get started guide.

All that remains is to set up a workflow that, based on the SLO, will trigger notifications to your service management solution and to your business teams.

See more Workflow automation use cases by visiting Workflows in Dynatrace Hub.

Automated business processes are the heart of modern organizations. IT operations and business teams benefit from a shared view of process health, using business KPIs as the primary metrics. Dynatrace makes monitoring, analyzing, and optimizing business processes easier than ever.

For a closer look at Business Flow, see this App Spotlight, or contact your Dynatrace representative.

The post Practical business process monitoring for real-time business observability appeared first on Dynatrace news.