Every organization runs on data. But for most leaders, the challenge is clarity. Traditional dashboards and reports often arrive too late, and system-level metrics don’t explain the business consequences of technical events.

When a payment API slows by 200 milliseconds, what does that mean for daily revenue? When user sessions drop, is it a performance issue or a recent pricing change? These are the questions business observability is designed to answer.

Business observability connects technical telemetry to business outcomes, creating a shared understanding of how digital performance drives, or hinders, organizational results. It’s less about adding more data, and more about connecting the right data in real time to the decisions that matter.

Importantly, business observability is broader than observing individual business processes. While end‑to‑end workflows like “order to fulfillment” or “claim to payout” are one expression of business observability, the discipline also encompasses digital experience, customer behavior, revenue impact, operational efficiency, and risk. Business observability focuses on understanding how technology performance influences business outcomes across the organization and not just how a single process executes.

Moving beyond traditional monitoring

Traditional monitoring focuses on uptime, latency, and error rates. These are essential for engineers but often disconnected from business context. Business observability closes that gap by linking system health directly to business performance.

That connection – the ability to translate technical telemetry into business insight – is what distinguishes business observability from conventional monitoring.

What makes business observability different

Business observability builds on traditional monitoring by expanding its scope from system health to business outcomes. It introduces three essential capabilities that operate across customer experience, revenue‑generating transactions, and end‑to‑end processes:

• Business context integration: IT metrics are linked with business KPIs, translating system behavior into measurable impact.
• End-to-end business process visibility: Processes like “loan approval to disbursement,” “claim to payout,” or “application to onboarding” are monitored across applications, infrastructure, and external systems.
• Real-time decision support: Business observability surfaces business implications in real time, allowing teams to respond to issues before they escalate.

Together, these principles give organizations a live understanding of how every digital interaction affects outcomes, from conversions and revenue to efficiency and satisfaction.

Where business observability gets its data

Business observability relies on unifying multiple data streams into a single, contextual view of performance:

• Business events: Structured, contextualized data that represents key business outcomes, such as completed checkouts, submitted claims, bookings, or failed transactions.
• Logs: Time-stamped records of system activity that show what happened and when, often containing critical technical and business data.
• Real user monitoring (RUM): Continuous insight into how users actually experience applications and digital services across devices, channels, and geographies.
• External business tools: Data from tools such as ERP, CRM, billing, and payment platforms that provide commercial, operational, and customer context.
• Instrumentation and agents: Technologies that collect telemetry and business-relevant data from applications and services, ranging from manual instrumentation to automated approaches that observe activity as it flows through systems with minimal configuration effort.
• OpenTelemetry: A standardized instrumentation framework that enables consistent collection of metrics, logs, and traces across hybrid and cloud-native environments.

When correlated, these data sources bridge the gap between technical operations and business results, providing a comprehensive view of how technology supports, or disrupts, performance.

How organizations put business observability to work

Modern organizations apply business observability in three key ways. Organizations may pursue these use cases through a variety of approaches, ranging from manually instrumented metrics and custom reporting to more automated, integrated platforms that reduce effort and time to insight.

1. Drive real-time decisions with IT context: When issues arise, teams and business leaders can see the business impact immediately. A sudden dip in conversions, for example, can be traced to a misconfigured API or third-party service outage, enabling immediate, targeted response.
2. Track and optimize business processes: Complex workflows—like “order to fulfillment” or “quote to claim”—are mapped from end to end. Teams can pinpoint where time, cost, or customer satisfaction are being lost and address bottlenecks before they affect outcomes.
3. Accelerate sustainability and reduce costs: By correlating business events with resource usage, organizations can identify inefficiencies in automation, cloud consumption, or scheduling that inflate cost and carbon impact.

Business observability, in action

Each of these examples shows how business observability does more than surface anomalies. It provides the context to act on them. By connecting business events, telemetry, and user experience data, organizations move from simply detecting issues to understanding their impact, cause, and resolution path in real time.

In practice, achieving this level of insight often depends on how business and technical data are captured and correlated. While some organizations rely on custom instrumentation, manual analysis, or post‑incident reporting, others use more automated approaches that make it possible to detect impact, trace root cause, and act in real time.

Financial services

A large financial institution monitored loan application volume as a business event rather than relying solely on system health metrics. When completed applications began declining, traditional monitoring showed no infrastructure failures. Business observability revealed that timeouts from a third-party credit scoring service were affecting only new applicants following a recent integration change. By correlating business events with external service performance, the bank isolated the issue quickly and rolled back the configuration—preventing lost loan volume and downstream compliance exposure.

Payments

A global payment services provider processes billions of transactions annually and needs to understand not just whether systems are available, but how performance impacts transaction success and revenue. By connecting transaction latency and failure rates directly to payment outcomes, the organization can quantify the financial impact of technical issues in real time. This shared visibility allows both internal teams and customers to see how payment flows are performing and proactively optimize transaction speed and reliability.

Travel and hospitality

A large travel platform aggregates booking data across partners, regions, and channels. Business observability enables teams to track quotes, bookings, and completed reservations as business events, segmented by partner and geography. When booking volume dips, teams can immediately determine whether the cause is a partner integration issue, a regional performance problem, or a downstream service slowdown—allowing rapid response to protect revenue across the ecosystem.

Retail and consumer services

A national restaurant chain observed high abandonment rates during online reservation flows. Rather than treating this as a generic user experience issue, business observability correlated real user behavior with backend availability and booking outcomes. This insight enabled automated recovery workflows that re-engaged customers who abandoned reservations due to technical or availability issues—recovering lost bookings without manual intervention.

Aviation and transportation

An international airline struggled with fragmented visibility across booking, pricing, and fulfillment systems. By modeling bookings as end-to-end business processes, business observability provided real-time insight into how technical issues affected customer bookings and operational teams. This shared context improved collaboration between IT, call centers, and operations, reducing response times and improving passenger experience during disruptions.

Insurance and regulated industries

An insurer tracked claims submissions as business events and noticed rising exception rates on mobile channels. Business observability revealed that document uploads from newer devices exceeded a backend file-size limit introduced during a recent update. Because business events, logs, and user session data were correlated in real time, teams deployed a same-day fix and notified affected customers—preventing claim backlogs and demonstrating operational transparency to regulators.

Manufacturing and public sector

Organizations running complex, multi-step production or licensing processes use business observability to monitor each step as it moves across applications, infrastructure, and external systems. In manufacturing and government services alike, correlating process steps with technical events allows teams to identify bottlenecks that delay outcomes—such as throttled payment validation or downstream capacity limits—and resolve them without disrupting customer- or citizen-facing services.

Enabling data-driven executive insight

For executives, business observability shifts technology from a cost center to a source of executive intelligence, providing leaders with real‑time visibility into revenue, customer experience, operational performance, and risk. It enables:

• Real-time business health monitoring: Live dashboards show key performance indicators such as order volume, claim processing times, or fulfillment success rates.
• Anomaly detection: Advanced analytics identify deviations in both technical and business metrics before they escalate.
• Impact analysis: Teams can immediately quantify how issues affect revenue, engagement, or satisfaction, and prioritize based on real business value.
• Trend analysis: Historical and real-time data combine to forecast outcomes and guide strategic decisions.

Improving collaboration between business and IT

One of the most transformative aspect of business observability is the way it unifies language and priorities across teams.

• IT teams can prioritize work by business impact instead of technical urgency.
• Business stakeholders gain visibility into technical dependencies that influence performance.
• Cross-functional teams align around shared outcomes rather than isolated metrics.

This shared context strengthens trust and speeds response, particularly during digital transformation, where both technology performance and customer experience are constantly evolving.

Laying the groundwork for business observability

While business observability may be expressed through dashboards, process views, or executive metrics, its success depends less on how data is visualized and more on how consistently business outcomes are connected to technical signals across teams. Adopting business observability effectively requires thoughtful preparation:

• Data integration: Pull from diverse sources – applications, infrastructure, and business systems – to form a cohesive view.
• Shared metrics: Define how business KPIs map to technical signals.
• Organizational alignment: Ensure teams are trained and incentivized to act on shared insights.
• Platform scalability: Choose an observability solution that supports hybrid, cloud, and partner ecosystems as data volume grows.

The road ahead

Business observability represents a shift from reactive monitoring to outcome-driven intelligence. Rather than focusing solely on system health or individual process performance, it enables organizations to understand in real time how technology influences revenue, customer experience, operational efficiency, and strategic decision‑making. For executives, it means real-time visibility into how technology influences outcomes. For IT teams, it means prioritizing based on business value. For organizations, it means a unified, data-driven way to make decisions with confidence.

In practice, many organizations attempt to reach this level of insight through manually instrumented metrics, custom dashboards, and offline analysis – approaches that require ongoing effort and often delay understanding when it matters most. Dynatrace Business Observability takes a different approach, capturing business events from multiple sources and automatically correlating them in real time with full‑stack telemetry. This delivers the context leaders need to act decisively, without the manual overhead of traditional approaches.

FAQs: Business observability

What is business observability in simple terms?

Business observability is the ability to understand how technical performance affects business outcomes in real time. It connects IT telemetry, such as logs, traces, and metrics, with business data such as transactions, claims, or orders, so teams can see both the cause and the consequence of an issue in one view.

How is business observability different from traditional monitoring?

Traditional monitoring reports on system health (uptime, latency, or resource use) without showing the business impact. Business observability goes further by linking these technical metrics with key performance indicators (KPIs), providing the context to understand how technical changes influence revenue, customer experience, and operational efficiency.

What types of data does business observability rely on?

Business observability combines multiple data sources, including:

• Business data from transactions or processes
• Logs and traces from applications and infrastructure
• Real user monitoring (RUM) for end-user experience
• Data from external business tools like CRM, ERP, or payment systems
• Instrumentation frameworks such as OneAgent and OpenTelemetry for consistent telemetry across environments

Who benefits most from business observability?

Executives gain real-time visibility into how technology affects performance and outcomes. IT and engineering teams gain business context to prioritize fixes based on impact. Together, these perspectives drive faster decision-making and closer alignment between technology operations and business goals.

What are common use cases for business observability?

Typical use cases include:

• Detecting and resolving process slowdowns in finance, healthcare, or logistics workflows
• Tracking and optimizing customer journeys and digital transactions
• Measuring the business impact of new releases or integrations
• Identifying inefficiencies that increase costs or carbon footprint

How does business observability support sustainability and cost efficiency?

By correlating business events with resource consumption, business observability helps identify where automation, compute, or storage are overused. This enables teams to optimize cloud spend, reduce energy consumption, and track sustainability metrics alongside operational performance.

What challenges do organizations face when implementing business observability?

Key challenges include integrating data from multiple systems, defining the right shared KPIs between business and IT, and ensuring teams are trained to act on insights collaboratively. Success depends on cross-functional alignment as much as on technology.

Is business observability only relevant for large enterprises?

No. Any organization that relies on digital processes – from mid-sized financial firms to healthcare networks or government agencies – can benefit. The ability to link technical performance to business results is valuable at any scale

The post The rise of business observability appeared first on Dynatrace news.

Observability data can tell you a lot, but often not in a language that your business understands. Traces fire, business events flow, and dashboards light up, yet P1 incidents still break out. The first question from the war room is typically, “Who’s impacted?” Too often, the honest answer is, “Let me check the database and get back to you.” This gap between raw telemetry and human-readable business context is exactly what lookup tables in Dynatrace are designed to close.

In our introductory blog post on Dynatrace lookup tables, we explained the fundamentals: what lookup tables are, how to ingest them, and initial use cases spanning security to business context enrichment.

In this blog, we’ll go deeper, with real-world examples of lookup tables, practical patterns, and how teams are already putting them to work.

The problem: Dashboards display cryptic identifiers, not insights

Daniel Adams, Observability Engineer at FreedomPay, put it plainly in a recent Dynatrace Tips & Tricks session:

“A lot of our apps are not coded to show customer names or plain text human-readable stuff. It’s mostly IDs being passed back and forth.”

The result is that dashboards are filled with cryptic identifiers that operations teams and business stakeholders can’t mentally decode. And splitting data by customer, country, or store requires trips back to the SQL database for further contextual configuration.

Many organizations that run distributed systems at scale face the same challenge: telemetry is rich, but the business context is missing.

The solution: Use lookup tables to make your reference data available in Grail

Lookup tables let you upload reference data (CSV, JSON, or XML files) directly into Dynatrace Grail®, where it lives alongside your logs, traces, metrics, and business events. Once uploaded, two DQL commands unlock the enrichment from your lookup tables:

• Load fetches the contents of a lookup table, working just like querying any other data type in Grail.
• lookup joins records from your observability data with matching rows in the lookup table, using a defined key field.

In FreedomPay’s case, the lookup table holds customer names, customer codes, store IDs, and countries. The join key is the store ID, the same cryptic identifier that was previously displayed on their dashboards. One DQL lookup command later, those IDs become readable names, and the data can be split by country, grouped by customer, and surfaced in a dashboard that anyone on the team can use.

Lookup tables reduce user cognitive load

The impact of lookup tables is not just cosmetic. Daniel described the before-and-after in P1 situations:

“Previously, everyone was asking: who’s impacted, which customer? Now it’s just very apparent and real-time. People can share screenshots directly from Dynatrace.”

The shift from “let me go check” to “it’s right here” compresses triage time and reduces the cognitive load on everyone in the room.

Beyond incident response, lookup tables also power dashboard variables. FreedomPay uses dashboard variables to populate dropdown filters (for example, clients and countries) directly from the lookup table itself, keeping the UI dynamic without manual maintenance. The load command behaves like any other fetch command but operates on reference data rather than telemetry, making it a natural fit for driving interactive dashboards.

And the enrichment isn’t limited to business events. The load and lookup commands work across all data types in Grail.

In practice: cost allocation with lookup tables

Cost allocation is a good example of how lookup tables bridge the gap between operational data and business reality. Many organizations already maintain mappings that associate users, teams, or services with products or cost centers, but that context rarely lives inside observability data. Lookup tables allow you to introduce such context.

Consider DPS (Dynatrace Platform Subscription) consumption driven by user activity such as running queries, triggering automation, or executing functions. On its own, such usage is hard to attribute to a specific part of the organization. By associating users with products or cost centers in a lookup table, you can attribute usage to organizational ownership rather than just technical activity, align cost views with existing financial or product structures, and keep that attribution logic centralized and reusable rather than embedding it in individual analyses.

What makes this pattern scale is that business mappings change over time, while usage data continues to flow. Lookup tables allow you to evolve the mapping without rewriting your analyses. The same mechanism used for cost allocation works equally well for mapping users to teams, services to portfolios, or environments to internal programs. Cost allocation simply highlights how powerful this becomes when operational data is interpreted through a business lens.

Importantly, this is just one way to approach cost allocation, not the only way. Some teams rely on host-based attribution, others on pipeline metadata or external financial systems. Lookup tables complement these models by making it easy to incorporate existing reference data wherever it adds clarity.

Keeping lookup data fresh

For lookup tables to deliver lasting value, their data must remain current. FreedomPay currently uses Postman to push updated CSVs via the upload API, but they’re building automation to pull this data from their SQL backend daily and sync changes using the overwrite: true parameter. The lookup table path stays the same; the data underneath gets refreshed. Downstream dashboards and queries are updated automatically.

More broadly, there are several approaches to keeping lookup data up to date:

• Dynatrace Workflows automate extraction and upload from SQL databases or APIs on a schedule.
• Periodic refresh updates your lookup data programmatically as part of CI/CD or data sync processes.
• Manual refresh uses Postman, cURL, or other API-based uploads with the overwrite flag when data changes infrequently.

Dynatrace lookup tables are now generally available

With the release of Dynatrace SaaS version 1.334, lookup tables are generally available for all customers running Dynatrace SaaS with an active Dynatrace Platform Subscription (DPS). GA brings production-readiness, improved query performance for the lookup command, and full integration with Grail’s scalability and access controls.

To get started

1. Identify a data enrichment use case: cost allocation, customer context, error code mapping, or security allow lists.
2. Prepare your reference data as a CSV, JSON, or JSONL (JSON Lines) file.
3. Upload the file to Grail using the Dynatrace API, Workflows, or a custom app.
4. Use the load and lookup commands in your DQL queries, notebooks, and dashboards.

For detailed instructions, visit our lookup data documentation. And to see how FreedomPay built its implementation from end to end, watch the full demo on YouTube.

The post How lookup tables turn observability data into business insight appeared first on Dynatrace news.

Compliance is only getting more complex, as organizations seek to proactively manage compliance risks and maintain trust with stakeholders. Traditional compliance tools often operate in silos, leaving critical compliance risks undetected. This fragmented approach makes it difficult to connect compliance risks to business impact, collaborate across teams, or respond quickly to incidents. Complex alignment between IT, legal, and business teams often results in inefficiencies, miscommunication, and critical compliance gaps. Furthermore, manual processes for managing compliance tasks are not only time-consuming but also insufficient in keeping pace with growing regulatory pressures.

From static checklists to continuous framework-specific visibility

With Compliance Assistant, Dynatrace provides compliance-critical observability and security insights streamlined into a single pane of glass. You can now track compliance health across IT and business landscapes with ease, with real-time insights mapped directly to a compliance framework.

Compliance Assistant provides an out-of-the-box, tiered score that reflects the current compliance risk posture across Information and Communication Technology (ICT) incidents, vulnerabilities, security detection findings, and misconfigurations. Designed to meet the demands of frameworks like EU DORA (Digital Operational Resilience Act), this score provides a quantifiable snapshot of ICT risks at a glance, enabling cross-functional collaboration and empowering teams to stay ahead of risks and maintain confidence in their compliance efforts.

Map IT assets to end-to-end compliance-critical business processes

Under EU DORA, organizations are required to identify and monitor critical or important functions (CIFs). This includes business operations that could significantly disrupt financial performance, service continuity, or compliance with regulatory obligations.

Identifying critical or important functions (CIFs), such as payment processing or fraud detection, requires in-depth business process monitoring and a clear understanding of how IT systems support them. Compliance Assistant transforms this traditionally complex task by leveraging Business Flow, powered by Dynatrace, to break down the steps of a critical or important function (CIF) directly connected to specific business milestones in real-time. With Smartscape on Grail, Dynatrace offers end-to-end visibility by linking compliance-critical business processes to specific IT components, hosts, or applications. For example, a payment approval process in Business Flow can be linked to a payment gateway service, a transaction database, and a fraud analytics engine — enabling Compliance Assistant to show how a single critical or important function (CIF) depends on multiple IT components.

With this business-centric approach, Compliance Assistant empowers teams to automatically track critical metrics such as conversions and errors, proactively addressing any potential disruptions to underlying services. The integration with Business Flow doesn’t just enhance visibility; it fosters collaboration by bridging IT performance data with tangible compliance-critical business outcomes.

Confidently manage compliance risk

Managing ICT risks is a cornerstone of compliance with resilience frameworks, and Compliance Assistant helps you leverage Dynatrace Application Security capabilities with insights mapped to regulatory requirements.

Compliance Assistant consolidates:

• Vulnerabilities with a breakdown of findings by severity and real runtime exposure, enabling security champions to prioritize risks through a compliance lens.
• Security detection findings offer visibility into suspicious activities across the digital landscape.
• Compliance results for evaluating configuration data against the relevant compliance standard. The built-in tile in ICT asset configuration rules summarizes assessment results by the percentage of passed and failed rules, powered by Dynatrace Security Posture Management.

Compliance teams must demonstrate regulatory readiness across security, infrastructure, and operations teams, often speaking different languages about configurations, vulnerabilities, and compliance gaps. The unified compliance-health view bridges domain gaps, reducing back‑and‑forth between teams and enabling efficient alignment. Compliance Assistant goes beyond ticking boxes next to regulatory requirements by translating abstract rules into concrete workflows, so you can close the cross-functional operational loop and confidently track progress towards compliance readiness.

AI-powered incident classification

Complying with regulations like EU DORA also requires organizations to identify, classify against thresholds, and report major incidents impacting compliance-critical business processes. This requirement poses significant challenges, especially in complex IT environments with high volumes of data.

Dynatrace Compliance Assistant simplifies this process with an AI-powered incident classification workflow. It automatically identifies potential incidents affecting critical or important functions (CIFs) and, based on the calculated impact against EU DORA classification criteria, categorizes them into unclassified, potential major incidents, and classified major incidents.

For each potential incident, you can access detailed insights into the triggered materiality thresholds, which signal the potential need to escalate an incident for classification as major:

1. Critical or important functions affected: Assesses the blast radius of the incident and its impact on compliance-critical business processes.
2. Incident duration: Monitors the 24-hour materiality threshold of the criterion for incident classification, according to EU DORA.
3. Economic impact: Indicates whether the impact surpasses the classification threshold of €100,000. The impact is calculated based on the estimated incurred cost per minute of the relevant CIFs and the duration of an incident.

For example, if payment processing is down for 30 minutes and the estimated economic impact exceeds €100k, the incident meets one of EU DORA’s materiality thresholds and Compliance Assistant flags it accordingly.

Under EU DORA, an incident must be classified as major if two or more materiality thresholds are breached. Dynatrace streamlines this process by automatically identifying threshold breaches and allowing users to manually classify incidents directly from the incident details page. Users can also add comments to document their reasoning, ensuring transparency and traceability. This end-to-end functionality ensures organizations can confidently manage incidents, align workflows, and accelerate regulatory reporting.

Classification of an incident in Compliance Assistant generates a snapshot of the compliance incident as a business event, enabling integration with your incident management ecosystem. Automations with Dynatrace Workflows can then be triggered by this classification event to bridge gaps between observability, compliance, and incident management teams. For example, you can use workflow actions to create incidents in your ServiceNow environment or to create a Jira ticket enriched with details of the incident’s compliance impact.

Ready to transform your compliance strategy?

Install and activate the Compliance Assistant app from Dynatrace Hub and take the first step toward streamlined, real-time compliance management. With Compliance Assistant, you can simplify compliance workflows while aligning IT operations with broader business objectives, ensuring more efficient compliance strategies.

• To learn more about setting up Compliance Assistant, check out the documentation.
• Share your feedback, suggestions, and ideas with us in the Dynatrace Community.
• New to Dynatrace? Try Compliance Assistant in the Dynatrace Playground or start a free trial to see Dynatrace in action

What’s next for compliance intelligence

We’re committed to continuously evolving Compliance Assistant to meet your ever-changing compliance needs. Upcoming enhancements include support for additional regulatory frameworks and expanded automation capabilities, allowing for even broader compliance coverage across industries. Stay tuned as we continue to empower organizations to simplify compliance, reduce risk, and stay ahead in a complex regulatory landscape.

The post Unlock business-centric compliance intelligence with Dynatrace Compliance Assistant appeared first on Dynatrace news.

Dynatrace introduced a new entity in Smartscape® that connects your IT topology with your critical business processes. Monitoring a business process as an entity via Business Flow establishes a direct link between your IT issues and business operations. This connection helps you prioritize problem resolution by showing which issues impact your business.

Group IT services by business purpose

Your business runs on processes that matter: purchase orders, loan approvals, employee onboarding, and more. But these business processes often span multiple IT systems, making it hard to see the full picture. When something breaks, it becomes nearly impossible to quickly understand which IT issues threaten critical business outcomes.

With Dynatrace Real User Monitoring, organizations can understand the impact of IT problems by seeing how many users are actively using an application, which users are affected, and how failures degrade user experience. Dynatrace also allows telemetry to be scoped and analyzed by business dimensions such as region, team, or customer-facing application, using segments.

This business context provides strong value, but it stops short of showing how individual IT services come together to support an end‑to‑end business process. One way to bridge that gap is tagging, but in practice, that approach is manual and difficult to keep up to date. It rarely reflects the current, real-time reality of dynamic environments, and many legacy systems can’t be tagged at all. Instead of relying on static tags, the integration of business flows within the new Smartscape captures these relationships directly, showing how services collectively support a business process as it actually runs. By showing which IT services underpin a critical business process and how disruptions propagate across them, teams can respond immediately and decisively when issues arise.

The new Smartscape: making business outcomes a part of your topology

Dynatrace models business flow configurations as entities in the new Smartscape, making business processes a first-class part of the topology. Representing critical business processes as entities creates a single source of truth across the enterprise, aligning IT and business priorities. This allows teams to:

• Understand business purpose across IT and OT, eliminating guesswork about what matters most.
• Prioritize security risks by business impact by linking vulnerabilities to revenue-critical systems.
• See business impact during problem resolution by connecting IT problems to the processes that drive growth in the Problems app.
• Align cost and sustainability with business outcomes by mapping spend or carbon emissions to specific business processes.

Connect your Business Flow configurations to Smartscape

Business events are the cornerstone of any business process monitoring initiative. Each event is automatically enriched with important topology and application context.

Business process milestones (or steps) are defined in Business Flow, where specific types of business events are grouped. By analyzing business-event groups, Dynatrace identifies the topological entities involved in each milestone.

Example

If a business event is collected by a specific process (software component) and a host, and that event corresponds to a step such as “Payment approval”, the business process entity will be linked to that host and process in Business Flow. These links are refreshed every two hours to reflect changes in the environment.

Once connected, business flow entities and their dependencies can instantly be visually explored in the Smartscape app. They can be viewed alongside applications, services, and infrastructure, or isolated to show all IT relationships supporting a specific business process.

Turning business flows into real-time business metrics

When your business flow configuration becomes an entity in Smartscape, it doesn’t just give you visibility; it becomes a continuous engine of business insight. Dynatrace automatically transforms each monitored business process into a powerful stream of business metrics, generating and storing new business events that are enriched with the KPIs that matter most to your organization. This means you’re not just observing how your IT impacts your business; you’re measuring how your business performs in real time.

With this new capability, you’re in complete control:

• Choose how often metrics are generated, from high-frequency snapshots for fast-moving operations to broader intervals for strategic monitoring of longer business processes.
• Define the timeframe of analysis, enabling a moving window of business performance that updates continuously.
• Track every business KPI with precision, from conversion rates to fulfillment times, total revenue, value of approved loans, business exceptions, and more.

These automatically-generated business metrics give you a dynamic, always-on view of how your business processes evolve over time. The result is a smarter, data-driven way to detect trends, anticipate issues, and optimize performance long before it impacts your customers or your bottom line.

Business impact of an IT problem

Modeling business flows as entities allows Dynatrace to show when IT problems impact critical business processes directly in Problems.

Here’s how the analysis works:

• Root-cause analysis identifies all IT entities impacted by the problem.
• When exploring a specific problem, the Business Impact Analyzer checks whether affected entities are connected to any business flow entities.
• Problems displays this connection in a new single-value tile, showing whether one or more business flows are impacted.

From this tile, you can navigate to Business Flow for detailed exploration.

Problem investigation mode in Business Flow

From Problems, you can drill down into the Business Flow app for affected business flows. This opens in problem investigation mode, which highlights:

• The impacted business flows from the list of entities.
• A timeframe aligned with the IT problem.
• A detailed view of all the business KPIs over time.

Exploring the different parts of the business flow tree or checking the business KPIs over time allows you to discover the direct impact of an IT problem on a business process.

Currently, the analysis focuses on business processes that are connected to affected IT entities. Soon, this will extend to step-level impact analysis—identifying fulfillment drops and enabling navigation to the exact step affected.

Take the next step into business observability

Dynatrace continues to enhance IT problem contextualization with the Business Impact Analyzer, connecting technical issues to critical business processes mapped in Business Flow.

Discover how to create your first business flow configuration and activate it as an entity in Smartscape.

The post Stop treating all IT problems the same: Prioritize what matters most with business process entities now in Dynatrace Smartscape appeared first on Dynatrace news.

Kubernetes has rapidly established itself as a cornerstone technology for deploying and managing applications at scale. It’s designed to streamline operations and offer considerable potential for fostering carbon-friendly applications by including automated deployment and dynamic scalability, which allow for efficient resource allocation and significant savings through optimized container orchestration. With its intelligent provisioning of containers, Kubernetes aims to optimize the use of underlying resources, ultimately leading to better infrastructure utilization compared to traditional, often over-provisioned, approaches.

However, the increasing complexity of Kubernetes environments necessitates active and diligent management of their carbon footprint. Mainly because, despite their promise of efficiency, if not properly managed, Kubernetes environments can paradoxically lead to excessive carbon emissions.

Measure Kubernetes energy consumption and carbon footprint

With the latest release of Cost & Carbon Optimization, Dynatrace now provides reporting and analytics for your Kubernetes infrastructure, allowing you to understand the carbon footprint (both energy and carbon emissions – CO2 equivalent) of Kubernetes clusters, namespaces, and nodes. You can now measure and determine whether the utilization of Kubernetes resources justifies their carbon footprint, identify anomalies and trends, and compare this against emissions from physical or single-use host infrastructure to ensure that migrating workloads to Kubernetes provides an appropriate sustainability return on investment.

Supporting all modes of Kubernetes monitoring, whether deployed in the cloud or on-premises, Cost & Carbon Optimization offers the following capabilities for your Kubernetes environment:

• Understand the energy and carbon footprint of Kubernetes clusters and namespaces with the new Kubernetes explorer interface.
• Highlight optimization opportunities by correlating the carbon footprint with the size of the cluster or node via Kubernetes metrics.
• Confirm if sustainability or optimization efforts deliver the assumed results with automatic time-period comparisons.
• Inspect resource requests and limits, quotas, or idle workloads/jobs that reserve resources but run infrequently with one-click contextual navigation into the Kubernetes app.
• Create custom reports using Notebooks or Dashboards
• Calculate your carbon footprint without installing additional complex Kubernetes plug-ins or configurations by leveraging information from your existing Dynatrace Kubernetes platform monitoring.
• Provide accurate measurements by using certified energy and carbon calculation algorithms.

Why bother with setting up a sustainable Kubernetes environment?

If you already use Kubernetes, or plan to migrate workloads to Kubernetes, you should consider using Dynatrace Cost & Carbon Optimization today to unlock the following benefits:

• Energy use is a direct driver of cost: Cloud infrastructure costs are largely driven by energy consumption. CPU, memory, storage, and networking all consume power, and cloud providers factor this into pricing. By measuring energy usage, you can track the underlying metric that influences cost.
• Carbon footprint adds environmental context: Carbon footprint translates energy consumption into environmental impact. This is especially valuable for organizations with sustainability goals or Environmental, Social, and Governance (ESG) reporting requirements.
• Opportunities to align cost and environmental optimization: Inefficient clusters, namespaces, and nodes that consume more energy (and thus emit more carbon) are often the ones driving up cloud costs. Identifying high-carbon workloads can highlight areas for both cost and environmental optimization.

Practical examples

Once activated, you can easily identify the Kubernetes clusters and namespaces with the highest energy consumption and carbon emissions, and correlate this with additional metrics from Dynatrace Kubernetes monitoring to identify the most costly and underutilized Kubernetes resources. Drill down from the Cost & Carbon Optimization app into Kubernetes to get more information on resource requests and limits, quotas, or idle workloads/jobs that reserve resources but run infrequently. Once identified, you can easily leverage this information to optimize your carbon and costs.

Use our ready-made dashboards to gain a deeper understanding of the data over time and identify anomalies that require further investigation. A large spike in energy and carbon usage could be a normal side effect of increased usage; it could also signal a change based on automatic scaling or inappropriate resource provisioning.

But why stop with focusing on your existing infrastructure only? Measure and compare carbon emissions from single-use servers against Kubernetes infrastructure and ensure that migration efforts meet the desired sustainability goals. You can even start gamifying this and challenge your engineering teams to develop solutions that delight end-users and the environment.

Start optimizing costs & carbon

If you’re already monitoring your Kubernetes infrastructure with Dynatrace, measuring Kubernetes energy consumption and emissions is as simple as installing and activating the Cost & Carbon Optimization app from Dynatrace Hub.

The app is available to all Dynatrace SaaS customers and leverages capabilities outlined in your rate card, supporting all Dynatrace Kubernetes monitoring modes. Are you interested in learning more? Do you know that Dynatrace Cost & Carbon Optimization is certified for accuracy and transparency? Have a look at our documentation and learn how to calculate and monitor your IT costs and carbon footprint. Then use the link below to install Cost & Carbon Optimization in your Dynatrace environment.

The post Sustainable Kubernetes at scale: Cost & Carbon Optimization appeared first on Dynatrace news.

The business observability gap in cloud-based transactions

Business observability, at its best, delivers real-time insights into business health, reporting, and interpretation of the metrics and KPIs that business and IT leaders need to make decisive and effective decisions.

But how can you access this data when cloud-based solutions deliver your critical services? One of the more common examples is payment gateways, or payment service providers (PSPs)—hosted services that verify account details, check for available funds, and transfer money into your business merchant account.

There’s a wealth of business data in your systems’ transaction requests to these PSPs and other SaaS solutions. Without visibility into this data, you’re left with an incomplete and delayed understanding of transaction success, sales data, and business health. This is particularly problematic since the transaction success or failure status is often embedded within the response body.

Here are some of the challenges our customers have identified:

• Delays in resolving issues. Failed transactions are only discovered in scheduled reports or when customers complain.
• Reconciliation discrepancies. Inconsistencies between internal records and PSP reports lead to frustrating, time-consuming, and error-prone manual work.
• Inability to understand short-term trends. Identifying failure patterns for specific providers or transaction types is nearly impossible without timely and detailed transaction data.
• Compliance risks. Lack of granular detail makes auditing and demonstrating compliance with payment regulations more challenging.

Business events from outgoing web requests

Dynatrace business events are in a special class designed to support even the most demanding business use cases. Whether derived from OneAgent, log files, RUM sessions, or APIs, business events deliver real-time lossless access to critical business data—wherever it lies. In particular, OneAgent’s unique capability to extract business data from in-flight application payloads—without writing any code—has proven invaluable to hundreds of our customers.

OneAgent now supports capturing business events from outgoing web requests that are specifically designed to illuminate these blind spots. You can now transform critical business information within your outgoing web requests and their corresponding responses into structured business events, which can then be analyzed, correlated, and acted upon within Dynatrace.

Use case: Business events and payment gateways

Here’s how it works, and what it means for our payment gateway use case.

Granular configuration for targeted capture

• Define endpoint-specific rules to capture data from requests to specific URLs or IP addresses (for example, api.stripe.com/payments or paypal.com/checkout).
• Define method-specific rules to capture data from relevant HTTP methods like POST or PUT that are used to initiate transactions.

Deep insight into request and response payloads

Support for business-event capture from outgoing web requests adds compelling new value and expands on current OneAgent capabilities for extracting business data from in-flight application payloads.

• Extract data from the request body. Imagine you’re sending payment requests that include customer account numbers, transaction amounts, and transaction identifiers. You can now define rules to extract these key pieces of information directly from your JSON or XML request bodies. This is crucial for linking your internal transaction IDs to the business data sent to the provider.
• Extract data from the response body. Potentially greater value lies in the response body. Often, PSPs return transaction status messages (for example, transactionStatus:success, authorizationResult:approved, or responseCode:1954) within the response body. Extracting these status messages allows you to report, alert, and act on failures or anomalies as they occur.

Transform raw data into meaningful business insights

Business data increases in value when enriched with business and IT attributes. For example, you could map extracted fields to meaningful attributes of a “Payment Transaction” business event. These attributes might include payment_provider_id, transaction_amount, and customer_id, extracted from the request body, and payment_status extracted from the response body.

These events are automatically enriched with Dynatrace observability data, such as the request’s originating host, service, user journey, or geographical source, facilitating business and IT collaboration.

Real-time visibility and proactive alerts

• Real-time business transaction monitoring. Know each PSP transaction’s success, failure, and value as it happens, not hours later.
• Custom dashboards. Dashboards make it easy to visualize different PSPs’ success rates and revenue, exposing bottlenecks and highlighting business and failure trends.
• Proactive alerting. Set up alerts based on real-time payment status messages. Trigger alerts on failed transactions over a certain amount, or when the success rate SLA degrades.

Enhanced traceability and root cause analysis

• End-to-end transaction tracing. Trace the entire lifecycle of a payment, from the user initiating the purchase through your internal services to the outgoing request to the PSP and the response status indicating success or failure.
• Accelerated root cause analysis. Quickly determine the source of payment transaction failures, bottlenecks, and anomalies to speed resolution and improve business outcomes.

Payment gateway example: From opaque to transparent

Here’s what this could mean for your organization:

1. A customer attempts a major purchase. Your e-commerce system sends the request to your PSP, but the transaction is declined.
2. OneAgent captures relevant business data from the outgoing request, including customer ID and transaction amount attributes. Dynatrace also captures the relevant response fields, including the status:declined message.
3. A “Payment Failure” business event is automatically generated in Dynatrace. This event triggers an alert to notify your operations and customer support teams.
4. Your customer support team can now proactively contact the customer while your operations team works to resolve the issue, knowing exactly why the transaction failed and which provider was involved.

This is possible without any code changes. Extracting business data from outgoing requests and responses turns opaque customer interactions into transparent, actionable business insights, empowering you to improve customer experience, optimize payment workflows, and reduce operational risk.

Initial support for outgoing web request capture is available for Java; see Supported Technologies for details. Additional technology support will be available soon.

The post Extend business observability: Extract business events from outgoing web requests appeared first on Dynatrace news.

While Dynatrace and Microsoft Power BI offer significant value on their own, connecting the two can exponentially enhance the insights they unlock. Here, we explore how companies that use both platforms can benefit from the Microsoft Power BI Connector from Dynatrace.

The impact of Dynatrace and Microsoft Power BI

Dynatrace is the leading AI-powered observability and security platform. It helps organizations understand their business like never before through AI-driven analytics and automation and offers deep insights into IT and business health based on real-time data from logs, metrics, traces, and business events.

Microsoft Power BI provides interactive visualizations and business intelligence capabilities with an intuitive user interface. It allows end users to create reports and dashboards easily. It integrates seamlessly with various data sources and offers robust manipulation and visualization features to help organizations accelerate the time to value from business analytics.

The synergy of integration

Combining the analytical prowess of Microsoft Power BI with the comprehensive observability data in Dynatrace creates a powerful synergy. Key benefits of this integration include the following:

Complementary data visualizations

Dynatrace captures a wealth of data across critical IT and business metrics like application and infrastructure performance, user experience, security, and business health. Additionally, Dynatrace offers a rich and expanding set of dashboards, charting, and analytics capabilities.

With the Microsoft Power BI Connector, joint customers can now transform complex Dynatrace data sets into intuitive, interactive visualizations within Microsoft Power BI to maximize the value of their investment in both solutions.

Integrated reporting

Microsoft Power BI analysts often model information from various sources, including extra categorical dimensional data from local databases or spreadsheets. Now, joint customers can bring rich data from Dynatrace into Microsoft Power BI and model it alongside other data sources that would typically not go into an observability platform.

Microsoft Power BI analysts are accustomed to creating powerful reports from a variety of databases and Microsoft Excel sources. Now, joint customers can bring observability-driven insights directly into Microsoft Power BI and combine them with external data sources to provide an even richer view. The seamless integration offered by the Microsoft Power BI Connector allows analysts to delve deeper into the effects of software and infrastructure performance, application security, and user experience metrics on business outcomes. This, in turn, helps them to maximize the value of their investments in business intelligence and analytics.

Improved collaboration

The Microsoft Power BI Connector makes it easy for teams to collaborate on projects that are informed by integrated Dynatrace business and observability data. Therefore, teams across different business and technology departments can access and analyze the same performance metrics in a single platform, fostering a collaborative approach to problem-solving and decision-making. This shared understanding is crucial for aligning objectives and strategies across the organization, with cross-functional teams leveraging enormous amounts of observability data and business intelligence to achieve better outcomes.

Additionally, Dynatrace data observability capabilities can verify the quality and security of data, giving analysts a rich, trustworthy, and secure source of truth they can rely on for reporting.

How to implement the Connector

The Microsoft Power BI Connector allows Power BI to access data stored in Dynatrace Grail™ data lakehouse. Implementation follows a standard set of steps:

• Define the Dynatrace environment to be used as a data source. The environment’s user information will be authenticated, and Dynatrace Grail permissions will be verified.
• Run Dynatrace Query Language (DQL) queries to load data into Microsoft Power BI, or further transform the data using the Power Query editor.

Dynatrace uses the integration for cost analysis

The Dynatrace FinOps team uses the Microsoft Power BI Connector to derive deeper insights into our cloud costs, making it easier to report this information to senior-level executives.

The Dynatrace platform ingests details of our cloud provider costs along with infrastructure and application consumption data. The FinOps team combines this with dynamic categorical information stored in Microsoft Excel and relational models within a Microsoft Power BI model. Dynatrace provides all the necessary backend and scale, while Microsoft Power BI provides the reporting, and Microsoft Excel provides the required ingestion, ultimately providing the best of both worlds.

Apply data-driven decision making for success

The Microsoft Power BI Connector offers a significant advantage to organizations that prioritize data-driven decision-making. By leveraging the strengths of both platforms, analysts can achieve a comprehensive, real-time understanding of their IT ecosystem, enabling them to optimize performance, improve user experience, and drive strategic initiatives.

For those already using Dynatrace and Microsoft Power BI, the Connector is a logical step toward maximizing the value of their data assets and enhancing their operational efficiency.

Watch this Dynatrace Observability lab video for a closer look at the Microsoft Power BI Connector in action.

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

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Dynatrace Business Flow simplifies business process observability, connecting top-level process KPIs with detailed flow analytics. The app tracks the progress of every process instance, reporting individual and aggregated process performance, throughput, exceptions, and business outcomes.

With this update, Davis® AI can track and alert on KPI threshold violations to assure end-to-end process efficiency and reliability.

Anomalies are inevitable

Despite the deep IT observability you might have deployed, many of your business processes will likely encounter failures, intermittent delays, or ongoing inefficiencies. These issues can impact a wide range of business outcomes, from a direct reduction in revenue to a decrease in Net Promoter Score (NPS), from idle production lines to departmental budget overruns. Each business unit relies on a collection of processes, and each process has metrics and KPIs that can be affected by delays, exceptions, or failures. Examples include:

• A stalled connection between two services delays the process of validating food orders, resulting in dissatisfied customers, idle delivery drivers, and canceled orders.
• A failure in a third-party API breaks a loan validation process, reducing the number of applications approved and directly impacting the company’s revenue.
• A delay in warehouse order processing results in late deliveries, impacting customer experience.

Business process observability

Real-time business process observability can minimize the impact of these and other incidents by ensuring anomalies are detected quickly and include the IT context required for rapid—even automated—remediation. Business process observability is a new approach to ensuring process efficiency and reliability, quickly detecting and remediating anomalies, and identifying optimization opportunities. Are detected business exceptions specific to one host in a cluster? Which services does the credit check API depend on? Is there a fund transfer bottleneck at the source or destination bank?

Business process observability becomes increasingly important as new regulatory frameworks like the Digital Operational Resilience Act (DORA) impose strict operational resiliency requirements on financial and other institutions.

Dynatrace Business Flow

Business Flow is a Dynatrace® App that delivers on the promise of business process observability, connecting top-level process KPIs with supporting step- and instance-level analytics. Some of the questions Business Flow answers include:

• What is the average end-to-end process delay? How does this change over time?
• Are the business goals achieved? (For example, average loan amount, service response time, or close rate.)
• What is the business exception rate? Is there a trend?
• Which process steps are most problematic? Which steps take longer than normal?
• Were optimizations successful in their goal of improving performance or reducing exceptions?
• How does one process path differ from another regarding exceptions and throughput?
• What is the current status of a specific customer order?

Business Flow: KPI alerts

The latest version of Business Flow introduces a significant enhancement to support anomaly detection and alerting. App users can configure alerts for any of the four reported business process KPIs, leveraging Davis AI Anomaly Detection for continuous KPI analysis.

Alerting can be configured for each of the app’s four business process KPIs:

• Conversions or fulfillments. How many process instances—claims, deliveries, payments, etc—have successfully completed the final step?
• Errors or business exceptions. Distinct from IT errors, these are process-specific exceptions, usually defined in the application and reported within the application payload.
• Average duration. This is the cycle time of process instances, the elapsed time from start to finish.
• Custom business KPI. This can be any user-defined metric extracted from process instances. Examples include revenue, order quantity, loan amount, and approval rate.

Configure anomaly detection

Use the time series charts from the KPIs over time view to configure Davis AI Anomaly Detection for any of the four key business process KPIs. Each KPI graph includes a Create alert button.

To create an alert for a KPI, select Create alert to open the Davis anomaly detection configuration page. Choose the analyzer type: auto-adaptive, seasonal, or static threshold.

The configuration window is from the Davis AI Anomaly Detection app, adapted for use with Business Flow KPIs. Since Business Flow automatically defines the DQL for the KPIs, the anomaly detection configuration is quite simple.

There are three Davis AI Analyzers to choose from:

• Static thresholds are fixed and don’t change over time
• Auto-adaptative thresholds are calculated by Dynatrace automatically and adapt dynamically to your data’s behavior
• Seasonal baseline thresholds adapt to observed seasonal baselines and are charted with a confidence band

Alerts can be triggered for any of the three Davis Analyzers whenever the metric falls above, below, or outside the defined thresholds. Dynatrace Documentation provides configuration guidance for Davis AI Anomaly Detection.

The actor—or simulated Dynatrace end-user operated by the Davis AI Anomaly Detector in automated workflows—can be a service user or an interactive user with privileges to run the anomaly detector and execute the DQL queries for the time series chart. For more details, see service users.

Once configured, the new Davis AI Anomaly Detector evaluates a certain metric each minute, creating problem events when alert conditions are met. The time series charts add alert annotations to facilitate further analytics in such cases.

What’s next

For more information about alerting on business process KPIs, please visit Dynatrace Documentation.

You can also try out the new Business Flow alerting feature in the Dynatrace Playground.

Note that anomaly detection currently supports process flows of less than 60 minutes. Support for longer-running processes will be added in a future release.

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Globally, organizations are increasingly prioritizing sustainability. Board-level mandates and executive-level sponsorship have become the norm. Motivations include regulatory pressures, favorable investment potential, cost savings, competitive advantage, talent acquisition, and moral imperative. While a dynamic political climate can disrupt how these drivers are prioritized, the goal remains important, and momentum remains strong.

IT carbon footprint is top of mind for observability professionals in many industries. The explosion of AI models shines a new spotlight on the issue, with a recent study showing that using AI to generate an image takes as much energy as a full smartphone charge. For IT, a natural focus should be reducing carbon emissions from electricity consumption from on-premises, hybrid, and multicloud computing.

The challenge along the path

Well-understood within IT are the coarse reduction levers used to reduce emissions; shifting workloads to the cloud and choosing green energy sources are two prime examples. To continue down the carbon reduction path, IT leaders must drive carbon optimization initiatives into the hands of IT operations teams, arming them with the tools needed to support analytics and optimization.

Cloud service providers (CSPs) share carbon footprint data with their customers, but the focus of these tools is on reporting and trending, effectively targeting sustainability officers and business leaders. Unfortunately, they lack the detailed IT context practitioners need to identify carbon reduction opportunities and analyze optimization solutions. While stand-alone tools attempt to complement CSP solutions, they face similar challenges:

• Data granularity and accuracy: Tools struggle with providing detailed and accurate data on carbon emissions. This is partly due to the complexity of instrumenting and analyzing emissions across diverse cloud and on-premises infrastructures.
• Real-time monitoring: The periodic reports from cloud service providers lack real-time monitoring and actionable insights, limiting IT teams’ ability to make immediate adjustments to reduce carbon footprints.
• Integration with existing systems and processes: Integration with existing IT infrastructure, observability solutions, and workflows often requires significant investment and customization.
• Quantifying impact: Quantifying the effectiveness of various emission reduction methods can be challenging, making it difficult for IT leaders to prioritize actions and justify sustainability investments.

The Dynatrace carbon optimization solution

Introduced in 2023, Carbon Impact helps practitioners identify and evaluate meaningful opportunities to optimize their cloud and on-premises infrastructures. The Carbon Impact app directly supports our customers’ sustainability efforts through granular real-time emissions reporting and analytics, translating host utilization metrics into their CO2 equivalent (CO2e). By leveraging existing OneAgent® instrumentation, customers can get started in minutes with no new instrumentation hurdles.

Today, Carbon Impact has a new name: Cost & Carbon Optimization. The name change reflects the app’s expansion into cloud cost analytics, driven by the understanding that optimization approaches for both cost and carbon mostly overlap. You’ll be able to read more about our approach to cloud cost optimization in an upcoming blog post.

Industry certification for Dynatrace Cost & Carbon Optimization

To enhance the trust our customers and partners have in our approach, we commissioned the Sustainable Digital Infrastructure Alliance (SDIA) to test and certify the Cost & Carbon Optimization app. The certification focuses on accuracy and transparency in calculating greenhouse gas (GHG) emissions for AWS, Azure, GCP, and on-premises host instances.

The certification results are now publicly available.

“The SDIA has certified Dynatrace Cost & Carbon Optimization app, ensuring its accuracy and adherence to the environmental management principles outlined in ISO 14004.

“Dynatrace Cost & Carbon Optimization is a reliable estimation system to calculate the operational GHG emissions of IT infrastructure both in cloud and on-premises environments. The calculations and methodology used are in line with the best available scientific approach, as well as with relevant reporting requirements. Further, Dynatrace meets the requirements on transparency, allowing customers to have insight into the way these metrics are calculated, as well as recreating the measurements themselves for independent verification.”

Actions resulting from the evaluation

The certification process surfaced a few recommendations for improving the app. These are the outcomes:

• We replaced GCP’s emissions estimations with more accurate data from Ember, a global not-for-profit clean energy think tank.
• We implemented a wasted energy metric in the app to enhance practitioner actionability.
• We are updating product documentation to include underlying static assumptions.

Transparency breeds confidence

In the spirit of transparency, we’re publishing details of the data sources and assumptions the app makes. Some highlights:

• Data conversion: To derive CO2e and wasted energy metrics, we convert OneAgent data using external sources:
  • Energy emission data is sourced from the European Energy Agency and the Cloud Carbon Footprint tool to determine emission factors specific to cloud data center locations.
  • Thermal design power (TDP) values are derived from AMD and Intel to calculate CPU power consumption.
  • Power usage effectiveness (PUE) is derived from data provided by the cloud providers and data center operators.
• Static assumptions: To complete the calculations, we apply these assumptions:
  • Memory power calculations assume a static draw value of 3 W for each 8 GB memory module.
  • Network traffic power calculations rely on static power estimations for both public and private networks. These estimates are converted using the emission factor for the data center location. Static assumptions are:
    • Local network traffic uses 0.12 W per GB.
    • Public network traffic uses 1.0 W per GB.
  • CPU calculations apply these assumptions:
    • A virtual CPU (vCPU) on any cloud host equals one thread of a physical CPU core, with two threads per core.
    • A CPU operating at 100% utilization consumes power equal to its TDP.
  • Storage calculations assume that one terabyte consumes 1.2 Wh.
  • Cloud storage is replicated twice, which doubles the energy consumption per terabyte.
  • Annual country-level emission factors from the European Environmental Agency are used as input to the calculations.

Connecting carbon reduction to cloud cost optimization through the FinOps Framework

As we merge cost and carbon analytics into a single solution, we expect to reduce redundant or conflicting optimization efforts. Approaches to optimizing IT carbon emissions overlap significantly with those applied to cloud cost management (CCM). Optimizing resource utilization and reducing waste benefit each of these goals. The FinOps Foundation includes sustainability in its framework, stating, “FinOps and cloud sustainability mutually support each other through a similar approach to conscientious and responsible technology usage that enables workload efficiency. If you’re doing one of these – you’re amplifying the other.”

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Business processes support virtually all aspects of an organization’s operations. They’re often categorized by their function; core processes directly create customer value, support processes increase departmental efficiency, and management processes drive strategic goals and compliance. Sometimes overlooked is a fourth category we might call “long-tail processes;” these are the ad hoc or custom workflows that develop in response to gaps between systems, applications, departments, or workflows. Regardless of their role, every business process is designed to improve business outcomes.

Most organizations have hundreds of business processes across these four categories, supported by IT systems through a mix of on-premises, cloud, and SaaS solutions. Business processes are valuable assets, and the lack of visibility is alarming, representing both risk and opportunity.

The whole is other than the sum of its parts

Processes are typically quite complex, involving multiple disparate systems, external interfaces, and human interactions. Despite the deep IT observability you may have deployed, you still can’t infer process health from system status; problems occur even when the underlying infrastructure is healthy. Many of your business processes likely encounter failures, intermittent delays, or ongoing inefficiencies, yet your observability solution likely remains oblivious to these issues.

Given the business-critical nature of many of these processes, it’s clear that the risk from unobserved processes is substantial, tangible, and an unfortunate shared experience.

Is business process management the answer?

Cost and complexity are two primary factors that limit the adoption of business process management and mining solutions. License fees are only the tip of the cost iceberg; it’s not uncommon for a process mining implementation to take many months and cost over $100K per process. Complex data integrations require significant skilled work and coordination from multiple teams and require ongoing maintenance. These factors often limit deployment to a few mission-critical processes, usually managed by a business process management (BPM) center of excellence. This centralized approach can compel organizations to prioritize process monitoring and optimization initiatives to just a few mission-critical processes while neglecting those with less obvious—though significant—impact on business outcomes.

At its best, business process management embraces collaboration between business teams responsible for optimizing business outcomes and IT teams responsible for system observability. But even the best BPM solutions lack the IT context to support actionable process analytics; this is the opportunity for observability platforms.

Enter business process observability

Business process observability determines process health and performance through data gathered at each step, leveraging appropriate levels of system monitoring or interfaces. Log files and APIs are the most common business data sources, and software agents may offer a simpler no-code option.

• Transaction data (such as purchase confirmations, loan approvals, or service requests) is used to calculate inter-step timings and capture the step’s outcome (for example, success, failure, or conditional branch).
• Transaction metadata (such as a product SKU, loan amount, or service address) enriches process insights and increases analytic granularity.
• Transaction context (such as the responsible host, service, or system process) connects each step to its supporting IT infrastructure for troubleshooting and optimization.
• Correlation IDs (such as a transaction ID, customer number, or order number) are used to reassemble discrete transactions into a sequenced end-to-end flow to support detailed process analytics.
• Process health is determined through calculated metrics and process-specific KPIs such as throughput, revenue, cycle time, and exception rate.

To summarize, business process observability:

• Treats the process as a business asset or entity with unique discernable flows.
• Determines process health via data collected at each step, reported as process-specific business KPIs.
• Includes end-to-end and step-specific details for every process instance.

Process observability benefits include enhanced operational efficiency, reduced costs, increased productivity, compliance visibility, and improved customer satisfaction. These benefits come from robust process analytics, often augmented by AI. They’re initially realized reactively and, as organizations mature, proactively, in two key categories:

• Remediation: When process KPIs degrade, process analytics uncover the root cause to inform or automate service recovery.
• Optimization: Whether an ad-hoc initiative or a continuous improvement function, process analytics provide the data-driven foundation for process optimization.

The Dynatrace advantage

Few observability platforms offer business process observability. At best, they group metrics from isolated process steps into a linear process-like view, ignoring the complexity of real-world process flows and lacking end-to-end flow details to support effective analytics and optimization.

Dynatrace treats your business processes as true business assets, connecting business KPIs with end-to-end process analytics to meet the collaboration and optimization needs of business and IT teams. Dynatrace makes it easy to get started and cost-effective to implement broadly.

Dynatrace business process observability leverages key platform capabilities, including:

Business events, which provide easy access to business data, are automatically enriched with IT context. Business events can come from:

• OneAgent – a unique capability offering configurable no-code access to in-flight application payload.
• Log files – using OpenPipeline to extract and transform business data while reducing log management and storage overhead.
• API – to ingest data from relevant business systems.
• RUM – for high-precision user journey analytics.

Business Flow is a Dynatrace® App that simplifies business process configuration, reporting, and analytics.

• Easy configuration of process flows
• Automatic KPI reporting
• Granular flow details

Simplified access to business data coupled with a purpose-built app makes it easy to get started with business process observability. It’s not uncommon for Dynatrace customers to implement Business Flow in just a few weeks, often without any development effort, with only incremental subscription costs. To learn first-hand about some of their successes, check out a few of these Business Analytics customer breakouts from our recent Perform user conference. You can also try it yourself in our Dynatrace Playground (registration is required).

Wherever you might be on your transformation journey, business processes form the framework that drives better business outcomes. This is an opportune time to expand the value IT delivers to your business teams.

The post Business process observability: An IT solution to a business challenge appeared first on Dynatrace news.

There’s a goldmine of business data traversing your IT systems, yet most of it remains untapped. To unlock business value, the data must be:

• Accessible from anywhere. Data has value only when you can access it, no matter where it lies.
• Easy to access. Simplicity accelerates time-to-value and reduces implementation and maintenance costs.
• Real time. Agile business decisions rely on fresh data.
• Precise. Accuracy provides the confidence needed for business automation.
• Contextualized. Metadata enrichment improves collaboration and increases analytic value.

The Dynatrace® platform continues to increase the value of your data—broadening and simplifying real-time access, enriching context, and delivering insightful, AI-augmented analytics. Our Business Observability solution is a prominent beneficiary of this commitment.

Business events: Delivering the best data

It’s been two years since we introduced business events, a special class of events designed to support even the most demanding business use cases. Since then, many of our customers have embraced the opportunity to explore and adopt new business observability use cases. Most of these leverage the unique capability of Dynatrace OneAgent® to extract business data from in-flight application payloads—without writing any code. Other data sources, including APIs and log files—are used to expand access, often to external or proprietary systems. Enhancing access to business data from log files is an important priority, and OpenPipeline makes this a reality.

Dynatrace OpenPipeline is a new stream processing technology that ingests and contextualizes data from any source. You can now use OpenPipeline to extract business events from log files, complementing OneAgent as a primary source of business data. This is especially important when legacy or proprietary systems don’t meet OneAgent’s environmental prerequisites; in these cases, log files are usually the preferred source of business data.

In fact, it’s likely that some of your critical business systems already write business data to log files. For years, logs have been the dominant approach many observability vendors have taken to report business metrics on dashboards. You might still be using one of these tools despite the drawbacks, which include a lack of IT context, constraints on data privacy and data retention, and, as the only convenient source of business data, a limiting lack of breadth. OpenPipeline makes migrating these use cases to Dynatrace easy, helping you overcome these limitations to realize greater value.

Use case categories

It’s helpful to categorize the nearly unlimited use cases covered by Business Observability. Two of the most important categories are:

• Business reporting, analytics, and automation. Track business metrics, key performance indicators (KPIs), and service level objectives (SLOs)—automatically and in context with IT infrastructure and services—to promote collaboration between business and IT teams.
• Business process monitoring and optimization. Monitor and optimize business processes with real-time visibility into process KPIs and detailed analytics for each step to improve customer satisfaction, increase operational efficiency, and reduce cost.

Most of the use cases in these two broad categories benefit from the flexibility that comes from multiple available sources of business data. For example:

• An airline’s reporting and analytics dashboard includes data showing flights, passengers, available seats, passenger load, revenue per passenger, flight crew staffing, arrival delays, and customer satisfaction metrics. The data may come from a mix of systems, including a departure control system (DCS), an airline reservation system (ARS), a legacy inventory control system, and a SaaS-based Voice of the Customer (VoC) solution.
• A financial institution’s loan origination business process includes a series of process milestones, including loan application, credit scoring, application review, contract generation, CRM, and loan funding. All of these steps are critical components of the process, likely to be implemented using different systems. Furthermore, to understand process health, individual steps must be viewed in the context of the entire process. For this, we use Business Flow to track, analyze, and optimize complex business processes, treating the process as an observable IT and business asset.

Use OpenPipeline to extract business events from logs

Using OpenPipeline, you can ingest log data into Dynatrace from a wide range of sources, including OneAgent, Extensions, the Log ingest API, and OpenTelemetry. The pipeline includes a configurable business event processor as part of the data extraction stage; this processor is used to extract and convert relevant business data into business events.

There are many benefits to extracting business events from log files. These include:

• Improved data privacy. Sensitive business data is separated from IT observability data.
• Improved data management. Fine-grained permission and retention policies can be tailored to individual business use cases.
• Reduced storage and query overhead for business use cases. Business events are a small, often negligible subset of log data.
• Simplified and enhanced analytics efficiency. Business events from log files are unified with business events from OneAgent, RUM, and API.

Extracting business events from logs: Configuring OpenPipeline

The OpenPipeline app guides you through the three configuration steps required to extract business events from log files:

1. Identify the source of the log file.
2. Define OpenPipeline’s dynamic routing matching criteria used to route the log lines of interest to a second pipeline.
   
3. Create the target pipeline. Use the Data extraction tab to define the matching condition that creates the business event. You need to include static or dynamic Event type and Event provider fields.
   

Within the target pipeline, you can also define processing rules, extract metrics, set the security context, and define retention periods. Log data is then processed accordingly, stored in Dynatrace Grail™ causational data lakehouse, and available for your Business Observability use cases.

The value is in the data

OpenPipeline broadens Dynatrace’s unified access to the best data to deliver the best value. Now’s the time to see how it can benefit your organization.

For more details about OpenPipeline read this Dynatrace OpenPipeline blog post.

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The world is more connected than ever before. With global e-commerce spending projected to reach $6.3 trillion this year¹, more than two-thirds of the adult population now relying on digital payments² for financial transactions, and more than 400 million terabytes of data being created each day³, it’s abundantly clear that the world now runs on software. The implications of software performance issues and outages have a significantly broader impact than in the past—with the potential to negatively impact revenue, customer experiences, patient outcomes, and, of course, brand reputation. Business resiliency has become a board imperative to bolster their organizations against the downside of these risks.

Ideally, resiliency plans would lead to complete prevention. But in a cloud-native world, resiliency must expand to include the ability for organizations to recover quickly from failures and ensure business continuity.

In many ways, the shift to cloud computing and the adoption of cloud-native architectures have enabled organizations to realize greater resiliency alongside scalability. However, it has also introduced more risk vectors that teams must consider when balancing performance, resiliency, and cost. Software performance can be compromised in many ways, including software bugs, cyberattacks, overwhelming demand, backup failures, network issues, and human error. Each of these factors can present unique challenges individually or in combination.

Implementing a robust monitoring and observability strategy has become the foundation of an organization’s ability to improve business resiliency and stay in control of their critical IT environments.

A unified platform approach to observability and security

Dynatrace and its partners offer powerful solutions to complex business resiliency challenges through an observability and security platform that delivers a unified view of applications, infrastructure, and business processes. Using this holistic approach, organizations can proactively identify and address potential issues before they negatively impact the business, operations, or user experience.

“Today’s rapidly evolving technology environment opens the door to both new opportunities and new threats. To keep pace, business resiliency is a must. It requires a clear understanding of business priorities and deep visibility into IT environments. Dynatrace helps organizations build resilient business capabilities that keep pace with evolving needs while providing the observability required to enable proactive issue detection and automated remediation.”

– Ram Ramalingam, Global Lead, Software and Platform Engineering, Accenture

Organizations increasingly rely on hybrid and multicloud environments to support business operations. But gaining observability of distributed environments, such as Kubernetes, microservices, and containerized application deployments, presents formidable challenges. Simply put, debugging and troubleshooting issues in a complex distributed system are beyond human scale to rapidly diagnose and remedy—pointing to the need for a solution that provides more than basic monitoring.

End-to-end observability and automation bolster business resilience

The Dynatrace end-to-end observability and security platform provides teams with critical insight into the health and performance of their infrastructure and applications. Powered by AI and automation, Dynatrace observability and security enable teams throughout an enterprise to eliminate silos, make better decisions, and innovate faster.

Release high-quality code every time

Dynatrace accelerates innovation through application observability capabilities that enable developers to monitor code behavior in real time, detecting anomalies and performance bottlenecks early in the development cycle. By integrating with continuous integration and continuous delivery (CI/CD) pipelines, Dynatrace helps ensure that only high-quality code reaches production.

Automate runtime application security and security posture management

Cyberattacks pose a constant threat to business continuity. In fact, recent research estimates the cost of downtime to be an estimated $9,000 per minute on average and potentially as high as $5 million per hour4. Dynatrace runtime application security capabilities enable advanced threat detection and response, helping organizations identify and mitigate malicious activities before they cause significant damage.

Likewise, Dynatrace security posture management automates the detection and remediation of misconfigurations to minimize the attack surface. By correlating security data with performance metrics, security teams can prioritize threats based on the potential impact on critical business operations.

Prevent outages during peak demand

Managing high demand is essential for preventing outages during peak usage periods. Using Dynatrace synthetic monitoring capabilities, organizations can simulate user behavior and identify performance bottlenecks under load. Teams can use this information to optimize infrastructure and application performance, ensuring that systems can handle increased traffic without compromising user experience.

Use AI to deliver great user experiences

Network issues, backup processes, and human errors are common sources of disruption to business operations and impact customer satisfaction. Through the power of causal, predictive, and generative AI working in concert, Dynatrace enables IT teams to pinpoint the root cause of issues and resolve them efficiently. Dynatrace’s digital experience monitoring (DEM) capabilities provide insights into end-user experience, helping organizations maintain healthy Service Level Agreements (SLAs) and Service Level Objectives (SLOs).

Ensure business resiliency and high performance with unified observability and security

As the digital landscape continues to evolve, businesses will increasingly demand resilient and high-performing infrastructure and applications. Correspondingly, business resiliency will remain a top priority for boards and executives alike.

The Dynatrace unified observability and security platform helps customers make informed decisions and minimize the potential for mistakes empowering IT teams with actionable insights. Automation solutions with embedded AI capabilities reduce the risk of human error by eliminating manual tasks and providing clear guidance for complex operations. As a result, Dynatrace will increasingly become an indispensable tool for organizations seeking to thrive in the face of uncertainty.

Contact us to learn how Dynatrace can help your organization maintain business resiliency through any contingency with unified observability and security.

¹ _{Shopify Global E-commerce Sales Growth Report}

² _{COVID-19 Drives Global Surge in Use of Digital Payments – World Bank Group}

³ _{Amount of Data Created Daily (2024) – Exploding Topics}

The post Why business resiliency depends on unified observability and security appeared first on Dynatrace news.

I’ve always been intrigued by monitoring the inner workings of technology to better understand its impact on the use cases it enables and supports. Driven by that value, Dynatrace brings real-time observability, security, and business data into context and makes sense of it so our customers can get answers, automate, predict, and prevent.

Executives invest in Dynatrace to enable their IT operations, security, and development teams to maintain visibility into all their digital services and ensure flawless, secure digital interactions.

A gold mine of answers

What may be a surprise for executives is that Dynatrace unearths a wealth of business insights from observability data. Information related to user experience, transaction parameters, and business process parameters has been an unretrieved treasure, now accessible through new and unique AI-powered contextual analytics in Dynatrace. Have you already thought about how you could use the data derived from your digital systems to accelerate your business and improve your ability to make decisions with real-time insights?

Executives drive business growth through strategic decisions, relying on data analytics for crucial insights. However, enabling faster and even automated decision-making is challenging due to a lack of real-time data access.

Several factors limit executives’ ability to get timely results for their business:

• Standard business intelligence (BI) systems don’t have access to the inner workings of digital systems, so teams don’t have access to the data they need.
• Different data types are in different silos, even averaged and generalized with lost information without a possibility for analytics in context.
• Common business analytics incur too much latency. There can even be days of reporting intervals, which hinders real-time business insights.
• Lack of visibility into business processes to improve, optimize, and remediate issues and systems harms business success.
• Different departments have different data sources and different ways to interpret data, causing misalignment.

With Dynatrace, executives can unearth a treasure trove of context-rich data that offers unprecedented insight into their business.

The real-time data in context with AI-driven analysis from Dynatrace provides executives with incomparable value and customer satisfaction to improve their business processes. The following are five examples of many:

• Order to cash processes to ensure timely order processing and revenue recognition.
• Order fulfillment to track the preparation and delivery of goods or services.
• Service provisioning to ensure resources are allocated, configured, and activated properly.
• Trade settlement to track the transfer of securities and funds after a trade is executed.
• Claims processing to ensure timely settlement, from first notice of loss to payment.

Turn business analytics real-time and get answers you couldn’t get before

My core goal was to create new value from automatically captured and enriched observability data and make it more accessible than today’s common BI solutions. That goal also requires eliminating barriers to real-time analytics, such as the many data transformation and preparation steps most that BI solutions need and the need for high-fidelity data in full context so users can find even the unknown unknowns.

Many organizations attempt to apply analytics to available data by making it static through data lakes, rehydrations, schemas, indexing, and warehousing, which seemed backward and complicated to me. This approach creates data silos, drives up costs, complicates contextual analysis, and limits the scope of business analytics.

To achieve my goal with Dynatrace, we had to rethink observability from the ground up. We concluded we needed to build a massively parallel processing data lakehouse at its core, as no existing database solution could overcome those analytics barriers at exabyte scale, especially in the era of AI.

With Dynatrace, we’ve created the only platform that can unify heterogeneous data, including logs, business events, user sessions, metrics, traces, emails, and much more with context and causal dependencies.

Dynatrace treats business processes as observable assets, putting each step in context with business and IT data. This integrated approach fosters mutual understanding and keeps business and technology in close lockstep, empowering everyone to get answers they couldn’t get before.

How executives leverage the newly gained visibility

Executives are change drivers. But change can only be driven with proper visibility and derived conclusions. Therefore, insights into how business growth and customer satisfaction are related to business processes are essential.

Business Observability employs a proven combination of three types of AI for analytics: causal, predictive, and generative. Using this hypermodal, “Power of 3” AI approach, teams can predict potential risks and disruptions. And with Dynatrace AutomationEngine, they can take preventive actions and enable intelligent orchestration and automation with business context. This predictive capability is crucial for business resilience as it allows organizations to anticipate challenges and mitigate their impact. Furthermore, by applying Dynatrace AI to historical data, executives can predict future trends and prepare contingency plans.

Only with this visibility is it possible to detect and fix broken processes, reduce and optimize process steps, steer investment priorities, automate and orchestrate, improve performance and user experiences, and ensure reliability and security.

Drive your business goals more effectively with a single source of truth

Organizations often struggle to align toward common goals, as every department measures them differently. What if you could take real-time data from your digital systems, such as consumption, usage, revenue, adoption, success rates, customer satisfaction, and more?

Dynatrace provides a single, real-time source of truth that eases alignment across departments to work toward joint critical business goals. Dashboards, apps, and reports with insights from digital systems originate from the same full-fidelity sources so that Business Observability becomes the “lingua franca.” As every department needs to place joint KPIs into its own context, Dynatrace makes it easy to expand, augment, and drill down to specifics. Dynatrace’s ability and ease to get answers to any question at any time is unmatched.

Dynatrace eases and increases data privacy by eliminating many steps in typical ETL (extract, transform, and load) and data warehouse procedures. Dynatrace unifies capture, storage, analytics, and visualization into a single platform that ensures consistent and gapless access to information. Dynatrace also certifies SSO access, encryption, filtering, and obfuscation techniques to meet the highest standards, so departments have access to what they need.

Causal AI: Connecting technical signals to business outcomes

At the core of Dynatrace’s business observability is our use of causal AI, one of the multiple AI models employed by Dynatrace, a unique capability that goes beyond correlation to uncover the actual root causes of issues and performance anomalies. Unlike traditional AI models that rely on pattern recognition alone, causal AI understands the why behind system behaviors. This enables business and IT leaders to make faster, more confident decisions by connecting technical signals directly to business outcomes. Whether it’s identifying the cause of a revenue-impacting slowdown or optimizing user journeys in real time, Dynatrace ensures that every insight is both explainable and actionable.

Becoming a data-driven enterprise

Business observability lets you tap incremental value from your observability investments, strengthening executives’ ability to drive businesses and customer satisfaction forward. A clear step towards a more data-driven enterprise, that is more competitive through insights from data of their digital services.

The post Real-Time Business Observability with Dynatrace appeared first on Dynatrace news.

Cloud-native technologies are driving the need for organizations to adopt a more sophisticated IT monitoring approach to satisfy the competitive demands of modern business. Business observability is emerging as the answer.

The ongoing drive for digital transformation has led to a dramatic shift in the role of IT departments. They’ve gone from just maintaining their organization’s hardware and software to becoming an essential function for meeting strategic business objectives. Today, IT services have a direct impact on almost every key business performance indicator, from revenue and conversions to customer satisfaction and operational efficiency.

As a result, organizations have been forced to reevaluate what success looks like for the modern IT department and how they monitor and manage the performance of IT services.

Seeking insights from data

Every organization depends on data to make decisions. However, too often teams are forced to rely on disjointed data that lacks context, which leads to poor decision-making and wasted resources.

This problem has worsened as enterprise operational complexity has grown. In today’s digital-first world, data resides across dozens of different IT systems, from critical business applications to the modern cloud platforms that underpin them. Connecting the dots between these various silos of data to understand the relationship between the health of IT services and the business outcomes they enable has become a particular challenge.

The journey toward business observability

Traditional IT monitoring that relies on a multitude of tools to collect, index, and correlate logs from IT infrastructure, networks, applications, and security systems is no longer effective at supporting the need of the wider organization for business insights. This traditional approach presents key performance metrics in an isolated and static way, providing little or no insight into the business impact or progress toward the goals systems support. Often, these metrics are unable to even identify trends from past to present, never mind helping teams to predict future trends.

As a result, organizations need to shift toward more sophisticated models of monitoring and managing IT operations. With hybrid and multi-cloud architectures rendering organizations’ environments more complex and distributed, cloud observability has become increasingly important. Likewise, integrating metrics and traces with log data helps to identify crucial context that reveals the interconnections among and importance of signals from all levels of the network. These capabilities are essential to providing real-time oversight of the infrastructure and applications that support modern business processes. With cloud observability, organizations can make data-driven decisions to improve the health of their IT services and proactively mitigate potential risks.

Partners such as Deloitte provide key expertise in cloud observability and are instrumental for many organizations embarking on digital transformation. By leveraging Deloitte’s strategic insights, businesses can align their IT investments more closely with their overarching business objectives, driving both efficiency and growth.

However, the journey doesn’t end there. The final stage is developing true business observability. Business observability ensures that all IT activity and investment is aligned with an organization’s strategic business objectives by enabling superior data-driven decision-making. It provides insights to help address not only operational issues such as cost reduction and risk mitigation but also customer-centric issues such as optimizing user journeys and creating personalized experiences.

Five ways business observability drives impact

There are several key advantages to making the transition to business observability, from mitigating the risks of adopting new cloud architectures and the challenges of data sovereignty, to rightsizing the IT estate and implementing greener technology. Five of the most important benefits of modern business observability are identified below.

1. Operational optimization. Across all sectors, system performance, infrastructure reliability, and transaction speeds are essential, whether it’s grid management for the energy industry or supply chain integration for retailers. An effective business observability strategy can help to meet these requirements by stabilizing the entire application stack, reducing operational expenditure, and preventing downtime in critical business systems.
2. Security and compliance. Organizations need to continually track transactions, user behaviors, and alerts to maintain security and compliance by detecting anomalies and indicators of potentially fraudulent activity or breaches. Business observability provides a cohesive approach to meeting these goals by offering a complete end-to-end view of application threats and vulnerabilities, assessed according to the level of potential risk to the enterprise.
3. Optimized experiences. By integrating data on user interactions, omnichannel behaviors, customer journeys, and purchasing patterns, organizations can take more effective action to deliver consistent and personalized experiences.
4. Resource optimization. Tracking and analyzing data from multiple sources enables businesses to optimize the performance of their IT services and prevent unnecessary downtime, while also reducing unnecessary resource consumption and carbon emissions through efficient asset utilization.
5. Agility and innovation. Organizations need oversight of the entire innovation pipeline, from ideation to implementation, to identify bottlenecks and streamline development and testing processes. Mature business observability capabilities allow businesses to reduce time-to-market for innovation by streamlining the product development cycle, while also providing key insights into user needs and the feasibility of potential feature additions.

Ultimately, organizations with mature business observability capabilities are better placed to use IT as a catalyst to drive better outcomes, streamline their operations, and mitigate risks, while unlocking greater customer satisfaction. This will help to place them at the forefront of the digital transformation landscape.

The post Business observability: From IT monitoring to driving digital transformation appeared first on Dynatrace news.

The business process observability challenge

Increasingly dynamic business conditions demand business agility; reacting to a supply chain disruption and optimizing order fulfillment are simple but illustrative examples. Business agility requires real-time visibility into process health and performance, measured by business Key Performance Indicators (KPIs) that are shared between business stakeholders and the supporting IT operations teams. However, business processes can be inefficient, broken, or violate Service Level Objectives (SLOs) even when the underlying system’s health is good; a process is greater than the sum of its parts. A business process only becomes observable when a) it is defined as a unique entity or asset and b) process-specific business KPIs are used to gauge health.

Business Process Management (BPM) solutions might seem like the answer, but they too often suffer from legacy technical constraints. Many are platform-centric, unable to expand beyond proprietary borders to embrace more common heterogeneous environments. They can be expensive to implement and maintain, rely on fragile data pipelines, and require highly skilled data analysts to ensure ongoing relevance. BPM solutions lack IT context, making them ill-suited for collaboration between business and IT operations teams.

Most business processes are not monitored. Why?

First and foremost, it’s a data problem. Locked away in disparate systems, difficult to access, and with different formats, business data can be days or weeks old. As a result, it takes significant effort to build and maintain these often fragile data pipelines. Undue reliance on log files as the primary business data source adds development overhead for implementation and maintenance, further limiting agility.

If you can collect the relevant data (and that’s a big if), the problem shifts to analytics. Business processes can be quite complex, often including conditional branches and loops; many business process monitoring initiatives are abandoned or simplified after attempting to map the process flow. Connecting data from different systems, stitching process steps together, calculating delays between steps, alerting on business exceptions and technical issues, and tracking SLOs are just some of the requirements for an effective analytics solution.

As a result, most business processes remain unmonitored or under-monitored, leaving business leaders and IT operations teams in the dark. Business health and IT health remain disconnected in separate silos, limiting opportunities for effective collaboration. The resulting business process blind spots delay response to business disruptions, leading to dissatisfied customers, BizOps friction, and inefficient IT resource allocation.

Business events: Addressing the data challenge

Dynatrace business events address the data challenge by making it easy to access real-time business data. Business events can come from anywhere—OneAgent^®, log files, Real User Monitoring (RUM) sessions, or external systems through an API. They deliver the real-time precision needed for confident data-driven business decisions. Uniquely, OneAgent can capture business data from in-flight application payloads, eliminating the need for application changes (for example, to write business data to a log file). Regardless of the source, business events are unified in Grail^® and are automatically enriched with Smartscape^® topology context, connecting business data directly to the supporting IT infrastructure.

Business Flow: Addressing the analytics challenge

Dynatrace addresses the analytics challenge with Business Flow (available on Dynatrace Hub), which was built using Dynatrace AppEngine. Initially released in April 2023, Business Flow masks analytics complexity through simple business process configuration and an intuitive interface. With Business Flow, you can:

• Connect business events from any source into an end-to-end process view.
• Report end-to-end process delays and measure delays between each step.
• Identify drops at each step.
• Report business exceptions at each step.
• Drill into the details of any step or process flow.
• Report process KPIs, including completed flows, average flow completion time, business exceptions, and a customizable business KPI.

Business Flow

The newest release of Business Flow introduces significant enhancements to cover more complex business processes and increase the depth of analysis.

To reduce the complexity of business process monitoring, it’s good practice to evaluate whether some process steps can be abstracted by monitoring only key milestones. For cases where process abstraction is not desirable, Business Flow adds two new features:

• Process branches – Business Flow now supports process branching. A branch can be conditional—only active for certain flows—as in the case of a document flagged for manual auditing. Branches can also represent alternate paths, one of which must be followed. A step may have up to five branches.
• Increased number of process steps – Business Flow now supports up to 20 steps in a single flow. Note that each branch is counted as a step when calculating the total number of steps in a process.

Business events are automatically connected into an end-to-end flow using a correlation ID such as order_number. Using consistent labels at each process step across all systems is good practice. For cases where the labels differ between systems (order_number at one step and order_id at another), Business Flow now supports step-specific local correlation IDs, overriding the global ID configured for the process.

New detailed flow views enhance process analysis. At each step, you can view a list of unique flows that a) pass through that step, b) are dropped at that step, or c) have been classified as in-flight (not yet complete). Each unique flow can be examined in its entirety to view the timestamps and attributes of the associated business events.

Greater business process complexity increases the potential for configuration errors. Business Flow now alerts on two conditions:

• Missing correlation ID – When a business event lacks a correlation ID, Business Flow can’t connect it to a unique end-to-end flow. Some use cases might benefit from isolated step metrics, but these are rare.
• Out-of-sequence flows – Business Flow generates an alert when an individual business flow skips a step. This condition can occur if a conditional process branch exists but has not been configured in Business Flow. A skipped step may also indicate a process anomaly worthy of investigation.

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 primary health indicators. Business Flow makes monitoring, analyzing, and optimizing complex business processes easier than ever.

The post Business Flow: Why IT operations teams should monitor business processes 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.

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