Enterprise cloud has outpaced traditional reactive monitoring. As workloads multiply across AWS, Azure, and Google Cloud—and extend into data centers—teams find themselves contending with vast amounts of telemetry, ephemeral infrastructures, and constant change. Visibility is tough; clarity of impact, ownership, and root cause is tougher.

Today’s tech stacks are distributed by design, featuring containers, serverless architectures, managed services, and data planes that can spin up and down in seconds. High-cardinality signals, fragmented logs, and partial traces create blind spots across accounts, subscriptions, and projects. In hybrid setups, network overlays, identity boundaries, and platform services blur the lines between where issues begin and how they propagate.

Organizationally, the challenge is even bigger. Platform, SRE, Dev, SecOps, and FinOps each hold a piece of the truth. However, inconsistent tagging and governance, manual runbooks, and handoffs across time zones can slow MTTR, fuel tool sprawl, and inflate budgets. The goal is to provide clear risk and cost insights, reduce noise, and deliver faster, context-rich answers.

However, visibility alone isn’t enough to achieve this goal. AI-driven context, such as topology-aware analytics, causal correlation, and safe automation, shifts operations from reactive firefighting to proactive prevention that’s aligned with SLOs, compliance, and budgets.

Today, we’re introducing Dynatrace enhanced cloud operations for AWS, Azure, and Google Cloud, delivering complete visibility across all your cloud and hybrid environments with deeper, actionable insights. If you’re ready to take the guesswork out of monitoring your cloud environments, read on to see how Dynatrace helps you collaborate faster, resolve issues earlier, and run at enterprise scale with confidence.

What is Dynatrace Cloud Platform Operations?

Dynatrace Cloud Platform Operations takes the guesswork out of monitoring by redefining how organizations manage complex cloud environments. By unifying all cloud signals—metrics, logs, and events—into a single AI-powered platform, Dynatrace delivers complete visibility and actionable insights at scale.

Every data point is enriched with context and analyzed by Dynatrace AI, enabling proactive automation and informed decision-making. This ensures faster troubleshooting, better resource efficiency, and simplified onboarding—all without the need for additional infrastructure components.

Organizations eliminate blind spots and accelerate resolution by gaining real-time visibility into the health, performance, and configuration of their cloud resources. This allows them to maintain the correct governance through tag-based control, ownership, and cost allocation, thereby aligning teams while reducing operational noise.

Additionally, the latest advancements in cloud observability provide real-time visibility into resource health, performance, and configurations, allowing teams to act quickly and decisively while reducing the time to resolution.

Start monitoring your cloud environment

Spin up monitoring without spinning up your infrastructure. The new cloud connections are fully managed by Dynatrace and guided by a simple wizard. It gets you from setup to actionable telemetry in minutes; no agents to wrangle, no custom pipelines to maintain.

Once connected, you gain instant visibility across all your cloud environments. Connect your AWS, Azure, or GCP accounts once, and Dynatrace auto‑ingests everything from compute and databases to storage, networking, and security configurations. Platform coverage has been expanded to capture more data types than ever, including metrics for any supported cloud service and a richer set of cloud events, such as hyperscaler‑native security alerts.

The new cloud connections are:

• Secure by design: native authentication offers least‑privilege access and auditable permissions.
• Practitioner‑friendly: a step‑by‑step wizard with built‑in checks and defaults works across accounts and regions.
• Zero overhead: the Dynatrace platform manages the connection end‑to‑end, so you focus on insights, not maintenance.

With all your cloud data unified, Dynatrace automatically applies the tags you already use in your cloud environments, bringing your existing operational model directly into the platform. Your existing cloud tags instantly drive access control, ownership, cost allocation, alert routing, and preventive workflows, with no manual tagging or re‑mapping required. Additionally, tag‑enriched signals keep operations aligned by allowing you to filter everything by owner, app, or environment for precise alert routing and actionable insights. This paves the way for more advanced analytics and clear insight into what’s happening across every environment.

The enhanced cloud ingest not only unifies telemetry and context; it also captures all configuration details (VPCs, load balancers, security groups, subnets, network services, compute metadata, and more). The new Smartscape® uses this information, along with cloud monitoring data, to provide a comprehensive, always-accurate topology of your cloud infrastructure. You can use the new Smartscape app to navigate your cloud topology, visualize dependencies, and eliminate hidden or forgotten resources. Ready-made views for AWS and Azure provide a comprehensive, automatically discovered cloud inventory across services, databases, networking layers, and security controls.

Additionally, you get ready-made dashboards, essential metrics, and expanded cross-cloud visibility, providing you with immediate clarity, especially when issues originate on the provider side, thanks to built-in AWS Health event integration.

All of this comes together in our newly enhanced Clouds app, a shared place for teams to analyze services, metrics, events, and logs. Pre-built dashboards and alerts automatically highlight unhealthy resources, helping teams stay ahead of issues, while the streamlined onboarding process eliminates the need for additional collectors or components. It’s fast, safe, and modern—exactly how cloud onboarding should feel. Ready to see it in action? Keep reading to see the magic.

Transform from reactive monitoring to proactive cloud operations

Dynatrace transformed cloud monitoring into proactive cloud operations by combining AI-powered observability with intelligent automation. This allows organizations to move beyond simply identifying problems to actively solving and preventing problems.

With Dynatrace, you can remediate issues before they impact your users, prevent future issues, and optimize your cloud environments to ensure they operate at maximum efficiency and resiliency.

Prevention

Leave reactive firefighting behind and gain the foresight needed to stay ahead of issues. Dynatrace’s AI-driven automation delivers proactive insights that allow you to identify and resolve potential problems before they impact your users. By predicting anomalies and triggering automated workflows, Dynatrace helps maintain high availability and optimal performance across your cloud environments. This proactive approach minimizes downtime, protects user experience, and ensures your teams can focus on strategic initiatives rather than crisis management.

Remediation

Instead of wasting valuable time on lengthy resolution cycles that disrupt business operations, accelerate recovery with intelligent automation. Dynatrace automates root cause analysis and remediation, enabling self-healing workflows that dramatically reduce resolution times. By eliminating manual troubleshooting and streamlining incident response, your teams can focus on driving innovation rather than firefighting. With AI-driven insights and automated corrective actions, Dynatrace ensures issues are resolved quickly and efficiently, thus minimizing impact, improving reliability, and keeping your business moving forward.

Optimization

Stop overspending on infrastructure due to a lack of visibility into resource usage and performance. With Dynatrace, you can continuously optimize both cost and efficiency across your environment. Real-time insights into resource consumption and application performance allow you to identify waste and prevent unnecessary expenses. By leveraging AI-driven analytics and automated recommendations, you can improve cost management and drive peak performance in your applications.

Ready to experience the new world of Cloud Operations for yourself?

With the introduction of enhanced cloud operations for AWS, Azure, and GCP, you can achieve smarter collaboration, faster issue resolution, and streamlined operations at scale using the Dynatrace Cloud Platform Operations solution.

AWS enhanced cloud operations

Discover how easy it is to get started using proactive monitoring capabilities for AWS. AWS cloud operations are now generally available for all Dynatrace SaaS customers.

Azure enhanced cloud operations

Interested in seeing the magic for your Azure environments?
Join the Azure Preview program

GCP enhanced cloud operations

Are you a GCP customer looking for a cloud operations solution?
Join the GCP Preview program

The post Redefining cloud operations: Dynatrace brings intelligence to observability appeared first on Dynatrace news.

Modern organizations face growing challenges in managing thousands of distributed databases across clouds, regions, and teams, often leading to blind spots and reactive firefighting. Dynatrace’s new Database Monitoring app changes the game by providing unified visibility and AI-powered insights across your entire database landscape. With proactive health scoring, query-level analytics, and seamless integration with application monitoring, teams can quickly identify and resolve issues before they impact users. This solution empowers developers, SREs, and platform engineers to collaborate effectively, reduce complexity, and take ownership of database performance with confidence.

Organizations today rely on thousands of databases spread across clouds, regions, and teams; traditional monitoring tools simply can’t keep up.

In the AI era, databases are increasingly ephemeral; workloads are massively data-intensive, and debugging efforts span across complex, distributed systems. Simply put, traditional tools were never designed for this pace or scale. Fragmented tooling and data silos add complexity, while usage-based costs limit observability, creating blind spots and slowing issue detection. Teams often end up firefighting problems, such as slow queries and deadlocks, leading to operational fatigue and delayed resolutions that impact performance and innovation.

At the same time, as database reliability shifts from DBAs to engineering teams, visibility gaps and expertise challenges grow. Developers often lack feedback on how their code impacts performance, which slows down releases, increases risk, and makes collaboration with SRE and platform teams more challenging. With many developers lacking in-depth database knowledge, it’s crucial to deliver tools that simplify management and provide actionable insights, allowing teams to innovate faster without compromising reliability.

It’s time to transform database observability with an AI-native approach designed specifically for developers, SREs, and platform engineers. Dynatrace’s new Database Monitoring solution is revolutionizing database observability with unified visibility across your entire database estate, from on-premises to hybrid and multicloud environments.

Unified observability across your entire database estate

The new Dynatrace Databases app, powered by the Dynatrace® unified observability platform, takes database monitoring to the next level with deep, actionable insights.

You can now monitor entire database clusters, gain deep AI-powered insights with remediation plans and alerts, and access granular visibility to reduce outages and downtime. Essentially, this means you can now go beyond basic health checks and gain visibility into:

• Query-level analytics and transaction tracing across services to pinpoint performance bottlenecks.
• Schema and index behavior analysis to understand structural inefficiencies.
• Preventive alerts and insights that help you act before issues impact users.
• Historical and real-time performance trends for smarter optimization and capacity planning.

With all critical data in one place, practitioners get a holistic view of their entire ecosystem. What used to take significant time, resources, and tools is now available in one central place.

The Databases application was designed to monitor a diverse range of database technologies across on-premises, public cloud, and hybrid cloud environments. With native support for cloud-specific services, Dynatrace delivers comprehensive coverage regardless of your infrastructure strategy.

From reactive to proactive database monitoring

Proactive database monitoring starts here. Instead of waiting for problems to surface and reacting to outages and slowdowns, teams can now prioritize the necessary adjustments to keep their databases healthy and performing optimally, and to ensure their applications run smoothly. This proactive approach drives performance improvements beyond query optimization, allowing you to address issues before they impact users.

With granular database views and new metrics, including replication status, cache hit ratios, lock contention, and server pulse overviews, practitioners gain the clarity needed to make informed decisions.

With real-time intelligence, Databases eliminates silos to help you optimize performance, reduce time to resolution, and deliver a seamless user experience. Combined with APM integration, Dynatrace delivers end-to-end visibility from services down to individual database queries, so you can understand how the layers interact.

How it works

After a seamless and quick integration, Databases immediately provides you with an overview of everything happening across all your databases.

You can dive deeper into the instances you’re responsible for. Go to the Overview tab and view the Health score, which indicates the instance’s health.

The health score is an innovative feature that allows you to be proactive with your database fleets and make sure they always meet your application needs. In this example, you can see how a low health score indicates a database health issue related to the instance’s Cache Hit Ratio.

Once you have a clear indication of what’s preventing a database from maximizing its potential, you can dive deeper into that specific database and the database calls reported as the root cause of the problem, all from the health score.

In the above graph, we can see that the problem is within the airbases. Now that we know which database is causing the problem, we can access it and debug the queries that are contributing to the low database Cache Hit Ratio.

Seamless debugging across databases and services

Experience the full power of Dynatrace’s unified platform by taking your database monitoring a step further. Monitoring your databases and services together in Dynatrace gives you a holistic view of your application ecosystem. This integration allows you to quickly get to the root cause, identify the issues, and transition effortlessly from the Database app to the Services app for deeper analysis, quick and efficient debugging, and resolution.

Let’s take a look at an example. Let’s say one of your databases experiences a Cache Hit Ratio problem, as depicted in the screenshot below.

From the database host overview page, go to the Calling Services tab. Here, you can pinpoint which service is causing, or is impacted by, the issue based on certain metrics:

Once you identify the problematic service in the Databases app, go to the Services app. There, you can debug the root cause by analyzing the problematic queries in detail.

Get started

By breaking down silos and delivering intuitive, actionable insights, the new Dynatrace Database Monitoring solution helps teams collaborate seamlessly, reduce complexity, and take ownership of database performance with confidence. From unified observability and AI-powered analytics to proactive health scoring and end-to-end debugging across databases and services, Dynatrace transforms how you manage and optimize your database landscape.

The post Database monitoring made easy with Dynatrace’s AI-powered solution appeared first on Dynatrace news.

When onboarding network devices for observability, challenges often arise related to inconsistent or partial monitoring coverage or inefficient processes.

Such challenges make it difficult to ensure that all devices are properly and uniformly monitored and can provide actionable insights. Managing network devices at scale exacerbates the problem, as organizations contend with thousands of devices from a diverse range of vendors. This can have an adverse impact on your ability to maintain and troubleshoot your networks.

Network monitoring tools often lack integration with the rest of the infrastructure, making it even more challenging to analyze network monitoring data in context.

To achieve consistent, end-to-end monitoring, you need a tool that allows deterministic network observability and automatically contextualizes all ingested data. Let’s take a look at how Dynatrace does this.

Simplified and accelerated network monitoring

When onboarding network devices to an observability platform, it’s not uncommon to spend a disproportionate amount of time configuring network observability. Despite spending valuable time in the process, the uncertainty that some devices might be overlooked remains. Furthermore, in today’s dynamic environments, devices can be added or removed at a moment’s notice and at a rapid pace. This creates a burden for the operations team to constantly prove that the level of observability is at the right level.

To gain a comprehensive overview of the state of observability across all your environments, Dynatrace has expanded the Discovery & Coverage application to include network device monitoring capabilities. This ensures that there are no blind spots in this domain and that no network device is left unmonitored.

The Discovery & Coverage app achieves that by scanning predefined IP ranges or subnets. Based on the outcome of the discovery process, the journey continues by offering the possibility to automatically onboard the right device extension and create Network Availability monitors. Statistics are provided for both extension and availability coverage, providing tangible data to measure the completion of the observability enablement process.

Manage network devices at scale across distributed environments

SNMP (Simple Network Management Protocol) provides a standardized framework for monitoring and managing devices on IP networks. Its simplicity, scalability, and compatibility with a wide range of hardware make it an ideal choice for network management across diverse environments.

However, managing and monitoring SNMP across devices from multiple vendors in large, distributed, or even siloed networks can become cumbersome. Additional complexity is introduced when various teams own and manage their load-balancing devices or application firewalls and core switches individually.

Historically, IP Address Management (IPAM) tools have been effective at mapping entire IP networks, but they struggle to leverage the observability potential of discovered endpoints. Health information on SNMP devices is often isolated, and discovered devices are not placed in the correct context or topology, thereby failing to fulfill the goal of the discovery process: associating SNMP device data with the IT environments where the devices reside. This is where Dynatrace excels.

Leverage the power of the Dynatrace platform for your SNMP devices

Driving tool consolidation and integrating auto discovery and monitoring into your observability solution reduces costs and boosts operational excellence. Additionally, using the Discovery & Coverage app for auto discovery of networking devices means you’ll spend less time manually tracking devices and reduce the chance of lacking the right extension or using the wrong extension for a device.

The Dynatrace end-to-end observability approach makes your discovered network devices available in Dynatrace Grail® and the Dynatrace platform, allowing you to build innovative functionality while simultaneously reducing tool sprawl.

Your discovered devices appear in the Infrastructure and Operations app as network devices, with essential properties automatically populated. Dynatrace and vendor-provided extensions offered in Dynatrace Hub can enhance the observability level and insights of your individual devices. Further, you’re automatically notified when predefined thresholds are exceeded or when anomalies are detected.

Your network devices will function as part of an integrated network, not as standalone entities. For Dynatrace SaaS customers, network devices are readily available in Grail and can be queried using Dynatrace Query Language (DQL) to create value-added insights in the Davis Anomaly Detection app or to create automations and workflows, such as auto-generated tickets for external systems or notifications sent to teams via Slack or PagerDuty.

Get started with network device autodiscovery in Dynatrace

The SNMP autodiscovery capability is provided by the Discovery & Coverage app. Open the app, navigate to the Network coverage tab, and select Configure scanning.

Once a configuration is activated, the discovery process begins.

The SNMP Autodiscovery extension regularly scans your IPv4 and IPv6 address lists, ranges, or subnets for devices with SNMP agents. If devices with matching SNMP parameters are present, they will be added to the environment.

Coverage reports for each device configuration provide an overview of the level of observability for each discovered device, answering questions such as: Is each device polled with the correct extension? Or, is the Network Availability Monitor installed on the management interface?

The Discovery & Coverage app allows you to add a device type-matching extension in bulk. The Poll icon opens the following windows, enabling the specific extensions with one select.

Additionally, you can centrally configure Network Availability Monitors (NAM) to continuously probe the health and availability of your devices. This ranges from simple ICMP ping tests to advanced probes, depending on your requirements and setup.

Take the first step to simplifying device onboarding

SNMP network device autodiscovery is a powerful tool for network administrators. It simplifies network management, improves efficiency, and allows for easy scalability. By leveraging this feature, organizations today ensure their networks are always accurately represented and observed.

Remember, a well-managed network with thorough observability and health monitors is the backbone of any successful organization. So, embrace the power of SNMP autodiscovery and take your network management to the next level!

If you have already deployed network observability using the extension apps, you need to download and open the Discovery & Coverage app. By configuring autodiscovery, you’ll ensure that no part of your network remains unattended and that you’ve configured the right level of observability in your environment. From now on, the Dynatrace network device onboarding process is greatly simplified and accelerated.

If you’re not yet a Dynatrace customer, consider starting a free trial, opening the Discovery & Coverage app, and navigating to the Network coverage tab. You can then immediately discover SNMP devices in one of your environment’s IP networks and add the right level of observability to the devices.

The post Accelerate SNMP network device observability with Dynatrace Discovery & Coverage appeared first on Dynatrace news.

With the wave of cloud-native transformation that’s been sweeping across the software industry in the past few years, Kubernetes has emerged as the backbone of modern application deployment and management.

However, as systems have evolved, traditional approaches to monitoring have struggled to keep up. To fill this gap, technologists have designed new tools and practices especially for modern, cloud-native environments. However, all this tooling and new workflows come with their own unique challenges.

Organizations now find themselves not only navigating the inherent complexities that come with the distributed nature of Kubernetes, but they’re doing it with a lack of unified data across their entire stack, especially when working in multi-cloud environments. Limited visibility into applications, a lack of full context, and data silos from multiple tools hinder their ability to get a comprehensive view of their systems and applications.

This is where the need for a unified platform becomes crucial, one that provides engineers with a full end-to-end view of their containerized applications, ensuring optimal performance, reliability, and proactive issue detection and resolution. Advanced monitoring capabilities, such as Dynatrace Kubernetes monitoring, are critical in achieving this performance.

The one-stop-shop for all Kubernetes observability needs

Dynatrace provides unparalleled end-to-end visibility across your entire Kubernetes stack. Gone are the days of gaps in visibility, lack of contextualized data, data silos, long resolution times, and inadequate context and alerts.

With Dynatrace Kubernetes monitoring, engineers gain unified observability across all their environments, the ability to drill down to pinpoint an issue, AI-driven insights, real-time data, and more.

We haven’t even discussed the best part yet, though. All of this is done end-to-end by utilizing the full power of the entire Dynatrace platform.

Dynatrace Kubernetes monitoring: End-to-end observability of your Kubernetes stack

End-to-end monitoring means having full visibility into every aspect of applications, from code and services to performance metrics. This awareness allows teams to quickly identify and resolve application issues, optimize performance, automate processes, and ensure a smooth user experience.

Dynatrace provides these capabilities in multiple ways.

Platform visibility

The Kubernetes application easily provides a comprehensive view of your entire Kubernetes inventory and the ability to drill down into individual clusters to eliminate blind spots. In a single view, engineers can easily see out-of-the-box health signals and resource indicators (including alerts), and easily explain warning signals, so they have real-time insights into the entire Kubernetes estate for easy and quick issue resolution.

Integrated observability

Dynatrace unifies telemetry data from all sources, including third-party data, providing a consolidated view of traces, metrics, and logs on a single platform. This integrated approach extends and adds value to the OpenTelemetry framework. With integrated observability, users gain deeper insights into application behavior and readily identify performance bottlenecks. Teams can monitor the golden signals—latency, traffic, errors, and saturation—to better understand the health and performance of applications in real-time. This allows teams to quickly pinpoint issues, leverage predictive AI-powered analysis, and ultimately ensure applications are running smoothly and efficiently across their entire Kubernetes stack.

AI-powered insights

The engine behind Dynatrace Kubernetes monitoring is Davis® AI, which is built into the Dynatrace platform. Davis redefines ‘modern monitoring’ by taking the guesswork out of troubleshooting. It detects anomalies and potential issues in real-time, providing proactive alerts before they become critical. Davis AI goes beyond alerting by performing data deep dives to pinpoint the exact cause of issues. This comprehensive analysis bubbles up the most important warning signals teams need to be aware of and provides clear, actionable insights to help users understand and resolve issues efficiently.

With the integration of Davis CoPilot™, teams can go a step further and navigate complex Kubernetes environments with confidence. CoPilot acts as a contextual guide to help teams of all levels understand Kubernetes-native concepts by explaining them in plain language and offering deeper insights into root cause and remediation options.

Log Management

Logs are critical sources of insight into Kubernetes environments. With Dynatrace, logs are centralized, easily accessible, and connected with other signals from your Kubernetes environments to allow speedy troubleshooting and effective monitoring. For instance, you can inspect and understand logs from crashing application containers and other workloads using the Dynatrace Kubernetes app. With Notebooks and DQL, you can analyze log data alongside traces and Kubernetes topology. For security issues and data forensics, Dynatrace supports evidence-based investigations. Metrics and events can be derived from logs for dashboarding and prediction, automating remediations with log data in the Workflows app, and manually exploring surrounding logs and patterns using Dynatrace Logs.

Observability for Developers

The widespread adoption of Kubernetes has made it easier and faster for organizations to deploy and manage software. However, this also means that developers are now facing more difficulties troubleshooting and understanding their code’s behavior. Dynatrace provides developers with real-time data and capabilities to overcome the highly distributed nature of Kubernetes workloads.

In addition to cloud-native apps such as distributed tracing, error analysis, and log analytics, the Live Debugger provides developers with real-time snapshots from their running code without the need to reproduce, add code, or redeploy. This helps them optimize their code and debug issues faster.

Additionally, application profiling with CPU, memory, and thread profilers help developers pinpoint processes and containers that consume CPU, identify memory leaks or usage patterns in order to solve issues and optimize their performance.

Users can also quickly understand why service requests are failing and identify root causes of increased failure rates with error and failure analysis.

Customization, automation, and ease-of-use

Managing Kubernetes workloads and clusters traditionally requires a lot of manual work that is often repetitive and time-consuming. Doing so at scale requires efficient resource management and automation to handle dynamic demands. Dynatrace’s automated workflows simplify this by predicting resource needs and scaling workloads accordingly. This allows you to manage your environments without constant oversight.

Workflow automation in Dynatrace allows for custom scaling events, based on Davis AI forecasting, enabling automated, predictive resource scaling for Kubernetes. This lets you manage your environments without the need for constant oversight, ensuring proactive issue detection and resolution.

Support for GitOps with automated observability, automatic anomaly remediation, and performance optimization are just a few ways this can be achieved.

With Dynatrace automation capabilities, monitoring your Kubernetes clusters becomes a seamless experience.

Dynatrace Kubernetes monitoring for seamless automation

In the dynamic world of cloud-native and Kubernetes, having integrated observability, AI-driven analysis, and automation is crucial for success—and Dynatrace is the answer. Let Dynatrace manage the dynamic intricacies of Kubernetes so your teams have the intelligence they need to automate and optimize.

Utilize the full power of the Dynatrace platform to gain unparalleled observability of your entire Kubernetes stack, ensure optimal performance and reliability, and proactively detect issues and automate resolution.

The post How Dynatrace Kubernetes Monitoring powers smarter insights appeared first on Dynatrace news.

SAP systems are used by many of the world’s largest enterprises, powering everything from finance to supply chain operations. However, monitoring SAP systems can be extremely challenging. As the SAP technology stack continues to evolve, it brings powerful innovations but also increased complexity due to the use of hybrid system architectures, massive amounts of data, and increasing adoption of cloud technologies. The IT teams that adopt SAP S/4HANA and benefit from RISE to achieve business efficiency also strive to maintain performance and reliability.

This growing complexity makes an end-to-end observability solution essential. With the PowerConnect application, Dynatrace makes it simple and quick to unlock deep visibility into SAP performance, on every level and for every requirement that modern, cloud native teams need to optimize. By seamlessly capturing metrics, logs, traces, and business events in one unified platform, teams are able to surface actionable insights and pinpoint issues in just minutes.

Seamlessly monitor SAP systems with Dynatrace

The latest version of the Dynatrace PowerConnect app for SAP Monitoring gives you a streamlined, intuitive experience that’s designed to make SAP observability faster to provision and easier to use. It was purpose-built to harness the full power of the Dynatrace® platform by bringing together real-time data ingestion, built-in data security, AI-powered analytics, and automation in a single, unified platform. With simplified deployment and configuration, you can activate SAP monitoring in just a few clicks.

PowerConnect-instrumented SAP systems feed observability signals straight into the Dynatrace platform. The PowerConnect app on the Dynatrace platform takes care of all necessary provisioning and settings, so the SAP metrics, logs, traces, and business events land securely in Grail™, the Dynatrace data lakehouse, and are available for Dynatrace Davis® AI analysis and reporting with powerful dashboards and trace-level analysis. Dynatrace automatically discovers the topology model of your SAP transactions, giving you a comprehensive and clear view of the relationships and dependencies between the different databases, systems, servers, applications, and interfaces you use.

IT landscape observability for SAP and interconnected systems

You no longer need to use multiple disconnected tools, perform manual instrumentation, or fly blind. You can now quickly, easily, and efficiently get all the data and insights you need into your IT landscape, including deep insights into SAP transactions, processes, jobs, iDocs, interfaces, cloud systems, and more. This is on top of the core Dynatrace platform capabilities for observing all your apps, clouds, networks, and infrastructure that your SAP runs on, depends on, and interacts with.

This is achieved by leveraging standard capabilities of the Dynatrace platform to observe SAP.

Accelerated root cause analysis

Dynatrace accelerates root cause analysis and proactive issue resolution in SAP environments. By combining real-time data with the Dynatrace Davis® AI engine, you can automatically detect anomalies, easily view core vitals with out-of-the-box metrics, trace issues down to individual transactions, and understand the business impact of performance issues. This reduces mean time to resolution and helps prevent problems before they affect users or business operations.

Precise troubleshooting

Dynatrace offers precise troubleshooting of SAP operations by tracing individual SAP transactions inside the complex SAP systems down to the database level. This allows you to pinpoint performance bottlenecks, understand dependencies, and resolve issues faster. This capability leverages native trace analytics available on the Dynatrace® platform for OpenTelemetry traces, placing SAP transaction tracing on equal footing with all other OTel-enabled applications.

Ready-made dashboards

Purpose-built, ready-made dashboards are available for all common SAP observability use cases and practices. A library of 200+ SAP-focused dashboards with KPIs familiar to every SAP practitioner gets you started in minutes. Expand them on the spot, tailor them to your and your team’s needs and preferences with granular access control, and combine them with the non-SAP IT landscape observability signals to arrive at efficient business analytics and performance objectives tracking views. All Dynatrace dashboards show real-time metrics and display historical data for as far back as you choose to retain the PowerConnect data on the Dynatrace platform.

Dynatrace business events analytics and business process modeling

Dynatrace business events analytics, business-process modeling, and business-process monitoring work with SAP-sourced signals in the same way as with any other business events. PowerConnect feeds the Dynatrace business event ingest endpoint in real time, with information on business-relevant metrics and related SAP systems performance. This allows faster, data-driven business decisions and helps you and your team track key performance indicators—both technical and business—continuously, including any business-specific signals you configured on the PowerConnect agent side with custom SAP data extractors.

RISE with SAP, with confidence

For any organization transitioning to SAP RISE, the need to maintain optimal observability before, during, and after the move is critical. With Dynatrace and PowerConnect, it’s not only straightforward, it’s simple. You get full visibility into your SAP landscape in the cloud and on-premises, on SAP S/4HANA, and on ECC.

PowerConnect is certified on all commonly used S/4HANA and ECC platforms. All PowerConnect observability signals land on the same, single Dynatrace platform, so you benefit from continuous, AI-powered insights into your SAP systems that ensure a smooth transition and minimal risk throughout your modernization journey.

Start monitoring your SAP systems today

To get started, turn on PowerConnect on all your SAP systems and follow the instructions in the PowerConnect documentation.

• As PowerConnect is certified to deploy on SAP systems, the procedure is similar to that of other SAP platform extensions.
• This results in PowerConnect metrics, logs, traces, and business events data being sent to Dynatrace.

Then, go to the Dynatrace Hub and request PowerConnect for SAP on Dynatrace app from Rhondos. You’ll be provided with the ZIP artifact download.

• Add the PowerConnect app to your tenant using the in-product Hub app (on your tenant: Hub > Manage > Upload app).
• Once the app is installed, open it and follow the instructions. The app will set up the Dynatrace platform to make the best out of PowerConnect signals.

This results in setting up Dynatrace OpenPipeline for PowerConnect data ingest, provisioning Grail buckets for security and performance, and deploying ready-to-use PowerConnect dashboards.

That‘s it. Now you can explore how your SAP systems perform by:

• Using the Dashboards app to get an overview or track specific SAP KPIs for all vital SAP components, already set up for you
• Using the Distributed Tracing app to analyze traces of the SAP transactions
• Using the Business Flow app to model SAP-run processes and analyze business events forwarded by PowerConnect to Dynatrace

Getting started with PowerConnect for SAP monitoring in Dynatrace is crucial to transforming your SAP performance management. In minutes, you can unlock powerful, use case-driven dashboards and gain deep insights into SAP systems.

PowerConnect by Rhondos seamlessly delivers SAP system data, while Dynatrace turns that data into actionable answers about performance, availability, usage, and business process health. Together, they’re the ultimate solution for SAP observability. So stop waiting. Start your journey today by visiting the Dynatrace Hub.

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The post Simplify SAP Monitoring with PowerConnect and Dynatrace appeared first on Dynatrace news.

The Dynatrace Log Module for Kubernetes is a fully automated, full-service approach to Kubernetes log management and analytics. Dynatrace is your one-stop shop and go-to solution for all Kubernetes needs.

Logging is integral to Kubernetes monitoring

In the ever-evolving software development landscape, logs have always been—and continue to be—one of the most critical sources of insight. Log data is essential, whether you’re troubleshooting and conducting forensics into past problems, investigating potential security issues, or debugging in real time.

However, the distributed and ephemeral nature of Kubernetes means that logs are scattered across multiple nodes and pods, making it difficult to ensure that all logs are preserved, easy to access, and enriched with necessary context for future analytics.

A robust log collection solution must ensure:

• Central log management. Logs must be centralized, preserved, easily accessible, and connected with other signals from your Kubernetes environments to allow effective monitoring and troubleshooting.
• Context-aware and topology-rich logs. Logs must be enriched with metadata and contextual information, allowing powerful log analytics of all distributed traces, metrics, and events within the Kubernetes topology. This allows analysis of logs from out-of-memory containers or pods with application errors.
• Powerful access controls. The ability to define fine-grained access control for logs based on Kubernetes namespace or cluster level is essential. This ensures that users can only access the necessary logs, helping maintain the highest security, compliance, and operational efficiency.

At Dynatrace, we support whichever integration you use to collect logs from your systems, whether it’s OpenTelemetry, Fluent Bit, or other tools. Moreover, we’re continuously looking to improve our customers’ experience, which is why we’ve enhanced our fully automated, full-service log streaming solution with the Dynatrace Log module.

The updated solution allows you to:

• Stream and analyze logs from your Kubernetes environments without running OneAgent on each Kubernetes node.
• Flexibly choose the level of observability you need. For example, you can start small with only Kubernetes platform monitoring and log analytics and grow into comprehensive observability maturity with distributed tracing, security analytics, real-user monitoring, and more. This flexibility extends to privileges, ensuring you can grant the least possible number of privileges in Kubernetes to get the needed data.
• Get insights into logs from short-lived containers and pods such as InitContainers or Jobs.
• Easily onboard log analytics within the Kubernetes app and control log ingestion and management centrally to ensure an optimal experience. Rather than configuring log collection locally, as you might have done with open source log shippers you’ve used, you can now centrally define and manage which logs Dynatrace collects.
• Effortlessly get logs in context as the Dynatrace Log Module for Kubernetes is fully managed for you; Dynatrace handles all upkeep, configuration, and lifecycle management.

Let’s look at how the new capabilities integrate with the Dynatrace platform.

One platform, complete log value

Not having to lift a finger to stream your logs is awesome, but that’s not the only value the Dynatrace Log Module provides.

Central log management

You have the ability to fully manage the lifecycle and configuration of your Kubernetes log collection within the Dynatrace platform. Gone are the days when you needed to manage the configuration of a log shipper across all your clusters. Dynatrace allows you to do this on one platform. You can centrally manage and control data collection, data masking, data dropping, data transformation, and data retention vs distributed configurations at the source. Additionally, the ability to dynamically define retention periods and compliance settings gives you much more flexibility when working and allows you to get the data you need to resolve issues easily. This ensures the smooth and reliable operation of applications running on Kubernetes.

Troubleshooting and remediation

Logs are critical to understanding and maintaining system health and performance. Dynatrace helps you quickly troubleshoot and easily remediate in a variety of ways, allowing you to:

• Inspect and understand logs from crashing application containers and other workloads in the Dynatrace Kubernetes app.
• Slice and dice log data with traces and Kubernetes topology in Notebooks with DQL.
• Drive evidence-based investigations for security issues and data forensics.
• Easily derive metrics and events from logs for dashboarding and prediction.

• Automate remediations with log data in the Workflows app.
• Dive into log data to explore surrounding logs and patterns using the Dynatrace Logs app.

Cost management and allocation

Dynatrace allows you to manage costs by controlling the amount of ingested logs, the retention period for which logs are kept for analysis, and query timeframes for your analytics. You can also manage ingest and retention by filtering log sources, managing buckets, and picking the right license model for your needs.

Additionally, you can leverage existing labels or annotations to enrich log data with cost-allocation metadata, making it easier to allocate expenses accurately. This allows for precise cross-charging, helping ensure that bills are charged to the correct departments.

Log enrichment

Dynatrace enriches every log line with additional Kubernetes metadata. In addition to cost-allocation use cases, you can enrich logs with security context and other common Kubernetes context metadata.

This allows you to define IAM rules to control access to log data so that only users with specific roles or permissions can query certain logs. This ensures that teams see only the logs they need, helping your organization maintain the highest levels of privacy and security. Further, if you also monitor your applications with Dynatrace, your log lines will be enriched with span and trace IDs for context-rich analytics of log, trace, and metrics data.

Get started

Seamlessly manage your logs with the new Dynatrace Log Module. Get started today to see how Dynatrace can help you with your observability and security needs.

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

The post Kubernetes logging made easy: Comprehensive Kubernetes observability with Dynatrace appeared first on Dynatrace news.

Managing Kubernetes environments can be challenging due to their distributed and ephemeral nature. This makes it difficult to easily find the information you need to ensure your environments are stable, efficient, and scalable. A common tool to stay on top of this challenge is dashboards, as they allow you to display the most important signals in one place and allow for easy customization. Especially in the open-source community, dashboards are the go-to tool for monitoring and optimizing Kubernetes environments.

When troubleshooting, having all your data in one place, especially in one view, is critical. While dashboards provide an easy means to see all signals in one place, setting up and scaling data management is a huge challenge for many teams relying on open-source monitoring solutions. Most of the time, teams end up with dashboards that show signals only from a small subset of their overall Kubernetes environment.

That’s why we built our ready-made dashboards utilizing the context-rich data provided by Dynatrace Grail™, the only causational data lakehouse with massively parallel processing. With Grail, you truly get all your data in one place while still being able to easily customize it to your preferences.

New Dynatrace dashboards for Kubernetes give platform engineers a more intuitive and optimized experience with the look and feel they already know and love.

Seamless Dynatrace experience

Easy dashboard customization is key, giving you a seamless Dynatrace experience and allowing you to harness the full power of the Dynatrace platform. With Dashboards, you can see both the Kubernetes data you want and the observability data you need within the Dynatrace platform. As all data is connected within the Dynatrace platform, you can seamlessly jump from viewing namespaces in a dashboard to their respective details within the Kubernetes app and vice versa. This allows for highly efficient navigation throughout Dynatrace, ultimately allowing you to find the information you’re looking for much faster than in any other tool. Of course, this applies to Kubernetes and any data residing in Dynatrace. The opportunities are limitless. Put Kubernetes and tracing data together with log and event data. Choose only the data and capabilities you and your team need. Design your dashboards with the exact data you need to ensure you’re working optimally from a single view.

How it works

The Kubernetes ready-made dashboards show you the most crucial information from your Kubernetes environment. From there, it’s easy to customize them to your personal preferences. Start with one of the platform’s base dashboards and customize it to your needs. With just a few clicks, you can add platform app data directly to your dashboards. For example, quickly add related logs of workloads to your dashboard directly from the Kubernetes app, as shown below.

Rather than starting with a blank page, you can easily add or remove what you need or don’t need for any scenario. Today, we provide you with the five most used dashboards for Kubernetes observability:

• Kubernetes Cluster: Get broad visibility into the scale, status, and resource usage of your Kubernetes clusters.

• Kubernetes Nodes – Pods: Understand pod resource consumption on your Kubernetes nodes.
• Kubernetes Namespace – Workloads: Explore the resource utilization distribution across workloads in your namespace.
• Kubernetes Namespace – Pods: Analyze resource allocation of all pods within a namespace.
• Kubernetes Persistent Volumes: Inspect the utilization and size of your persistent volume claims.

Get started

There’s no time like the present to get all your data quickly and easily on one dashboard. Check out the ready-made dashboards in the new Kubernetes platform monitoring solution in the Dynatrace Playground today.

The post Level up your Kubernetes experience with new Dynatrace dashboards appeared first on Dynatrace news.

As we did with IBM Power, we’re delighted to share that IBM and Dynatrace have joined forces to bring the Dynatrace Operator, along with the comprehensive capabilities of the Dynatrace platform, to Red Hat OpenShift on the IBM Z and LinuxONE architecture (s390x). IBM Z and LinuxONE mainframes running the Linux operating system enable you to respond faster to business demands, protect data from core to cloud, and streamline insights and automation. By leveraging Dynatrace observability on Red Hat OpenShift running on Linux, you can accelerate modernization to hybrid cloud and increase operational efficiencies with greater visibility across the full stack from hardware through application processes.

Dynatrace full stack observability for Red Hat OpenShift

Dynatrace enhances software quality and operational efficiency, which drives innovation by unifying application, operation, and platform engineering teams on a single platform. Dynatrace with Red Hat OpenShift monitoring stands out for the following reasons:

1. With infrastructure health monitoring and optimization, you can assess the status of your infrastructure at a glance to understand resource consumption and thus optimize resource allocation for cost efficiency.
2. Full stack observability gives you comprehensive observability across your entire stack, including Kubernetes clusters, logs, and more. Telemetry data, such as traces and metrics, allow you to analyze the end-to-end performance of your deployed applications. You also benefit from enhanced monitoring capabilities with seamless Dynatrace integrations with cloud-native technologies and services like Istio and Prometheus.
3. Dynatrace Smartscape® technology provides all data in context to simplify analytics and problem detection by semantically mapping metrics, traces, logs, and real user data to specific Kubernetes objects, including containers, pods, nodes, and services.
4. You can automatically detect and analyze performance issues across your entire tech stack with Davis® AI. This lets you quickly troubleshoot issues by identifying problematic components or configurations and providing insights into the root cause.
5. Dynatrace is designed to scale easily across the entire Kubernetes stack. Its support of GitOps practices allows for handling large-scale deployments with thousands of nodes and containers, making it the best option for enterprise-grade Red Hat OpenShift monitoring.

The new Dynatrace Kubernetes experience also marks a groundbreaking advancement for platform engineering teams by enabling you to pull critical observability and security information into a centralized Kubernetes management console. In particular, it allows you to explore cluster health, resource utilization, security, and the performance of applications built and deployed on a Kubernetes-centric platform. This is significant when coupled with the  OpenShift platform.

Dynatrace Operator for OneAgent, API monitoring, routing, and more

Dynatrace Operator leverages Kubernetes’ native capabilities to automate the rollout, configuration, and lifecycle management of Dynatrace components within Kubernetes environments. It simplifies setting up and maintaining Dynatrace observability by encapsulating the necessary configuration and operational logic into a single entity.

Dynatrace Operator acts as an intelligent controller that understands the desired state of your Dynatrace monitoring environment and takes actions to achieve it. It automates tasks such as provisioning and scaling Dynatrace monitoring components, updating configurations, and ensuring the health and availability of your monitoring infrastructure.

Dynatrace Operator consumes DynaKubes with cloud-native full-stack configuration and deploys the following resources:

• Dynatrace OneAgent, deployed as a DaemonSet, collects host metrics from Kubernetes nodes.
• Dynatrace code modules, enabled via Dynatrace webhook, provide distributed tracing and code-level visibility for applications deployed on Kubernetes.
• Dynatrace ActiveGate is used for routing and monitoring Kubernetes objects by collecting data (metrics, events, status) from the Kubernetes API.

With this approach:

• Red Hat OpenShift infrastructure (control plane and worker nodes) and workloads are instrumented automatically without manual code change.
• The scope of automatic workload instrumentation is user-configurable, for example, by namespace.
• Lifecycle management of Dynatrace components (for example, ActiveGate and OneAgent) is automatic and secure.

Get started monitoring Red Hat OpenShift on IBM Z and LinuxONE

• New to Dynatrace? Sign up for a fully functional Dynatrace free trial.
• Learn more about the new Kubernetes Experience for Platform Engineering.
• Dynatrace observability is available for Red Hat OpenShift on IBM Power.

The post Dynatrace observability now available for Red Hat OpenShift on IBM Z and LinuxONE mainframes appeared first on Dynatrace news.

With the move towards cloud-native computing, having a clear understanding of your Kubernetes platform’s performance and application behavior is a requirement. Having the ability to troubleshoot quickly and easily is especially important. Logging provides platform and application owners with an effective way to understand the state of their workloads by giving them a view into the inner workings of their systems. Log collection solutions, such as the Dynatrace Kubernetes Log Module or Fluent Bit, give organizations a much-needed solution for quickly gathering and processing log data to make it available in different backends for further analytics. This is especially necessary within complex cloud-native—and, more specifically, Kubernetes—environments.

Fluent Bit, an open source tool within the CNCF ecosystem, is a popular choice when choosing which log collection tool to use. At Dynatrace, we’re happy to make your life easier by providing a ready-to-use integration with Fluent Bit. The integration ensures all logs are enriched properly to enable context-rich troubleshooting and allows you to connect the streamed logs with distributed traces and the Kubernetes domain model.

Speed up your troubleshooting processes

Log analysis is typically the first step in the troubleshooting process. Therefore, it’s critical that when an issue arises, you have the right data and tools to quickly and easily understand the full scope of what’s happening within your applications.

Dynatrace integration with Fluent Bit allows platform and development teams to examine Kubernetes logs in the context of their workloads and pods. For containers, they get the full context of individual traces throughout the hybrid microservices application stack.

When your microservices have an issue, you can look into error logs within the Kubernetes app at the respective namespace or workload and search for erroneous log lines.

When using Dynatrace OneAgent® for automated distributed tracing of all your Kubernetes workloads, the logs are automatically enriched with tracing metadata. You get the complete picture of the logs of each workload or namespace.

From there, you can drill down to the distributed traces and inspect the spans of the full trace down to the code level that caused the suspicious log line in Kubernetes.

Get started with a simple installation

In addition to an easier troubleshooting process, you benefit from less friction when onboarding.

Dynatrace is tech agnostic, having been purpose-built with cloud-native architectures in mind. This gives you more freedom and flexibility in your workspaces, allowing you to work with whatever tools you already have. Specifically, the release of the Fluent Bit integration gives you two options to get started:

• The in-product onboarding experience lets you quickly roll out a ready-to-use and preconfigured Fluent Bit installation as a DaemonSet. This is the most convenient way to get started. Dynatrace ensures that all logs are properly enriched with metadata to enable context-rich analytics on the platform. You can restrict streaming logs to certain namespaces or pods during the in-product onboarding or customize the created Fluent Bit filters in the YAML file of the used helm chart.
• You can also integrate the required Dynatrace configuration into your existing Fluent Bit installations by adding the required sections. The Dynatrace-specific configurations can be found in the preconfigured YAML file and added to existing and customized Fluent Bit.

Get started on your improved log streaming journey

Troubleshooting is only the beginning of what you can do with a proper log streaming solution. Whether it’s seamlessly using logs for health checks to understand why pods are failing, faster innovation, using log data to understand the issue and context of problems detected by Davis® AI in your Kubernetes setup, or investigating security incidents, the options are endless.

Ready to experience the Fluent Bit integration for yourself?

Get started on your log streaming journey and see how the Fluent Bit integration with Dynatrace simplifies your troubleshooting process.

If you’re looking for a full-service, fully automated approach to monitoring Kubernetes, check out our Kubernetes Log Module to seamlessly manage your logs.

The post Full Kubernetes logging in context: Easily stream logs from Fluent Bit to Dynatrace appeared first on Dynatrace news.

As with all new tech, implementation and understanding don’t occur overnight. The adoption process takes time and consideration. While more investments are being directed towards Kubernetes-native or cloud-native methods, the challenges in using Kubernetes remain. Its complex, distributed nature makes it difficult to use and understand.

Monitoring cluster health is critical for ensuring that applications operate efficiently and reliably. However, the complexity and numerous moving parts of Kubernetes multicloud clusters mean that platform engineers often struggle when monitoring cluster health. This creates a lack of insight into Kubernetes platform health and the potential issues that can arise.

Gain comprehensive observability of your Kubernetes clusters

As organizations continue to adopt Kubernetes-centric infrastructure, it’s increasingly crucial that platform engineers have the right tools and capabilities to properly manage and track their Kubernetes clusters end-to-end.

The new Dynatrace Kubernetes experience provides a 10,000-foot view of all Kubernetes clusters across all environments and distributions from GCP, Azure, and AWS to OpenShift or on-premises solutions. With the Kubernetes experience, platform engineers can look across and drill down to quickly identify problem nodes, issues, and the underlying root causes for faster mean time to resolution (MTTR).

For any organization, maintaining a fast MTTR and customer happiness is critical. The enhanced web UI and out-of-the-box health signals give engineers the ability to easily understand which clusters are experiencing issues and negatively impacting customer experience. Additionally, the auto-baselining of performance and automated alerts allow engineers to understand issues within any of their clusters before they become serious or result in outages.

All the data a platform engineer needs to understand what’s going on can easily be seen in one place. This is a revolutionary improvement for platform engineers and R&D teams in general. What used to take a lot of valuable time, resources, and tools is now available in one central place.

When working with Kubernetes, it’s imperative to carefully keep track of what is going on in your clusters to ensure optimal health and efficiency. For instance, pods of misconfigured workloads can render the nodes they are running on unhealthy. Such critical situations are signaled by warning events and unhealthy node conditions. Engineers get a detailed view of a single cluster status, providing insight into the relevant Kubernetes health signals of container resources like nodes, namespaces, and workloads.

The new Dynatrace Kubernetes experience allows engineers to easily drill down to their unhealthy workloads, investigate ongoing issues, and gather all information required to fix problems quickly. If an unhealthy workload is owned by another team, having access to the provided ownership information enables engineers to promptly notify the correct team, ensuring a faster, more efficient resolution process.

Optimize resource utilization across workloads

In addition to the complexity that makes assessing the ongoing state of cluster health challenging, engineers face the issue of runaway cloud costs due to inefficient resource utilization. Platform engineers size their Kubernetes clusters based on the workload’s resource requests. As these engineers often manage a large fleet of clusters, node-scalers are frequently used to automate the task of dynamic optimization. However, if workload owners underutilize the requested resources, the platform wastes an incredible amount of unused resources, leading to an unnecessarily high carbon footprint and soaring cloud costs.

The ability to switch to the resource perspective helps engineers to easily assess the current state of resource efficiency of their Kubernetes environments. This allows for a fast drill-down to determine the workload contributing most to the situation, whether it’s CPU or memory waste. By using the available ownership information, teams can quickly and immediately begin to collaborate on optimizing these workloads.

Onboarding is faster than brewing a cup of coffee

Onboard a new Kubernetes cluster in three minutes. Yes, it only takes three minutes to activate Dynatrace Kubernetes Observability. It doesn’t matter which distribution you use, and no documentation is needed.

During onboarding, you can easily and seamlessly add Dynatrace Application Observability functionality like automated distributed tracing and code-level visibility to enhance workload health and performance.

Good product experiences go hand-in-hand with good pricing

That’s why the full Kubernetes Observability experience—which includes Kubernetes monitoring and application observability—is set at a price that is simple and transparent. Pricing relies on two key pillars:

• Predictable pricing for monitoring Kubernetes cluster health based on pod-hours. The longer a pod is monitored, the more pod-hours are consumed. Dynatrace pricing is independent of pod sizes or the number of nodes. It seamlessly works with all types of Kubernetes environments, whether they are fully managed (for example, GKE-Autopilot, EKS, AKS) or self-managed (on-premises or in the cloud).
• Flexible, consumption-based pricing for applications running on Kubernetes. Pricing is based solely on the memory used by the containerized applications that you are monitoring. Dynatrace Kubernetes cluster onboarding is rolling out its Full-Stack Monitoring mode in such a way that OneAgent code modules are only deployed to selected application pods.

All this is done automatically, simply, and conveniently. So, stop waiting. Embrace the experience of Dynatrace’s comprehensive Kubernetes observability offering and gain insights into your running workloads, pods, containers, and more.

What’s the next step in ensuring your Kubernetes health?

• The Kubernetes Observability app requires the latest Dynatrace platform, powered by Grail™, and a Dynatrace Platform Subscription. For more details, take a look at this blog post in the Dynatrace Community.
• You can find out more about the Kubernetes app in Dynatrace Documentation. For monitoring consumption documentation, see Container monitoring (DPS).
• Want to try it for yourself? Check it out here.

The post Kubernetes health at a glance: One experience to rule it all appeared first on Dynatrace news.