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Extend infrastructure observability with JMX Extensions and additional full-stack metrics

Dynatrace

Infrastructure exists to support the backing services that are collectively perceived by users to be your web application. Issues that manifest themselves as performance degradation on a user’s device can often be traced back to underlying infrastructure issues. Monitor additional metrics. Dynatrace news.

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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

This challenge has given rise to the discipline of observability engineering, which concentrates on the details of telemetry data to fine-tune observability use cases. To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus.

Metrics 177
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. Recovery time of the throughput metric.

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9 key DevOps metrics for success

Dynatrace

Now, with the hard work done, you can sit back, relax, and witness the collaboration between your Dev and Ops teams as they deliver better quality software faster. The emerging concepts of working with DevOps metrics and DevOps KPIs have really come a long way. DevOps metrics to help you meet your DevOps goals.

DevOps 199
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Dynatrace innovates again with the release of topology-driven auto-adaptive metric baselines

Dynatrace

With the advent and ingestion of thousands of custom metrics into Dynatrace, we’ve once again pushed the boundaries of automatic, AI-based root cause analysis with the introduction of auto-adaptive baselines as a foundational concept for Dynatrace topology-driven timeseries measurements. In many cases, metric behavior changes over time.

Metrics 210
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Enhancing Kubernetes cluster management key to platform engineering success

Dynatrace

As organizations continue to modernize their technology stacks, many turn to Kubernetes , an open source container orchestration system for automating software deployment, scaling, and management. ” First, Akamas collects metrics, then recommends configuration improvements and applies these recommendations.