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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 206
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AI-driven analysis of Spring Micrometer metrics in context, with typology at scale

Dynatrace

Spring Boot 2 uses Micrometer as its default application metrics collector and automatically registers metrics for a wide variety of technologies, like JVM, CPU Usage, Spring MVC, and WebFlux request latencies, cache utilization, data source utilization, Rabbit MQ connection factories, and more. To learn more, see our documentation.

Metrics 210
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AI-driven analysis of Spring Micrometer metrics in context, with topology at scale

Dynatrace

Spring Boot 2 uses Micrometer as its default application metrics collector and automatically registers metrics for a wide variety of technologies, like JVM, CPU Usage, Spring MVC, and WebFlux request latencies, cache utilization, data source utilization, Rabbit MQ connection factories, and more. To learn more, see our documentation.

Metrics 130
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AI-driven analysis of Spring Micrometer metrics in context, with topology at scale

Dynatrace

Spring Boot 2 uses Micrometer as its default application metrics collector and automatically registers metrics for a wide variety of technologies, like JVM, CPU Usage, Spring MVC, and WebFlux request latencies, cache utilization, data source utilization, Rabbit MQ connection factories, and more. To learn more, see our documentation.

Metrics 130
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI. You can find a lot more details about how this works in the Spinnaker canaries documentation. This meant that data that was static (e.g.

Latency 233
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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

There is no way to model how much more traffic you can send to that system before it exceeds it’s SLA. This is unfortunate, because we’d really like to be able to build systems that have an SLA that we can share with the consumers of our interfaces, and be able to measure how well we are doing.

Lambda 98
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Rethinking Server-Timing As A Critical Monitoring Tool

Smashing Magazine

This allows resource requests, including the HTML document itself, to be enriched with data during its lifecycle, and that information can be inspected for measuring the attributes of that resource! For the top-level HTML document, it is fetched upon user navigation but is still a resource request.

Servers 92