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Maximize user experience with out-of-the-box service-performance SLOs

Dynatrace

These signals ( latency, traffic, errors, and saturation ) provide a solid means of proactively monitoring operative systems via SLOs and tracking business success. Performance typically addresses response times or latency aspects and contributes to the four golden signals. This is what Dynatrace captures as response time.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

In this post, I’m going to break these processes down into each of: ? Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download. Read the complete test methodology. It gets worse.

Cache 291
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Dynatrace automatically monitors OpenAI ChatGPT for companies that deliver reliable, cost-effective services powered by generative AI

Dynatrace

Advanced AI applications using OpenAI services don’t just forward user input to OpenAI models; they also require client-side pre- and post-processing. A typical design pattern is the use of a semantic search over a domain-specific knowledge base, like internal documentation, to provide the required context in the prompt.

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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 200
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MongoDB Rollback: How to Minimize Data Loss

Scalegrid

Key Takeaways Rollbacks in MongoDB are triggered by disruptions in the replication process due to primary node crashes, network partitions, or other failures, which can lead to substantial data loss and inconsistencies. With direct, actionable insights, prepare to navigate the complexities of rollbacks with confidence.

Database 130
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Automated observability, security, and reliability at scale

Dynatrace

As software development grows more complex, managing components using an automated onboarding process becomes increasingly important. The validation process is automated based on events that occur, while the objectives’ configuration, which is validated by the Site Reliability Guardian , is stored in a separate file.

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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