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Java memory optimizations: 3x Jenkins performance improvement with Dynatrace

Dynatrace

In my last blog I covered how our Engineering Productivity (EP) and Infrastructure & Services (IAS) Teams are ensuring that our DevOps tool chain is running as expected, even while workloads have shifted as our global engineering teams are now working from home. But let’s start from the beginning: Step #1 – Switching to Java 11.

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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. Reconstructing a streaming session was a tedious and time consuming process that involved tracing all interactions (requests) between the Netflix app, our Content Delivery Network (CDN), and backend microservices.

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What is infrastructure as code? Discover the basics, benefits, and best practices

Dynatrace

“As code” means simplifying complex and time-consuming tasks by automating some, or all, of their processes. ” While this methodology extends to every layer of the IT stack, infrastructure as code (IAC) is the most prominent example. .” What is infrastructure as code? What challenges does IAC solve?

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Automatic and intelligent end-to-end observability for OpenTelemetry Java

Dynatrace

Today, Dynatrace is happy to announce OneAgent support for discovering and automatically capturing OpenTelemetry trace data for Java. PurePath integrates OpenTelemetry Java data for enterprise-grade collection and contextual analytics. OpenTelemetry Java API version 1.0.0 Use-case example: WorldAtlas sample application.

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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. Dynatrace news. Monitor additional metrics.

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Simplify log onboarding: From zero to observability in minutes

Dynatrace

The newly introduced step-by-step guidance streamlines the process, while quick data flow validation accelerates the onboarding experience even for power users. Step-by-step setup The log ingestion wizard guides you through the prerequisites and provides ready-to-use command examples to start the installation process. Figure 5.

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is Apache Kafka?

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