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Java memory optimizations: 3x Jenkins performance improvement with Dynatrace

Dynatrace

Dynatrace also alerted on intermittent outages throughout the day and especially after 8pm when the bulk of the nightly jobs were executed: On March 31st our Jenkins violated our SLAs from both availability and user experience. But let’s start from the beginning: Step #1 – Switching to Java 11.

Java 332
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Transform mainframe applications into z/OS Java services with end-to-end transaction visibility and anomaly detection (Preview)

Dynatrace

Although these COBOL applications operate with consistent performance, companies and governments are forced to transform them to new platforms and rewrite them in modern programming languages (like Java) for several reasons. Processing capacity associated with zIIPs isn’t subject to license costs and maintenance fees.

Java 257
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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. Use-case example: WorldAtlas sample application. protection of sensitive data.

Java 236
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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.

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Unlock end-to-end observability insights with Dynatrace PurePath 4 seamless integration of OpenTracing for Java

Dynatrace

Therefore, we’re happy to announce support for OpenTracing data that’s emitted by auto- and custom-instrumentation of Java source code with Dynatrace PurePath 4, our distributed tracing and code-level analysis technology. Find OpenTracing for Java seamlessly integrated into PurePath 4.

Java 264
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Managing High Availability in PostgreSQL – Part III: Patroni

Scalegrid

In the final post of this series, we will review the last solution, Patroni by Zalando, and compare all three at the end so you can determine which high availability framework is best for your PostgreSQL hosting deployment. Managing High Availability in PostgreSQL – Part I: PostgreSQL Automatic Failover. Kill the PostgreSQL process.

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Managing PostgreSQL® High Availability – Part I: PostgreSQL Automatic Failover

Scalegrid

Managing High Availability (HA) in your PostgreSQL hosting is very important to ensuring your database deployment clusters maintain exceptional uptime and strong operational performance so your data is always available to your application. Effective management of failover and switchover operations is crucial for high availability.