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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0: available, and more are in the pipeline. Dynatrace Extensions 1.0

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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. The world service uses the custom web server? Use-case example: WorldAtlas sample application.

Java 156
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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. Standby Server Tests.

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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. Already a Dynatrace customer?

Java 233
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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. Thus, implementing applications in Java can result in considerable financial savings. IBM Java version 7.

Java 178
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Optimizing Java XPath CPU and memory overhead by 98%

Dynatrace

Solution : Use optimized methods to access / query for specific data, e.g.: getNodeByType resulted in 98% reduction of CPU usage, better performance, returned high availability and reduced operational costs. Perform an audit on default settings of the application server. Increase JVM memory limits to better handle spike load.

Java 222
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Managing High Availability in PostgreSQL – Part II

Scalegrid

Are you deploying PostgreSQL in the cloud and want to understand your options for achieving high availability? In our previous blog post, Managing High Availability in PostgreSQL – Part I , we discussed the capabilities and functioning of PostgreSQL Automatic Failover (PAF) by ClusterLabs. How it Works.