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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

already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. are technologically very different, Python and JMX extensions designed for Extension Framework 1.0 Extensions can monitor virtually any type of technology in your environment. Extensions 2.0

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Automatic connection of logs and traces accelerates AI-driven cloud analytics

Dynatrace

With PurePath ® distributed tracing and analysis technology at the code level, Dynatrace already provides the deepest possible insights into every transaction. By unifying log analytics with PurePath tracing, Dynatrace is now able to automatically connect monitored logs with PurePath distributed traces. How to get started.

Analytics 221
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New analytics capabilities for messaging system-related anomalies

Dynatrace

We’ve introduced brand-new analytics capabilities by building on top of existing features for messaging systems. Now, with technology-specific views, DevOps teams can see messaging system-related anomalies, which significantly simplifies troubleshooting efforts. Easily troubleshoot anomalies with technology-specific views.

Analytics 183
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Unlock end-to-end observability insights with Dynatrace PurePath 4 seamless integration of OpenTracing for Java

Dynatrace

Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Observability for heterogeneous cloud-native technologies is key. Dynatrace news. Deep-code execution details. Always-on profiling in transaction context.

Java 230
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Dynatrace extends AI-powered observability for SAP together with PowerConnect

Dynatrace

Monitoring SAP products can present challenges Monitoring SAP systems can be challenging due to the inherent complexity of using different technologies—such as ABAP, Java, and cloud offerings—and the sheer amount of generated data. Visibility into SAP CPI messages, down to every single attribute.

Java 185
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Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

Utilizing an additional OpenTelemetry SDK layer, this data seamlessly flows into the Dynatrace environment, offering advanced analytics and a holistic view of the AI deployment stack. While Dynatrace automates tracing for various technologies, Python-based AI models require OpenTelemetry. However, Python models are trickier.

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Log auditing and log forensics benefit from converging observability and security data

Dynatrace

As organizations adopt more cloud-native technologies, observability data—telemetry from applications and infrastructure, including logs, metrics, and traces—and security data are converging. However, cloud-native technologies have introduced a level of complexity that make a logs-only approach to auditing and forensics limiting.

Analytics 182