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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

Code changes are often required to refine observability data. This results in site reliability engineers nudging development teams to add resource attributes, endpoints, and tokens to their source code. Thus, measuring application performance becomes an unnecessarily frustrating coordination effort between teams.

Analytics 276
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Digital Business Analytics: Let’s get started!

Dynatrace

We introduced Digital Business Analytics in part one as a way for our customers to tie business metrics to application performance and user experience, delivering unified insights into how these metrics influence business milestones and KPIs. A sample Digital Business Analytics dashboard. Dynatrace news.

Analytics 206
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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. While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. Dynatrace Extensions 1.0 Extensions 2.0

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

Successful deployments of cloud-native workloads at the edge help to reduce costs, boost performance, and improve customer experience. By drilling down further on the workload level, you can gain valuable insights into the performance and potential problems of any containerized workload.

Retail 255
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Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

AI model observability plays a crucial role in achieving this by addressing these key aspects: Model performance and reliability: Evaluating the model’s ability to provide accurate and timely responses, ensuring stability, and assessing domain-specific semantic accuracy. Maintained under the Apache 2.0

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How a data lakehouse brings data insights to life

Dynatrace

Logs assist operations, security, and development teams in ensuring the reliability and performance of application environments. These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues.

Analytics 217
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Dynatrace leverages new AWS Lambda extensions for seamless end-to-end observability

Dynatrace

Dynatrace provides automatic and intelligent observability without touching any code through auto-instrumentation, thereby helping you to better understand potential issues that may impact your end users’ experience. All improvements are available with OneAgent version 1.217.

Lambda 295