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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

Second, embracing the complexity of OpenTelemetry signal collection must come with a guaranteed payoff: gaining analytical insights and causal relationships that improve business performance. The missed SLO can be analytically explored and improved using Davis insights on an out-of-the-box Kubernetes workload overview.

Analytics 293
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Unlock the power of contextual log analytics

Dynatrace

For instance, in a Kubernetes environment, if an application fails, logs in context not only highlight the error alongside corresponding log entries but also provide correlated logs from surrounding services and infrastructure components. The Kubernetes app provides an overview of the current log volume, criticality, and security status.

Analytics 248
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Supercharge your end-to-end infrastructure and operations observability experience

Dynatrace

Dynatrace introduced numerous powerful features to its Infrastructure & Operations app, addressing the emerging requirement for enhanced end-to-end infrastructure observability. Let’s explore these exciting new features and see how they elevate infrastructure management. Overview of a cloud-hosted frontend web application.

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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Current analytics tools are fragmented and lack context for meaningful analysis. Effective analytics with the Dynatrace Query Language.

Analytics 246
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Dynatrace extends contextual analytics and AIOps for open observability

Dynatrace

With extended contextual analytics and AIOps for open observability, Dynatrace now provides you with deep insights into every entity in your IT landscape, enabling you to seamlessly integrate metrics, logs, and traces—the three pillars of observability. Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Stream Processing: to sample or not to sample trace data?

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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 222