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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

address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0: Comprehensive metrics support Extensions 2.0 Reporting and analytics assets out-of-the-box Bundles offered by Extensions 2.0 available, and more are in the pipeline. Extensions 2.0

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Dynatrace extends contextual analytics and AIOps for open observability

Dynatrace

The result is that IT teams must often contend with metrics, logs, and traces that aren’t relevant to organizational business objectives—their challenge is to translate such unstructured data into actionable business insights. Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246
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Automatic connection of logs and traces accelerates AI-driven cloud analytics

Dynatrace

Manual and configuration-heavy approaches to putting telemetry data into context and connecting metrics, traces, and logs simply don’t scale. By unifying log analytics with PurePath tracing, Dynatrace is now able to automatically connect monitored logs with PurePath distributed traces. How to get started. New to Dynatrace?

Analytics 221
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Adding business analytics data to your observability strategy delivers better business outcomes

Dynatrace

To stay competitive in an increasingly digital landscape, organizations seek easier access to business analytics data from IT to make better business decisions faster. Five constraints that limit insights from business analytics data. Teams derive business metrics from many sources. Data silos.

Analytics 185
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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. A log is a detailed, timestamped record of an event generated by an operating system, computing environment, application, server, or network device.

Analytics 205
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Dynatrace observability is now available for Red Hat OpenShift on the IBM® Power® architecture

Dynatrace

IBM Power servers enable customers to respond faster to business demands, protect data from core to cloud, and streamline insights and automation. Captures metrics, traces, logs, and other telemetry data in context. Having all data in context tremendously simplifies analytics and problem detection.

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The road to observability with OpenTelemetry demo part 1: Identifying metrics and traces

Dynatrace

That is, relying on metrics, logs, and traces to understand what software is doing and where it’s running into snags. When software runs in a monolithic stack on on-site servers, observability is manageable enough. In addition to tracing, observability also defines two other key concepts, metrics and logs. What is OpenTelemetry?

Metrics 177