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What is observability? Not just logs, metrics and traces

Dynatrace

In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. In a monitoring scenario, you typically preconfigure dashboards that are meant to alert you to performance issues you expect to see later. What is observability?

Metrics 363
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Dynatrace extends Synthetic Monitoring capabilities with Network Availability Monitors to validate the availability of infrastructure and services

Dynatrace

As HTTP and browser monitors cover the application level of the ISO /OSI model , successful executions of synthetic tests indicate that availability and performance meet the expected thresholds of your entire technological stack. Our script, available on GitHub , provides details. into NAM test definitions.

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Dynatrace simplifies OpenTelemetry metric collection for context-aware AI analytics

Dynatrace

The release candidate of OpenTelemetry metrics was announced earlier this year at Kubecon in Valencia, Spain. Since then, organizations have embraced OTLP as an all-in-one protocol for observability signals, including metrics, traces, and logs, which will also gain Dynatrace support in early 2023.

Analytics 293
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Mobile Performance Metrics You Should Know: Part 1

DZone

Speed, UX, availability, and frequency of updates are increasingly important with mobile apps. The responsibility of developers keeps growing, and as mobile apps get more complex, new tools for mobile performance monitoring and testing are being born. Consumers and enterprises alike expect more from software.

Mobile 246
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Dynatrace observability now available for Red Hat OpenShift on IBM Z and LinuxONE mainframes

Dynatrace

Telemetry data, such as traces and metrics, allow you to analyze the end-to-end performance of your deployed applications. You can automatically detect and analyze performance issues across your entire tech stack with Davis® AI. Dynatrace observability is available for Red Hat OpenShift on IBM Power.

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Spark-Radiant: Apache Spark Performance and Cost Optimizer

DZone

Spark-Radiant is Apache Spark Performance and Cost Optimizer. Spark-Radiant will help optimize performance and cost considering catalyst optimizer rules, enhance auto-scaling in Spark, collect important metrics related to a Spark job, Bloom filter index in Spark, etc. Spark-Radiant is now available and ready to use.

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Create compelling insights into business and operational KPIs through metric calculations in the Data explorer

Dynatrace

Metrics matter. But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. To achieve relevant insights, raw metrics typically need to be processed through filtering, aggregation, or arithmetic operations. Examples of metric calculations. Dynatrace news.

Metrics 246