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dt-obs-services

Monitor and analyze service performance and runtime metrics using DQL and OneAgent.

Updated Jun 18, 2026
Search Tags:#service mesh#service monitoring#application performance#runtime metrics#DQL
One-click install
npx skills add https://github.com/mf-dynatrace/dt-mcp-workspace --skill dt-obs-services-mf-dynatrace
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dt-obs-services
Source: https://github.com/mf-dynatrace/dt-mcp-workspace/tree/main/skills/dt-obs-services
Command: npx skills add https://github.com/mf-dynatrace/dt-mcp-workspace --skill dt-obs-services-mf-dynatrace

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides comprehensive monitoring and analysis of service performance and runtime metrics, enabling users to identify issues and optimize service health.

Core Features & Use Cases

  • Service Performance Monitoring: Monitor response time, error rate, and throughput for services.
  • Runtime Metrics: Track memory, garbage collection, and thread pool usage for Java, .NET, Node.js, Python, PHP, and Go services.
  • Service Mesh Insights: Analyze service mesh performance and overhead.
  • Use Case: For a Java application, use this Skill to monitor JVM memory usage, garbage collection activity, and thread pool performance to optimize resource allocation.

Quick Start

Use the dt-obs-services skill to get the response time and error rate for the service 'my-service'.

Frequently Asked Questions about dt-obs-services

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor service performance and runtime metrics for my applications?▼

To monitor service performance, you can track RED metrics like response time, error rate, and throughput, alongside runtime metrics such as memory and garbage collection for supported languages.

Does service monitoring work with Node.js, Python, and Go applications?▼

Yes, runtime service monitoring supports Java, .NET, Node.js, Python, PHP, and Go applications to track memory, garbage collection, and thread pool usage effectively.

How do I analyze service mesh performance and overhead?▼

You can analyze service mesh performance and overhead by leveraging built-in service mesh insights to evaluate traffic behavior and identify latency issues within your architecture.

Do I need DQL and OneAgent for application monitoring?▼

Yes, you need the DQL query language to query metrics and the OneAgent installed to collect application monitoring data and runtime metrics from your services.

What is the best way to track JVM memory usage and garbage collection?▼

The best way to track JVM memory usage and garbage collection is by applying runtime metrics analysis to your Java services, optimizing resource allocation based on thread pool performance.

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