dt-obs-services

Monitor RED metrics and runtime telemetry across multiple runtimes using DQL templates.

Updated Aug 23, 2026

Search Tags:#microservices #metrics #observability #service-monitoring #runtime-telemetry

Ready to run

npx skills add https://github.com/virtualrussel/dynatrace-ai-workspace --skill dt-obs-services-virtualrussel

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dt-obs-services
Source: https://github.com/virtualrussel/dynatrace-ai-workspace/tree/main/.agents/skills/dt-obs-services
Command: npx skills add https://github.com/virtualrussel/dynatrace-ai-workspace --skill dt-obs-services-virtualrussel

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Monitoring service performance, health, and runtime telemetry across multiple runtimes to enable faster incident triage, SLA tracking, and cross-service analysis.

Core Features & Use Cases

RED metrics (Rate, Errors, Duration) for services to quantify traffic and reliability
Runtime-specific telemetry for .NET, Java, Node.js, Python, PHP, and Go applications
Cross-service analytics: service mesh, messaging, and multi-cluster comparisons to reveal bottlenecks

Quick Start

Start by enabling runtime telemetry collection and querying core service-metrics to surface latency and error hotspots

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 RED metrics for microservices to ensure SLA compliance?▼

Monitoring RED metrics for microservices involves tracking Rate, Errors, and Duration to quantify traffic and reliability. This skill surfaces latency and error hotspots using DQL templates to enable proactive incident triage and SLA assurance.

Can I query runtime-specific telemetry for Node.js, Java, and Python applications?▼

Yes, you can query runtime-specific telemetry for Node.js, Java, and Python, alongside .NET, PHP, and Go. This skill provides runtime-aware telemetry and per-runtime metrics queries to monitor distinct application environments across microservices.

What is the best way to analyze service mesh overhead and cross-runtime telemetry?▼

Analyzing service mesh overhead and cross-runtime telemetry is best accomplished through cross-service analytics. This skill compares multi-cluster metrics and messaging bottlenecks using DQL templates to reveal performance degradation across cloud-native apps.

Do I need to enable runtime telemetry collection before querying core service metrics?▼

Yes, you need to enable runtime telemetry collection before querying core service metrics. Starting this collection allows the skill to successfully surface latency issues and error hotspots across your microservices and cloud-native applications.

How does cross-service analytics help with incident triage in cloud-native apps?▼

Cross-service analytics accelerates incident triage in cloud-native apps by comparing multi-cluster metrics and messaging bottlenecks. This skill uses DQL templates to perform cross-runtime telemetry analysis, revealing service bottlenecks and ensuring SLA compliance.