dt-obs-services
Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. Trigger: "service response time", "error rate", "throughput", "SLA compliance", "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).
Install
git clone https://github.com/Dynatrace/dynatrace-for-ai /tmp/dynatrace-for-ai && ln -s /tmp/dynatrace-for-ai/skills/dt-obs-services ~/.claude/skills/dt-obs-servicesFrom README
Application Services Skill Monitor application service performance, health, and runtime-specific metrics using DQL. --- Core Capabilities Service Performance (RED Metrics) Monitor service Rate, Errors, Duration using metrics-based timeseries queries. Key Metrics: dt.service.request.responsetime - Response time (microseconds) dt.service.request.count - Request count dt.service.request.failurecount - Failed request count Common Use Cases: Response time monitoring (avg, p50, p95, p99) Error rate tracking and spike detection Traffic analysis (throughput, peaks, growth) Performance degradation detection Multi-cluster comparison Quick Example: → For detailed queries: See references/service-metrics.md Advanced Service Analysis Span-based queries for complex scenarios requiring flexible filtering and custom aggregations.
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