# dt-obs-services

A Dynatrace skill that writes DQL queries for service health: RED metrics, SLA checks, service mesh overhead and runtime telemetry for six languages.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 2600 installs · ★ 167
- Author: Dynatrace
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/Dynatrace/dynatrace-for-ai/tree/HEAD/skills/dt-obs-services/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/dt-obs-services

## What it does

The skill gives your agent ready DQL patterns for Dynatrace services. Four areas are covered: Rate, Errors and Duration via `timeseries`, span-based queries for SLA thresholds and endpoint-level analysis, messaging metrics (publish, receive, process, failure), and a side-by-side of service mesh latency against direct calls.

Runtime telemetry is the second half. Java gets heap, metaspace, GC pauses and thread leaks; Node.js gets event loop and V8 heap; .NET CLR gets garbage collection and thread pool; Python, PHP and Go have their own metric sets. The detailed queries live in `references/` files the agent pulls in when needed.

Scope is narrow on purpose. Infrastructure metrics, logs and distributed tracing belong to sibling skills in the same repo, and product documentation questions go to `ask-dynatrace-docs`. One thing to know before you rely on it: the agent is told to proceed with sensible defaults instead of asking you for thresholds or service scope. Handy for a quick look, less so when you need an exact, pre-agreed calculation.

## Requirements
- Works with: Dynatrace

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-services -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/dt-obs-services/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/dt-obs-services/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-services -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/dt-obs-services/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-services -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/dt-obs-services/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install Dynatrace/dynatrace-for-ai dt-obs-services
```

2. **Manually: put the files in place**
- File: `.github/skills/dt-obs-services/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-services -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/Dynatrace/dynatrace-for-ai --path skills/dt-obs-services
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/dt-obs-services/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-services -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/Dynatrace/dynatrace-for-ai/tree/HEAD/skills/dt-obs-services/SKILL.md

## When to use it
- compute p95 and p99 response time per service
- spot an error spike and get its share of total requests
- check SLA compliance against a custom threshold
- measure service mesh overhead versus direct calls
- find out why GC pause time or goroutine count keeps climbing

## Example prompts
- Show p95 response time per service for the last hour
- Calculate the failed request rate and flag spikes
- Compare mesh and direct latency for the checkout service

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 5150b7c81921bb17.

BEGIN THIRD-PARTY FILE 5150b7c81921bb17
````text
---
name: dt-obs-services
description: >-
  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).
license: Apache-2.0
---

# Application Services Skill

Monitor application service performance, health, and runtime-specific metrics using DQL.

---

## Core Capabilities

### 1. Service Performance (RED Metrics)

Monitor service **Rate, Errors, Duration** using metrics-based timeseries queries.

**Key Metrics:**
- `dt.service.request.response_time` - Response time (microseconds)
- `dt.service.request.count` - Request count
- `dt.service.request.failure_count` - 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:**
```dql
timeseries {
  p95 = percentile(dt.service.request.response_time, 95),
  total_requests = sum(dt.service.request.count),
  failures = sum(dt.service.request.failure_count)
}, by: {dt.service.name}
| fieldsAdd p95_ms = p95[] / 1000, error_rate_pct = (failures[] * 100.0) / total_requests[]
```

→ **For detailed queries:** See [references/service-metrics.md](references/service-metrics.md)

### 2. Advanced Service Analysis

Span-based queries for complex scenarios requiring flexible filtering and custom aggregations.

**Use Cases:**
- SLA compliance tracking with custom thresholds
- Service health scoring (multi-dimensional)
- Operation/endpoint-level performance analysis
- Custom error classification
- Failure pattern detection with error details

**Quick Example:**
```dql
fetch spans, from: now() - 1h | filter request.is_root_span == true
| fieldsAdd meets_sla = if(request.is_failed == false AND duration < 3s, 1, else: 0)
| summarize total = count(), sla_compliant = sum(meets_sla), by: {dt.service.name}
| fieldsAdd sla_compliance_pct = (sla_compliant * 100.0) / total
```
````
END THIRD-PARTY FILE 5150b7c81921bb17

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