1. Ingestion and retention #
Two levels of control.
Principle #
- Trace metrics (hits, errors, latency per resource) are computed on all traffic, whatever the sampling.
- Sampling rules (
DD_TRACE_SAMPLING_RULESvariable or remote configuration) decide which traces are ingested. - Retention filters choose the spans indexed for 15 days: by default errors, high latencies and a diverse sample.
export DD_TRACE_SAMPLING_RULES='[{"service":"shop","name":"http.request","sample_rate":0.2},{"service":"shop","resource":"GET /health","sample_rate":0}]' 2. Profiler and dynamic instrumentation #
Beyond traces.
Tools #
| Tool | Brings | Usage |
|---|---|---|
| Continuous Profiler | CPU, memory, locks per function, continuously | Find the expensive function behind a slow endpoint |
| Code Hotspots | Link between a span and the profile during that span | Explain the latency of a specific request |
| Dynamic Instrumentation | Add a log or a metric to the code in production, without redeploying | Investigate a rare bug |
| Error Tracking | Grouping errors into issues | Prioritize fixes |
3. Software Catalog #
Who owns what.
Service ownership #
The Software Catalog (formerly Service Catalog) lists services with their team, on-call, repositories, runbooks and criticality level, described in a file versioned with the code:
# service.datadog.yaml
apiVersion: v3
kind: service
metadata:
name: shop
owner: team-commerce
links:
- { name: Runbook, type: runbook, url: https://wiki.example.com/shop }
spec:
lifecycle: production
tier: "1"Good practice: A service without an owner is an incident without anyone responsible: make the catalog entry a prerequisite for going to production.
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