Integration Matrix
Runtime and platform integration coverage
Integrations connect telemetry to infrastructure reality. Without them, incidents lack deployment and runtime context.
Platform Matrix
| Platform | Runtime | Status | Doc |
|---|---|---|---|
| Kubernetes | Container | GA | Open |
| Docker | Container | GA | Open |
| Vercel | Node + Edge | GA | Open |
| Railway | Node | GA | Open |
| Supabase | Deno Edge | GA | Open |
| Cloudflare | Workers | GA | Open |
| AWS Lambda | Serverless | GA | Open |
| GCP Cloud Run | Container | GA | Open |
| Azure Container Apps | Container | GA | Open |
| GitHub Actions | CI pipeline | GA | Open |
Choosing the Right Integration Path
Decide using these dimensions:
- Runtime lifecycle (long-lived container vs serverless cold start).
- Deployment frequency and release process.
- Secrets and key distribution model.
- Network constraints and egress policies.
- Expected telemetry volume and retry behavior.
Integration Readiness Checklist
Before enabling an integration:
- Environment variables are centralized and audited.
- Service naming is standardized.
- Deployment metadata can be attached.
- Error budget for telemetry overhead is defined.
Runtime-Specific Considerations
Container Platforms (K8s, Docker, Cloud Run, ACA)
- Ensure graceful shutdown flush behavior.
- Validate queue drain during rolling deployments.
- Watch restart storms and duplicate signal bursts.
Serverless / Edge (Lambda, Cloudflare, Supabase, Vercel Edge)
- Prioritize low startup overhead.
- Tune sampling carefully for burst traffic.
- Validate async flush behavior in short execution windows.
CI/CD Integration (GitHub Actions)
- Propagate commit/build/deploy metadata.
- Keep artifact-version consistency.
- Fail fast on missing release context.
Operational Maturity Model
- Basic: telemetry ingestion works.
- Structured: tags and release metadata are consistent.
- Reliable: alerting and triage are stable.
- Intelligent: AI-assisted diagnosis is trusted due to strong data quality.