Infra
KUBERNETES
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Observability Baseline Builder
Build a practical observability baseline including metrics, logs, alerting, dashboards, and retention policy recommendations.
Monitoring BaselineAlertingDashboardsRetention
Disclaimer: These estimates are indicative and should not replace a formal infrastructure assessment.
Summary
Stack
PROM GRAFANA
Criticality
HIGH
Generated Output
Recommended Metrics
- Availability: uptime, health check pass rate, restart count.
- Latency: p50/p95/p99 response time by endpoint/service.
- Traffic: request rate, queue depth, ingress/egress volume.
- Saturation: CPU, memory, disk I/O, network utilization.
- Business KPIs: successful transactions, checkout completion, revenue-impact metrics.
Logs to Collect
- Application structured logs with correlation/request IDs.
- Security/authentication logs including failed sign-in attempts.
- Infrastructure/system logs from hosts/nodes/runtime.
- Audit trail logs for admin/configuration changes.
- Load balancer and gateway access/error logs.
Alerts to Configure
- Error rate exceeds baseline for 5+ minutes.
- Latency budget burn exceeds SLO warning threshold.
- CPU/memory saturation sustained above safe limits.
- No telemetry data received from critical service.
- Paging alerts for customer-impacting incidents with on-call escalation.
Dashboards to Create
- Executive service health overview (availability, latency, errors).
- Platform operations dashboard (capacity, incidents, deployment markers).
- Dependency dashboard (database, queue, cache, third-party APIs).
- Security monitoring dashboard (auth failures, suspicious patterns).
- On-call diagnostic dashboard with last-hour and last-24h deep views.
Retention Recommendations
- High-resolution metrics: 30 days, aggregated metrics: 13 months.
- Security/audit logs: minimum 12 months (or per compliance obligation).
- Application logs: 30–90 days hot tier + archive for long-term investigations.
- Trace data: 7–30 days based on cost and incident response needs.
Generated Baseline Summary
This baseline prioritizes high observability controls for kubernetes workloads, with stack assumptions aligned to prom grafana.
Take the Next Step
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