What monitoring stack should I use?

For most teams: Prometheus + Grafana for metrics, Loki or ELK for logs, and Jaeger or Tempo for traces. Datadog is an excellent all-in-one alternative if budget allows.

How many alerts should I start with?

Start with 5-10 critical alerts: service down, error rate above threshold, latency P99 above SLO, disk space low, and certificate expiry. Add more gradually based on incident learnings.

Do I need distributed tracing from day one?

If you have more than two services, yes. Tracing becomes essential for debugging cross-service issues. Instrument with OpenTelemetry early — retrofitting is much harder.

Monitoring Setup Checklist

Build comprehensive observability with metrics, logs, traces, and alerts. Know what is happening in production before your users tell you.

Checklist: Monitoring Setup (engineering)

Production monitoring is the foundation of operational reliability. Without proper observability, you are flying blind — incidents go undetected, performance degrades silently, and debugging takes hours instead of minutes. This checklist covers the three pillars of observability (metrics, logs, traces) plus alerting and dashboarding.

Checklist Items

Define key service-level indicators (SLIs) [critical]: Identify the metrics that matter most: latency, error rate, throughput, and saturation for each service.
Set up infrastructure metrics collection [critical]: Collect CPU, memory, disk, and network metrics from all servers and containers using Prometheus, Datadog, or CloudWatch.
Implement structured application logging [critical]: Log in JSON format with consistent fields: timestamp, level, request ID, service name, and context.
Configure centralized log aggregation [important]: Ship all logs to a central system (ELK, Datadog, Loki) with retention policies and search capability.
Set up distributed tracing [important]: Implement OpenTelemetry or Jaeger tracing across services to track requests from ingress to database and back.
Create alerting rules for critical conditions [important]: Define alerts for error rate spikes, latency degradation, service downtime, and resource exhaustion with appropriate thresholds.
Configure alert routing and on-call schedules [important]: Route alerts to the right team via PagerDuty or Opsgenie with escalation policies and on-call rotations.
Build service health dashboards [recommended]: Create dashboards showing the RED metrics (Rate, Errors, Duration) for each service at a glance.
Implement synthetic monitoring [recommended]: Run automated health checks from external locations to detect outages and performance issues before users report them.
Set up SLO tracking and error budget dashboards [recommended]: Define service-level objectives and track error budgets to balance reliability with feature velocity.

Common Mistakes

Alert fatigue from noisy alerts: Start with few, high-signal alerts on symptoms (error rate, latency) not causes (CPU usage). Add more only when needed.
No correlation between metrics, logs, and traces: Include trace IDs in log entries and link metrics to traces. Correlated observability data cuts debugging time dramatically.
Monitoring only the happy path: Monitor error paths, timeout rates, retry rates, and queue depths. Problems hide in the flows you do not watch.

Frequently Asked Questions

What monitoring stack should I use?: For most teams: Prometheus + Grafana for metrics, Loki or ELK for logs, and Jaeger or Tempo for traces. Datadog is an excellent all-in-one alternative if budget allows.
How many alerts should I start with?: Start with 5-10 critical alerts: service down, error rate above threshold, latency P99 above SLO, disk space low, and certificate expiry. Add more gradually based on incident learnings.
Do I need distributed tracing from day one?: If you have more than two services, yes. Tracing becomes essential for debugging cross-service issues. Instrument with OpenTelemetry early — retrofitting is much harder.