Prometheus + Grafana Monitoring Stack
Observability Stack for Microservices Architecture Client Early-stage startup
Challenge After migrating to a microservices architecture (15+ services), the team had no centralized monitoring in place. Issues were only discovered through user complaints β typically 30+ minutes after they occurred. A full observability stack was needed to detect and diagnose problems proactively.
Solution 1. Monitoring Architecture Prometheus for metrics collection Grafana for visualization Loki for centralized log aggregation Jaeger for distributed tracing Alertmanager for notifications 2. Metrics Collection Automatic service discovery in Kubernetes Application-level custom metrics System metrics via node-exporter Database metrics via postgres-exporter and redis-exporter 3. Grafana Dashboards Per-service dashboards for each microservice Unified infrastructure overview dashboard SLA/SLO tracking metrics Business metrics (RPS, conversion rate) 4. Centralized Logging (Loki) Log aggregation across all services Full-text log search via Grafana Log-to-metric correlation 5. Distributed Tracing (Jaeger) HTTP request tracing across services Call chain visualization Bottleneck identification Per-service latency analysis 6. Alerting Alerts delivered to Slack / PagerDuty / custom webhooks Critical issue escalation On-call rotation support Automatic incident creation Technologies Prometheus Grafana Kubernetes Docker Helm Linux Results β
MTTD: reduced from 30 minutes to under 1 minute
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MTTR: recovery time reduced by 60%
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Alerts: proactive notifications before users are impacted
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Visibility: full observability across all services
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Capacity planning: data-driven resource forecasting
