Prometheus + Grafana Monitoring Stack

Mon, 01 Jan 0001 00:00:00 +0000

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 — 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

✅ MTTD: reduced from 30 minutes to under 1 minute
✅ MTTR: recovery time reduced by 60%
✅ Alerts: proactive notifications before users are impacted
✅ Visibility: full observability across all services
✅ Capacity planning: data-driven resource forecasting

SRE and Observability on DevOps Engineer & CloudAdmin