local Prometheus + Grafana monitoring stack

🔍 Just spun up a local Prometheus + Grafana monitoring stack — and honestly, every DevOps engineer should do this at least once.

After working with monitoring tools in production for a while, I wanted to rebuild the full observability pipeline from scratch on my local machine to really understand what's happening under the hood.

Here's what the stack looks like:

⚙️ Node Exporter → scrapes system-level metrics (CPU, RAM, Disk, Network) 📦 Prometheus → scrapes and stores time-series data every 15s 📊 Grafana → visualizes everything with real-time dashboards

All containerized with Docker Compose on WSL2 — clean, reproducible, no Windows headaches.

A few things I was reminded of doing this: → Understanding the scrape pipeline makes you way better at debugging metric gaps in production → PromQL is simple once you stop being scared of it — start with rate() and go from here → Dashboard ID 1860 on Grafana is an absolute cheat code for Node Exporter visualization

Next up: Adding Alertmanager and wiring it to Slack for real alerting practice.

If you're learning DevOps or SRE, don't wait for a job to give you a monitoring setup — build one yourself. Took me under 30 minutes.

#DevOps #Prometheus #Grafana #Monitoring #Observability #Docker #SRE #Linux