Quickstart

Get the full PLG observability stack running locally in under 5 minutes.

This guide walks you through starting the stack, verifying all five containers, connecting Grafana to Prometheus and Loki, and cleaning up when you’re done.

1. Clone the repository

   git clone https://github.com/dev-ugo/learning-observability-plg.git
   cd learning-observability-plg
   
2. Start the stack

   Start all five containers in detached mode:

   docker compose up -d
   

   Docker pulls any missing images on the first run, so this may take a minute or two depending on your connection speed.

3. Verify all containers are running

   docker compose ps
   

   You should see five containers with a running status:

   Container	Role
   prometheus	Metrics collection and storage
   node-exporter	Exposes system metrics (CPU, RAM, disk)
   loki	Log storage
   promtail	Log collection and forwarding to Loki
   grafana	Unified dashboard for metrics and logs

   If any container is not running, check its logs with docker compose logs <container-name>.

4. Open Grafana

   Go to http://localhost:3000 in your browser.

   The default credentials are admin / admin. Grafana will prompt you to change the password after your first login. The password is also set via the GF_SECURITY_ADMIN_PASSWORD environment variable in docker-compose.yml.

5. Add the Prometheus datasource

   1. In Grafana, go to Connections → Data sources → Add new data source.
   2. Select Prometheus.
   3. Set the URL field to:

   http://prometheus:9090
   

   4. Click Save & test. Grafana should confirm that the datasource is working.
6. Add the Loki datasource

   1. Go to Connections → Data sources → Add new data source.
   2. Select Loki.
   3. Set the URL field to:

   http://loki:3100
   

   4. Click Save & test.

   Both datasource URLs use Docker’s internal service names, which resolve correctly because all containers share the same Compose network.

   Datasource	URL
   Prometheus	http://prometheus:9090
   Loki	http://loki:3100

7. Create or import a dashboard

   With both datasources connected, you can build a dashboard or import an existing one:

   • Create a dashboard: go to Dashboards → New → New dashboard and add panels using PromQL for metrics and LogQL for logs.
   • Import a dashboard: go to Dashboards → New → Import and enter a Grafana dashboard ID from grafana.com/grafana/dashboards (for example, ID 1860 for the Node Exporter Full dashboard).

   Example PromQL queries to get started:

   # CPU usage %
   100 - (avg(rate(node_cpu_seconds_total{mode="idle"}[1m])) * 100)
   
   # RAM used (GB)
   (node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes) / 1024 / 1024 / 1024
   

   Example LogQL queries:

   # All system logs
   {job="varlogs"}
   
   # Filter errors only
   {job="varlogs"} |= "error"
   
8. Clean up

   When you’re done, stop and remove all containers:

   docker compose down
   

   This stops all running containers and removes the networks created by Compose. Your configuration files are not affected.