Pebble
Pebble is a stat's visualization tool, this will provide a skeleton to develop a monitoring tool.
- Prometheus: http://localhost:9090/graph
- Grafana: http://localhost:3000/
The combination of grafana and Prometheus is becoming a more and more common monitoring stack used by DevOps teams for storing and visualizing time series data. Prometheus acts as the storage backend and open source grafana as the interface for analysis and visualization.
Prometheus collects metrics from monitored targets by scraping metrics from HTTP endpoints on these targets.
Getting Start:
We have deployed Prometheus and Grafana in Docker. (Note: Storing the Prometheus data to disk volue is yet to finish).
.
├── Makefile
├── README.md
├── docker-compose.yml
├── grafana
│ ├── config.ini
│ ├── dashboards
│ │ └── dashboard.json
│ └── provisioning
│ ├── dashboards
│ │ └── all.yml
│ └── datasources
│ └── all.yml
├── pebble.png
├── prometheus
│ ├── prometheus.yml
│ └── rules.yml
└── push.py
docker-compose.yml
- starting configuration
Make start
will start the container and the application will be exposed in the following urls
- Prometheus: http://localhost:9090/graph
- Grafana: http://localhost:3000/ The login by default is admin:admin.
- The metrics from the app: http://localhost:9001/metrics
Make push
will push the data to pushgateway
of metrics.
Docs
PushGateWay Ref: https://github.com/prometheus/client_python#exporting-to-a-pushgateway
Grafana: https://grafana.com/tutorials/grafana-fundamentals/?utm_source=grafana_gettingstarted
Project Ref: https://github.com/Guardian-Development/yak/tree/main/yak-server/src/main/docker
Push gateway Client: https://github.com/prometheus/client_python#exporting-to-a-pushgateway
promhttp_metric_handler_requests_total
sample filter
Docker Ref: