Prometheus is a free open source software application used for event monitoring and alerting. It was originally built at SoundCloud. It is now a standalone open source project and maintained independently of any company.
Prometheus collects and stores its metrics as time series data, i.e. metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels. Metrics are numeric measurements, time series mean that changes are recorded over time. What users want to measure differs from application to application. For a web server it might be request times, for a database it might be number of active connections or number of active queries etc.
Metrics play an important role in understanding why your application is working in a certain way. If you are running a web application and find that the application is slow. You will need some information to find out what is happening with your application. For example the application can become slow when the number of requests are high. If you have the request count metric you can spot the reason and increase the number of servers to handle the load.
In this guide we will learn how to run prometheus with docker and docker-compose.
- How to Setup Prometheus Monitoring On Kubernetes Cluster
- How to install and configure Prometheus AlertManager in Linux
- How to Setup Promtail, Grafana and Loki for free Log Management in Debian 11
- How to run Grafana Loki with docker and docker-compose
- How to install and set up Grafana in Ubuntu 20.04 using Ansible
- How To Install and Configure Prometheus On a Linux Server
- How to run Prometheus with docker and docker-compose
- How To Monitor Linux Servers Using Prometheus Node Exporter
Ensure that docker and docker compose is installed
Since we will be using docker to run prometheus, it is important that it is installed and running. Please ensure that you are have docker installed. If you are using an Ubuntu system, checkout this guide on How to Install and Use Docker in Ubuntu 22.04.
Confirm that docker is working as expecting by checking the version:
$ docker version Client: Docker Engine - Community Version: 20.10.17 API version: 1.41 Go version: go1.17.11 Git commit: 100c701 Built: Mon Jun 6 23:02:46 2022 OS/Arch: linux/amd64 Context: default Experimental: true Server: Docker Engine - Community Engine: Version: 20.10.17 API version: 1.41 (minimum version 1.12) Go version: go1.17.11 Git commit: a89b842 Built: Mon Jun 6 23:00:51 2022 OS/Arch: linux/amd64 Experimental: false containerd: Version: 1.6.6 GitCommit: 10c12954828e7c7c9b6e0ea9b0c02b01407d3ae1 runc: Version: 1.1.2 GitCommit: v1.1.2-0-ga916309 docker-init: Version: 0.19.0 GitCommit: de40ad0
Next, ensure that docker-compose is installed. Docker compose is available as a python pip package. Ensure that python and pip is installed then install docker-compose with this command:
sudo pip3 install docker-compose
Running prometheus with Docker
All Prometheus services are available as Docker images on Quay.io or Docker Hub.
Running Prometheus on Docker is as simple as
docker run -p 9090:9090 prom/prometheus. This starts Prometheus with a sample configuration and exposes it on port 9090.
You will need some basic configuration to use. Save this as prometheus.yml in the current directory:
# my global config global: scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute. evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute. # scrape_timeout is set to the global default (10s). # Alertmanager configuration alerting: alertmanagers: - static_configs: - targets: # - alertmanager:9093 # Load rules once and periodically evaluate them according to the global 'evaluation_interval'. rule_files: # - "first_rules.yml" # - "second_rules.yml" # A scrape configuration containing exactly one endpoint to scrape: # Here it's Prometheus itself. scrape_configs: # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config. - job_name: "prometheus" # metrics_path defaults to '/metrics' # scheme defaults to 'http'. static_configs: - targets: ["localhost:9090"]
The Prometheus image uses a volume to store the actual metrics. For production deployments it is highly recommended to use a named volume to ease managing the data on Prometheus upgrades.
To provide your own configuration, there are several options. Here are two examples.
Volumes & bind-mount
prometheus.yml from the host by running:
docker run \ -p 9090:9090 \ -v /path/to/prometheus.yml:/etc/prometheus/prometheus.yml \ prom/prometheus:latest
Or bind-mount the directory containing
/etc/prometheus by running:
docker run \ -p 9090:9090 \ -v /path/to/config:/etc/prometheus \ prom/prometheus:latest
This is the output on my system:
$ docker run \ -p 9090:9090 \ -v ./prometheus.yml:/etc/prometheus/prometheus.yml \ prom/prometheus:latest Unable to find image 'prom/prometheus:latest' locally latest: Pulling from prom/prometheus 50e8d59317eb: Pull complete b6c3b3e34d73: Pull complete c25d1f04e478: Pull complete cf87de5429d8: Pull complete f30143b595e6: Pull complete 9d4045bcdf1f: Pull complete 11e771ad0e20: Pull complete 26449787f2fa: Pull complete 9d2e147a0f6b: Pull complete fecd900b3277: Pull complete e18940bc0d33: Pull complete 76c3b14215ee: Pull complete Digest: sha256:f4c5fa1018a5c15f81250b8122f36f90146d5c2b323f9ec1f41d1b36dc0e7cb9 Status: Downloaded newer image for prom/prometheus:latest
To avoid managing a file on the host and bind-mount it, the configuration can be baked into the image. This works well if the configuration itself is rather static and the same across all environments.
For this, create a new directory with a Prometheus configuration and a
Dockerfile like this:
FROM prom/prometheus ADD prometheus.yml /etc/prometheus/
Now build and run it:
docker build -t my-prometheus . docker run -p 9090:9090 my-prometheus
A more advanced option is to render the configuration dynamically on start with some tooling or even have a daemon update it periodically.
Running prometheus with Docker Compose
We can add the instructions above to a docker compose file to make it easy for us to create, update and manage the deployments. Docker Compose is a tool for defining and running multi-container Docker applications. With Compose, you use a YAML file to configure your application’s services. Then, with a single command, you create and start all the services from your configuration.
Add the following to a
version: '3.9' services: prometheus: image: prom/prometheus:latest restart: always ports: - 9090:9090 volumes: - type: bind source: ./prometheus.yml target: /etc/prometheus/prometheus.yml
Save that file in the same directory where the configuration file
Now you can bring up the services with this command:
docker-compose up -d
This is the output in my system:
$ docker-compose up -d Creating network "prom_default" with the default driver Creating prom_prometheus_1 ... done
Now you can check the processes:
$ docker-compose ps Name Command State Ports ----------------------------------------------------------------------------------------------------- prom_prometheus_1 /bin/prometheus --config.f ... Up 0.0.0.0:9090->9090/tcp,:::9090->9090/tcp
From the above we can see that the service is up and running in port 9090. To access prometheus endpoint, visit http://server_ip:9090.
In this guide we managed to run prometheus using docker and docker-compose.
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