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An example can be seen at https://mon.jaytaala.com.

Guide

We'll cover the following steps:

Installing and configuring Prometheus (with Docker)

I'm assuming you are running an up-to-date Linux distro and you have Docker installed (if not, you'll need to install Docker).

We only need to run a single command (although it's not a short one) to install and configure our Prometheus setup.  To make this a bit easier, I provide my setup files in a git repo you can clone: 

https://gitlab.jaytaala.com/docker/prometheus.git

git clone https://gitlab.jaytaala.com/docker/prometheus

The repo contains only two files (which are the only two we need):

• run-container.sh : shell script that will run our docker command to install / configure prometheus.
• prometheus.yml : single configuration file for prometheus;

See the Explanation of run-container.sh section for an explanation and several notes for these files.

Once you've cloned the repo, simply make the script executable (if it isn't already) and run the script with:

chmod +x run-container.sh
./run-container.sh

Docker will then download the latest official Prometheus Docker image, create and configure the container and then run said container. 

If things worked as they should you should be able to visit the basic Prometheus web interface at http:\\<INTERNAL-SERVER-IP>:10090.

That's it!  You will now have Prometheus running on port 10090.

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This script simply creates (and/or runs) our Prometheus container.  So what's going on here?

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removes / deletes the container.  This deletes the already running container (if it exists) before creating a new one.

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main docker run command.

The -d flag means "detached" (i.e. run it detached or in the background) and the --name=prom names the container that will be created "prom".

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this data-binds our prometheus.yml config file to /etc/prometheus/prometheus.yml in the created Docker container.  I.e. prometheus running in the container will use this file for it's configuration.

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this instructs Docker to create a data volume (for storing our persistent Prometheus data) and call it "prom-data".

It's kind of similar to a data-bind but it's managed by Docker and provides many advantages.

The actual files (and persistent data) can be found at:
/var/lib/docker/volumes/prom-data/_data

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binds port 10090 on the host to post 10090 on the container (in other words exposes the prometheus port on the host).

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This file is the main Prometheus.yml scrape configuration file.  It defines things like how often Prometheus should scrape (query) data and from where (and how) it should scrape this data.

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Prometheus (be default) monitors itself and can report on scrape query duration, samples added to db, data compaction stats etc.

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Scrape configutation for node_exporter, an exporter which scrape server machine metrics.  We haven't set this up yet but will in the following sections.

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Scrape configuration for blackbox, a prober that can probe endpoints over HTTP, HTTPS, DNS, TCP and ICMP.  We haven't set this up yet but will in the following sections.

A bit about Blackbox Exporter, Node_Exporter and Grafana...

Guide

We'll cover the following steps:

Installing and configuring Prometheus, Blackbox exporter, and Grafana with Docker-Compose

I'm assuming you are running an up-to-date Linux distro and you have Docker and Docker Compose installed (if not, you'll need to install Docker and then Docker Compose).

Thanks to Docker and Docker Compose, we'll only need to run a single command to deploy Prometheus, an exporter (which can query endpoints), and Grafana.  Let's start by cloning our setup files from my git repo:

https://gitlab.jaytaala.com/docker/docker-compose-prometheus-grafana

git clone https://gitlab.jaytaala.com/docker/docker-compose-prometheus-grafana.git

The repo contains several files:

• blackbox-exporter.yml : configuration file for blackbox-exporter
• dashboard-blackbox.json : blackbox exporter dashboard I've customised see Adding monitoring dashboards;
• dashboard-node_exporter.json : node_exporter dashboard I've customised see Adding monitoring dashboards;
• docker-compose.yml : docker compose config file
• grafana.ini : grafana configuration file
• prometheus.yml : prometheus configuration file

Once you've cloned the repo, simply run (from the with the cloned folder:

docker-compose up -d

If things worked as they should you should be able to visit the basic Grafana web interface at http:\\<INTERNAL-SERVER-IP>:3000.

That's it!  that wasn't so bad was it?

Troubleshooting

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    ports:
      - 4000:3000
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Optional reading (explanation of configuration files)

Installing and configuring node_exporter (to monitor server stats)

By default node_exporter enables a large number of "collectors" (modules which collect certain information from the machine).  See here for a list of collectors enabled by default (and what info they collect).

node_exporter can be run from a docker container, but it's not recommended since it should be run directly on the host hardware to collect stats.

Installing node_exporter can be done by downloading a recent version version, untar'ing and executing.  We're going to be doing an extra step here to manage node_exporter with systemd (so it starts on server boot etc.).

We start with downloading.  You can find a link for the latest version at https://prometheus.io/download/#node_exporter.  At the time of this writing the latest stable version for linux-amd64 was node_exporter-0.18.1.linux-amd64.tar.gz.

We'll download, untar, and then move it to /opt/node_exporter

wget https://github.com/prometheus/node_exporter/releases/download/v0.18.1/node_exporter-0.18.1.linux-amd64.tar.gz
tar -xf node_exporter-0.18.1.linux-amd64.tar.gz
sudo mv node_exporter-0.18.1.linux-amd64 /opt/node_exporter

With node_exporter installed let's make it easier to manage by creating a systemd service.  Create a file in /etc/systemd/system/ with your favourite text editor (I'm using vim here):

sudo vim /etc/systemd/system/node_exporter.service

and paste the following:

[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target

[Service]
Type=simple
ExecStart=/opt/node_exporter/node_exporter --web.listen-address=:10091

[Install]
WantedBy=multi-user.target

Finally let's enable it (to start on boot) and start the service

sudo systemctl daemon-reload
sudo systemctl enable --now node_exporter

We've already setup node_exporter in our prometheus configuration file (see lines 31 to 34). 

Setting up Grafana data sources and dashboards

Updating Prometheus with Docker

Updating with Docker is straight-forward.  We just need to pull the (latest) image and then re-run our run-container.sh script.

docker pull prom/prometheus
./run-container.sh

Installing and configuring node_exporter (to monitor server stats)

node_exporter is a prometheus exporter which monitors hardware and 'nix OS metrics.  It runs on a port exposed to prometheus and prometheus can then query it and get a (large) ranger of metrics for whatever machine is running node_exporter.

By default node_exporter enables a large number of "collectors" (modules which collect certain information from the machine).  See here for a list of collectors enabled by default (and what info they collect).

node_exporter can be run from a docker container, but it's not recommended since it should be run directly on the host hardware to collect stats.

Installing node_exporter can be done by downloading a recent version version, untar'ing and executing.  We're going to be doing an extra step here to manage node_exporter with systemd (so it starts on server boot etc.).

We start with downloading.  You can find a link for the latest version at https://prometheus.io/download/#node_exporter.  At the time of this writing the latest stable version for linux-amd64 was node_exporter-0.18.1.linux-amd64.tar.gz.

We'll download, untar, and then move it to /opt/node_exporter

wget https://github.com/prometheus/node_exporter/releases/download/v0.18.1/node_exporter-0.18.1.linux-amd64.tar.gz
tar -xf node_exporter-0.18.1.linux-amd64.tar.gz
sudo mv node_exporter-0.18.1.linux-amd64 /opt/node_exporter

With node_exporter installed let's make it easier to manage by creating a systemd service.  Create a file in /etc/systemd/system/ with your favourite text editor (I'm using vim here):

sudo vim /etc/systemd/system/node_exporter.service

and paste the following:

[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target

[Service]
Type=simple
ExecStart=/opt/node_exporter --web.listen-address=:10091

[Install]
WantedBy=multi-user.target

Finally let's enable it (to start on boot) and start the service

sudo systemctl daemon-reload
sudo systemctl enable --now node_exporter

We've already setup node_exporter in our prometheus configuration file (see lines 31 to 34). 

Installing and configuring blackbox (to monitor endpoints)

Blackbox exporter is a prometheus exporter which can probe endpoints via http/https, icmp, etc.  It's extremely simple to setup and can be used to monitor the status of various endpoints (which could be web applications, REST endpoints, etc.).

We'll be using the a docker image to install and configure Blackbox exporter.

Start by cloning https://gitlab.jaytaala.com/docker/blackbox:

git clone https://gitlab.jaytaala.com/docker/blackbox

Similar to our prometheus docker image install, the repo contains only two files (which are the only two we need):

• run-container.sh : shell script that will run our docker command to install / configure blackbox exporter;
• config.yml : single configuration file for for blackbox exporter.

To setup and run our blackbox exporter simply make the run-container.sh executable and run it:

chmod +x run-container.sh
./run-container.sh

This will start blackbox-exporter on the default port (9115).  The config.yml file is similar to the default blackbox-exporter config.yml, but set the preferred ip protocol to ipv4 (by default it uses ipv6).

We've already setup blackbox-exporter in our prometheus configuration file (see lines 36 to 57). 

Installing and configuring Grafana

Grafana is a great platform for visualising data and metrics from large data sets.  It can connect with a very large number of data sources and has native (built-in) prometheus support, which makes it extremely easy to integrate prometheus and provides an attractive and versatile front-end to view various prometheus metrics.

So let's go ahead and install grafana and do some basic setup.

Like previous approaches, we'll use a simple docker image and setup data-persistency via a docker-volume, set a port for grafana to use (in this example we use a custom port), as well as setup public (anonymous) viewing access.

We only need two files for all this - which you can get by cloning

https://gitlab.jaytaala.com/docker/grafana.git

git clone https://gitlab.jaytaala.com/docker/grafana.git

The repo contains:

• run-container.sh : shell script that will run our docker command to install / configure grafana.
• grafana.ini : single configuration file for grafana;
• dashboard-blackbox.json : blackbox exporter dashboard I've customised see Adding monitoring dashboards;
• dashboard-node_exporter.json : node_exporter dashboard I've customised see Adding monitoring dashboards;

See the Explanation of run-container.sh section for an explanation and several notes for these files.

Once you've cloned the repo, simply make the script executable (if it isn't already) and run the script with:

chmod +x run-container.sh
./run-container.sh

Docker will then download the latest official Prometheus Docker image, create and configure the container and then run said container. 

If things worked as they should you should be able to visit the basic Prometheus web interface at http:\\<INTERNAL-SERVER-IP>:10090.

That's it!  You will now have Prometheus running on port 10090.

...

This script simply creates (and/or runs) our grafana container.  So what's going on here?

...

removes / deletes the container.  This deletes the already running container (if it exists) before creating a new one.

...

main docker run command.

The -d flag means "detached" (i.e. run it detached or in the background) and the --name=graf names the container that will be created "graf".

...

this data-binds our grafana.ini config file to /etc/grafana/grafana.ini in the created Docker container.

...

this instructs Docker to create a data volume (for storing our persistent grafana data) and call it "graf-data".

It's kind of similar to a data-bind but it's managed by Docker and provides many advantages.

The actual files (and persistent data) can be found at:
/var/lib/docker/volumes/graf-data/_data

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binds port 4000 on the host to post 4000 on the container.

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This file is the main grafana config file for our setup.  It defines things server related settings, as well as settings we'll use to enable public viewing access.

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Adding Prometheus as a data source to Grafana

Once you have your docker container containers running, access port 4000 3000 on the server with a browser (e.g. visit http://192.168.0.1:4000 3000 or whatever your internal address is for your server). 

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Grafana will grab the dashboard and after a second or so will fetch the dashboard ready for importing.  Enter a few options (see arrows) and then click "Import":

References

1. https://www.docker.com/
2. https://docs.docker.com/compose/
3. https://prometheus.io/
4. https://github.com/prometheus/node_exporter
5. https://prometheus.io/download/#node_exporter
6. https://github.com/prometheus/blackbox_exporter
7. https://grafana.com/

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