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Using Grafana with Prometheus for Alerting and Monitoring

Hands-On Lab


Photo of Travis Thomsen

Travis Thomsen

Course Development Director in Content





For the last six months, the Acme Anvil Corporation has been migrating some of their bare metal infrastructure to Docker containers. The team has set up Prometheus using cAdvisor to help monitor containers. After running Prometheus in the production environment for a few weeks, the team has decided to add Grafana for visualization and alerting.

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Using Grafana with Prometheus for Alerting and Monitoring


In this learning activity, we will learn how to set up Prometheus and Grafana for alerting and monitoring.

Accessing the Live Environment

On the lab instructions page, copy the public IP address of the cloud server to your clipboard. Open your terminal application, and run the following command:

ssh cloud_user@PUBLIC_IP_ADDRESS

At the prompt, enter yes to confirm that we wish to continue connecting.

Next, copy the password from the lab instructions page and enter it at the password prompt in your terminal. Then elevate privileges to root.

sudo su -

Enter the password again when prompted. We have now successfully logged in to the environment.

Using Grafana with Prometheus

Before we get started, let's take a look at our root directory to see what we have.


Currently, we have a dashboard, the docker-compose file that was used to set up the environment, and a Prometheus configuration file. Run clear to clear your screen.

Configure Docker

The first thing we need to do is create a daemon.json file for Docker.

vi /etc/docker/daemon.json

Once /etc/docker/daemon.json is open in the vi text editor, add the following:

  "metrics-addr" : "",
  "experimental" : true

Then, save and exit the vi editor.


Restart the Docker service.

systemctl restart docker

Run clear to clear your screen.

Update Prometheus

Next, we're going to edit the prometheus.yml file in the /root directory.

vi prometheus.yml

Change the contents of the file to the following: (Be sure to provide the private IP address of your instance)

  - job_name: prometheus
    scrape_interval: 5s
    - targets:
      - prometheus:9090
      - node-exporter:9100
      - pushgateway:9091
      - cadvisor:8080

  - job_name: docker
    scrape_interval: 5s
    - targets:
      - <PRIVATE_IP_ADDRESS>:9323

Then, save and quit.


Update Docker Compose

The next step is to open our docker-compose file and add three new services. Open docker-compose.yml.

vi ~/docker-compose.yml

Change the contents of the file to the following:

version: '3'
    image: prom/prometheus:latest
    container_name: prometheus
      - 9090:9090
      - --config.file=/etc/prometheus/prometheus.yml
      - ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
      - cadvisor
    image: google/cadvisor:latest
    container_name: cadvisor
      - 8080:8080
      - /:/rootfs:ro
      - /var/run:/var/run:rw
      - /sys:/sys:ro
      - /var/lib/docker/:/var/lib/docker:ro
    image: prom/pushgateway
    container_name: pushgateway
      - 9091:9091
    image: prom/node-exporter:latest
    container_name: node-exporter
    restart: unless-stopped
      - 9100
    image: grafana/grafana
    container_name: grafana
      - 3000:3000
      - prometheus
      - cadvisor

Then, save and quit.


Next, let's apply our changes and rebuild the environment.

docker-compose up -d

Then, let's make sure everything is running.

docker ps

Lastly, let's verify that all of our Prometheus targets are healthy. Open a web browser tab, and go to http://PUBLIC_IP_ADDRESS:9090. Click Status, and select Targets. Everything should be up and running correctly.

Create a New Grafana Data Source

Navigate to Grafana by entering http://PUBLIC_IP_ADDRESS:3000 in the address bar of your browser.

Type "admin" for username and "password" for password. Click Log In.

In the Grafana Home Dashboard, click the Add data source icon. For Name, type "Prometheus". Click into the Type field, and select Prometheus from the dropdown. Under URL, select http://localhost:9090. (But we're going to change this in a moment.) Navigate to the lab instructions page, and copy the private IP address to your clipboard. Then, replace "localhost" in the URL with the private IP address. (It should look like this: http://PRIVATE_IP_ADDRESS:9090).

Click Save & Test.

Add the Docker Dashboard to Grafana

Click the plus sign (+) on the left side of the Grafana interface, and click Import. Then, navigate to the lab instructions page. Open the JSON file included in the Instructions & Tasks section in a new browser tab. Copy the contents of the file to your clipboard.

Switch back to Grafana, and paste the text we just copied into the Or paste JSON field. Click Load. On the Import screen, click the dropdown menu for Prometheus, and select the Prometheus data source that we created earlier. Click Import.

We now have our Grafana visualization. In the upper right corner, click on Refresh every 5m and select Last 5 minutes.

Add an Email Notification Channel

In the left sidebar, click the bell icon, and select Notification channels. Click Add channel. For Name, type "Email". In Email addresses, enter your email address. Click Save.

Create an Alert for CPU Usage

Click the dashboard icon in the left sidebar, and select Home. Select the Docker and system monitoring dashboard. Click the CPU Usage graph, and select Edit from the dropdown.

In the Metrics tab, click Add Query. Enter the following:

sum(rate(process_cpu_seconds_total[1m])) * 100

Click the eye icon on the right side of Row E to hide the new rule from view.

Click the Alert tab, then Create Alert. Under Conditions, click into the query field and select E from the dropdown. For IS ABOVE, type "75". Click Test Rule.

Click Notifications in the left sidebar, then click the + icon next to Sent to. Select Email Alerts. Next, click into the Message text box, and type "CPU usage is over 75%." Click the save button at the top of the page. In the save popup that opens, check the box next to Save current variables. In the description box, type "Add alerting". Then click Save.


Congratulations, you've successfully completed this lab!