Configure Grafana to visualize metrics emitted from the managed instance cluster

When you deploy an Azure Managed Instance for Apache Cassandra cluster, the service provisions Metrics Collector for Apache Cassandra agent software on each data node. Prometheus consumes the metrics and they're visualized through Grafana. This article describes how to configure Prometheus and Grafana to visualize metrics emitted from your managed instance cluster.

The following tasks are required to visualize metrics:

• Deploy an Ubuntu virtual machine (VM) inside the Azure virtual network where the managed instance is present.
• Install the Prometheus dashboards onto the VM.

Deploy an Ubuntu server

1. Sign in to the Azure portal.

2. Go to the resource group where your managed instance cluster is located. Select Add and search for the Ubuntu Server 18.04 LTS image.

   

3. Select the image, and then select Create.

4. On the Create a virtual machine pane, enter values for the following fields. You can leave default values for other fields:

   • Virtual machine name: Enter a name for your VM.
   • Region: Select the same region where your virtual network is deployed.

   

5. On the Networking tab, select the virtual network in which your managed instance is deployed.

   

6. Finally, select Review + create to create your metrics server.

Install Prometheus dashboards

1. First, ensure that the networking settings for your newly deployed Ubuntu server have inbound port rules that allow ports 9090 and 3000. These ports are required later for Prometheus and Grafana, respectively.

   

2. Connect to your Ubuntu server by using the Azure CLI or your preferred client tool to connect via Secure Shell.

3. After you connect to the VM, install the metrics collector software. First, download and unzip the files:

    #install unzip utility (if not already installed)
    sudo apt install unzip
   
    #get dashboards
    wget https://github.com/datastax/metric-collector-for-apache-cassandra/releases/download/v0.3.0/datastax-mcac-dashboards-0.3.0.zip -O temp.zip
    unzip temp.zip
   

4. Next, go to the Prometheus directory and use vi to edit the tg_mcac.json file:

    cd */prometheus
    vi tg_mcac.json    
   

5. Add the IP addresses of each node in your cluster in targets, each with port 9443. Your tg_mcac.json file should look like the following example:

    [
      {
        "targets": [
          "10.9.0.6:9443","10.9.0.7:9443","10.9.0.8:9443"
        ],
        "labels": {
   
        }
      }
    ]  
   

6. Save the file. Next, edit the prometheus.yaml file in the same directory. Locate the following section:

    file_sd_configs:
      - files:
        - 'tg_mcac.json'
   

7. Directly underneath this section, add the following snippet. This step is required because metrics are exposed via HTTPS.

    scheme: https
    tls_config:
            insecure_skip_verify: true
   

8. The file should now look like the following example. Ensure that the tabs on each line match the example:

    file_sd_configs:
      - files:
        - 'tg_mcac.json'
    scheme: https
    tls_config:
            insecure_skip_verify: true
   

9. Save the file. Now you can start Prometheus and Grafana. First, install Docker:

   sudo apt install apt-transport-https ca-certificates curl software-properties-common
   curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
   sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu `lsb_release -cs` test"
   sudo apt update
   sudo apt install docker-ce
   

10. Then install docker-compose:

    sudo apt install docker-compose
    

11. Now go to the top-level directory where docker-compose.yaml is located, and start the application:

    cd ..
    sudo docker-compose up
    

12. Prometheus should be available at port 9090 and Grafana dashboards on port 3000 on your metrics server.

    

Related content

In this article, you learned how to configure dashboards to visualize metrics in Prometheus by using Grafana. Learn more about Azure Managed Instance for Apache Cassandra with the following articles:

• What is Azure Managed Instance for Apache Cassandra?
• Deploy a Managed Apache Spark Cluster with Azure Databricks