Prometheus and Grafana are two popular open source tools for monitoring and analyzing system metrics. Prometheus collects and stores time series data from various sources, while Grafana provides a powerful and customizable dashboard for visualizing the data. In this blog post, I will show you how to use these tools to monitor workloads on three different cloud platforms: OpenShift, Microsoft Azure, and Amazon AWS.
What is OpenShift?
OpenShift is a Kubernetes-based platform as a service (PaaS) that allows you to build, deploy, and run containerized applications on any cloud or on-premises environment. OpenShift provides a consistent and secure platform for developers and operators, with features such as self-service provisioning, automated scaling, integrated CI/CD, service mesh, serverless, and more. OpenShift also offers a managed service option called Red Hat OpenShift Service on AWS (ROSA), which provides an integrated experience with AWS services and billing.
What is Microsoft Azure?
Microsoft Azure is a cloud computing service that offers a wide range of solutions for various scenarios, such as infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), and hybrid cloud. Azure supports multiple programming languages, frameworks, and tools, and provides services for compute, storage, networking, database, analytics, machine learning, IoT, security, and more. Azure also has a Kubernetes service called Azure Kubernetes Service (AKS), which simplifies the deployment and management of Kubernetes clusters on Azure.
What is Amazon AWS?
Amazon AWS is a cloud computing service that provides on-demand access to a variety of resources and services, such as compute, storage, networking, database, analytics, machine learning, IoT, security, and more. AWS supports multiple programming languages, frameworks, and tools, and offers a range of options for deploying and running applications, such as EC2, Lambda, Elastic Beanstalk, and more. AWS also has a Kubernetes service called Amazon Elastic Kubernetes Service (EKS), which makes it easy to run Kubernetes applications on AWS.
How to install Prometheus and Grafana on OpenShift, Azure, and AWS?
There are different ways to install Prometheus and Grafana on each cloud platform, depending on your preferences and requirements. Here are some examples of how to do it:
OpenShift
On OpenShift, you can use the OpenShift Container Platform (OCP) web console or the oc command-line tool to install Prometheus and Grafana from the OperatorHub, which is a catalog of operators that can be easily deployed and managed on OpenShift. Alternatively, you can use Helm, which is a package manager for Kubernetes, to install Prometheus and Grafana from the Helm charts repository.
On OpenShift, you can use Prometheus and Grafana to monitor the performance and availability of your 3scale API Management service, which is a platform for managing and securing APIs. You can collect metrics such as requests, errors, latency, and traffic from the 3scale components and visualize them in Grafana dashboards. You can also set up alerts to notify you of any issues or anomalies with your API service.
MS Azure
On Azure, you can use the Azure portal or the az command-line tool to create an AKS cluster and enable the monitoring add-on, which automatically installs Prometheus and Grafana on the cluster. Alternatively, you can use Helm to install Prometheus and Grafana from the Helm charts repository.
On Azure, you can use Prometheus and Grafana to monitor the health and performance of your Azure Kubernetes Service (AKS) cluster, which is a managed service for running Kubernetes applications on Azure. You can collect metrics such as cluster state, node status, pod status, resource utilization, and network traffic from the AKS components and visualize them in Grafana dashboards. You can also set up alerts to notify you of any problems or bottlenecks with your cluster.
Amazon AWS
On AWS, you can use the AWS Management Console or the aws command-line tool to create an EKS cluster and install Prometheus and Grafana using the eksctl command-line tool, which is a simple and easy way to create and manage EKS clusters. Alternatively, you can use Helm to install Prometheus and Grafana from the Helm charts repository.
On AWS, you can use Prometheus and Grafana to monitor the scalability and reliability of your Amazon Elastic Kubernetes Service (EKS) cluster, which is a managed service for running Kubernetes applications on AWS. You can collect metrics such as cluster autoscaling, node group scaling, pod disruption budget, and pod readiness from the EKS components and visualize them in Grafana dashboards. You can also set up alerts to notify you of any changes or disruptions with your cluster.
How to configure Prometheus and Grafana on OpenShift, Azure, and AWS?
After installing Prometheus and Grafana on your chosen cloud platform, you need to configure them to collect and display the metrics that you are interested in. Here are some examples of how to do it:
On OpenShift, you can use the Prometheus web UI or the oc command-line tool to configure Prometheus to scrape metrics from the OpenShift cluster components, such as the API server, the controller manager, the scheduler, the kubelet, and the etcd. You can also configure Prometheus to scrape metrics from your own applications running on OpenShift, by adding annotations or service monitors to your pods or services. You can use the Grafana web UI or the oc command-line tool to configure Grafana to connect to the Prometheus data source and create dashboards to visualize the metrics. You can also import pre-built dashboards from the Grafana website or the OpenShift community.
On Azure, you can use the Prometheus web UI or the az command-line tool to configure Prometheus to scrape metrics from the AKS cluster components, such as the API server, the controller manager, the scheduler, the kubelet, and the etcd. You can also configure Prometheus to scrape metrics from your own applications running on AKS, by adding annotations or service monitors to your pods or services. You can use the Grafana web UI or the az command-line tool to configure Grafana to connect to the Prometheus data source and create dashboards to visualize the metrics. You can also import pre-built dashboards from the Grafana website or the Azure community.
On AWS, you can use the Prometheus web UI or the aws command-line tool to configure Prometheus to scrape metrics from the EKS cluster components, such as the API server, the controller manager, the scheduler, the kubelet, and the etcd. You can also configure Prometheus to scrape metrics from your own applications running on EKS, by adding annotations or service monitors to your pods or services. You can use the Grafana web UI or the aws command-line tool to configure Grafana to connect to the Prometheus data source and create dashboards to visualize the metrics. You can also import pre-built dashboards from the Grafana website or the AWS community.
Conclusion
Prometheus and Grafana are powerful tools for monitoring and analyzing system metrics on any cloud platform. In this blog post, I have shown you how to use these tools to monitor workloads on OpenShift, Azure, and AWS. I hope you have found this post useful and informative. If you have any questions or feedback, please feel free to leave a comment below.
References:
1: Cloud Integration – Red Hat OpenShift Service on AWS – AWS 2: Amazon AWS vs Microsoft Azure vs OpenShift comparison 3: Deploy and run OpenShift on AWS: 4 options | Enable Sysadmin 4: Amazon AWS vs OpenShift Comparison 2023 | PeerSpot 5: Get started with Grafana and Prometheus | Grafana documentation 6: What is Prometheus? | Grafana documentation 7: How Grafana and Prometheus work together | MetricFire Blog 8: Prometheus vs Grafana: Knowing the Difference : OpsRamp