Prometheus is a monitoring system that collects metrics from services and makes them available for querying.
It can be used to monitor any system. In this blog post, we will show the strengths of Prometheus in different environments.
Prometheus was designed for monitoring distributed systems, making it ideal for monitoring the complex architectures found in Kubernetes deployments.
The Prometheus service discovery mechanism automatically identifies and monitors services, containers, ingresses, and endpoints running in your Kubernetes cluster. You don’t have to change your configuration to have new pods reflected in your monitoring solution.
Kubernetes itself integrates natively with Prometheus. Its main components, such as the kubelet, support Prometheus natively.
Kubernetes and Prometheus sit in the Cloud Native Compute Foundation (CNCF). As graduated projects, they are widely used by the cloud-native community in production.
They are open source and free to use, and they will remain like this. It also means that both projects are supported by a large ecosystem of vendors and users.
You can even use the Prometheus Operator for Kubernetes that simplifies the configuration and management of Prometheus monitoring for Kubernetes services and applications.
Prometheus can monitor any system with exporters making it suitable for on-prem environment monitoring. Exporters are programs that expose metrics from a given system in a format that Prometheus can understand.
This means you can use Prometheus to monitor anything, from system performance to application health. There are many exporters available, both official and unofficial.
Click here for a full list of exporters
As Prometheus is Open Source and stores the data locally, you don’t have to worry about where your data is sent or what happens with it. It’s all stored locally in your datacenter.
Virtual machines metrics can be fetched with exporters that support a wide range of operating systems:
- node_exporter for Linux and Unix-like machines
- windows_exporters for Windows machines.
Those exporters provide great insights about the health and the status of the machines they are running on.
The SNMP exporter integrates Prometheus nicely with networking devices.
By collecting metrics from the various SNMP objects, Prometheus can provide a detailed view of how the device performs.
This can be valuable for troubleshooting and performance tuning, as the data is queryable over time with the Prometheus Query Language, PromQL.
The Prometheus client libraries can be used to instrument your own code and expose metrics to the Prometheus server.
Client libraries exist for a variety of programming languages, allowing you to instrument your code in the language of your choice. Go, Java or Scala, Python, Ruby, and Rust are officially supported. There are many other libraries from the community that covers other programming languages.
On top of those client libraries, many frameworks also integrate natively with Prometheus.
Those libraries will provide you with metrics about the health and performances of your applications, and can be expanded to provided you business metrics.
The flexibility and openness of Prometheus make it suitable for many different scenarios.
If you have a service or an infrastructure, Prometheus can monitor it.
Do you have questions about how to expose metrics from just about anything? We provide premium Prometheus support and have Prometheus experts ready to help with all your questions.