Discover the differences between two of the most used CRDs from Prometheus Operator and how to use each of them.
We have covered a lot about Prometheus in the past articles. It is one of the primary references when we talk about monitoring in a cloud-native environment and is specially focused on the Kubernetes ecosystem.
Prometheus has a new deployment model under the Kubernetes Operator Framework in recent times. That has generated several changes in terms of resources and how we configure several aspects of the monitoring of our workloads. Some of these concepts are now managed as Customer Resource Definition (CRD) that are included to simplify the system’s configuration and be more aligned with the capabilities of the Kubernetes platform itself. This is great but, at the same time, changes how we need to use this excellent monitoring tool for cloud-native workloads.
Today, we will cover two of these new CRDs, one of the most relevant ones: ServiceMonitor and PodMonitor. These are the new objects that specify the resources that will be under monitoring scope to the platform, and each of them covers a different type of object, as you can imagine: Services and Pods.
Each of them has its definition file with its particular fields and metadata, and to highlight them, I will present a sample for each of them below:
apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: labels: serviceMonitorSelector: prometheus name: prometheus namespace: prometheus spec: endpoints: - interval: 30s targetPort: 9090 path: /metrics namespaceSelector: matchNames: - prometheus selector: matchLabels: operated-prometheus: "true"
apiVersion: monitoring.coreos.com/v1 kind: PodMonitor metadata: name: front-end labels: name: front-end spec: namespaceSelector: matchNames: - sock-shop selector: matchLabels: name: front-end podMetricsEndpoints: - targetPort: 8079
As you can see, the definitions of the components are very similar and very intuitive, focusing on the selector to detect which pods or services we should monitor and some data regarding the specific target of the monitoring, so Prometheus knows how to scrape them.
If you want to take a look more in detail at any option you can configure on this CRD, I would recommend you to take a look at this URL which includes a detailed field to field documentation of the most common CRDs:
These components will belong to the definition of your workloads, which means that the creation and maintenance of these objects will be from the application’s developers.
That is great because several reasons:
- It will include the Monitoring aspect of the component itself, so you will never forget the add the configuration from a specific component. That means it can be included in the duplicate YAML files or Helm Chart or a Kustomize resources as another needed resource.
- It will de-centralize the monitoring configuration making it more agile, and it will progress as the software components do it.
- It will reduce the impact on other monitored components as there is no need to act in any standard file or resource, so any different workloads will continue to work as expected.
Both objects are very similar in their purposes as both of them scrape all the endpoints that match the selector that we added. So, in which cases should I use one or the other?
The answer will be straightforward. By default, you will go with a ServiceMonitor because it will provide the metrics from the service itself and each of the endpoints that the service has, so each of the pods that are implementing the service will be discovered and scraped as part of this action.
So, in which cases should I use PodMonitor? Where the workload you are trying to monitor doesn’t act behind a service, so as there is no service defined, you cannot use ServiceMonitor. Do you want some examples of those? Let’s bring some!
- Services that interact using other protocols that are not HTTP-based, such as Kafka, SQS/SNS, JMS, or similar ones.
- Components such as CronJobs, DaemonSets, or non exposing any incoming connection model.
So I hope this article will help you understand the main difference between those objects and go a little deeper into how the new Prometheus Operator Framework resources work. We will continue covering other aspects in upcoming posts.