Scaling Prometheus: What You Need to Know

Prometheus is an essential part of any cloud-native setup. Prometheus monitoring is now its own subcategory because it has become the de facto standard for visibility in Kubernetes deployments. From proof of concept to full-scale production, the Prometheus journey is typically linked to the Kubernetes journey.

During the early stages of a project’s development, while a new Kubernetes cluster is being set up, scaling with prometheus is often deployed alongside it. Some applications may be deployed before it is realized that the old host-based toolkit is inadequate for gaining visibility into the cluster. Prometheus is the first search result you find after conducting extensive study.

Once the server, some simple exporters, and Grafana have been set up, you will have access to metrics and will be able to begin creating dashboards and alerts. Then, as you explore Prometheus, you find several excellent capabilities:

  • Facilitating setup through service discovery.
  • Hundreds more open-source exporters created by users.
  • Library instrumentation for gathering arbitrary application metrics.
  • It is free and accessible to the public, and it is the second project to graduate from the CNCF following Kubernetes.
  • Kubernetes is already instrumented and exposes Prometheus metrics in all of its services.

Everything seems fine at the moment. Your apps will scale effortlessly, and you’ll have a wealth of monitoring data at your fingertips thanks to Kubernetes and its slick control panel. You’re prepared to move forward.

Let’s Go To Making Things Now

You’ve got a second Kubernetes cluster up and running, and it’s just like the first one you use the same procedure to roll out Prometheus, exporters, and Grafana. The staging cluster is typically larger than the development cluster, yet Prometheus handles it with ease. Since the number of programs, dashboards, and users is modest, making a switch is straightforward.

The first minor issue crops up. Since development and staging use different instances of Grafana, you now have to toggle between the two to compare data. Developers aren’t overly concerned right now, but they are starting to feel an itch. All systems are go for release into production.

Now you have it. This is your third set. Prometheus, exporters, and Grafana should be deployed, and the dashboards and users should be migrated, just like before. The addition of a third dashboard site is not well received by users, but it is not a deal breaker.

The positive outcomes prompted further application migration to Kubernetes inside the company. Each cluster must be individually updated with new users, configurations, dashboards, and alarms. Consistent configuration management requires a greater investment of time and planning.

Preserving a Presence Abroad

No worldwide visibility is possible. This would be a new necessity if many production clusters were to be established. Sometimes it’s hard work to get things done. As a result, this strategy may make governance and regulatory compliance more difficult. A centralized visualization tool not only facilitates access to many clusters, but also permits the visualization and correlation of data from services distributed across numerous clusters inside a single dashboard.

Conclusion

Prometheus has been a game changer in the monitoring landscape for cloud-native apps, like Kubernetes has been to container orchestration. DIY Prometheus scaling, however, is difficult enough that even the largest IT organizations are wary of trying it. If you have to allocate resources to keeping this method up and running, that’s one fewer developer working on game-changing code for your company.