Nagios is an open-source monitoring system used to track the performance and health of IT infrastructure, including servers, network devices, applications, and services. It is widely used because of its ability to provide real-time alerts, identify issues before they become critical, and ensure uptime by detecting and addressing system failures promptly. Monitoring Nagios plugins on a more robust platform allows for better scalability, deeper analytics, and long-term storage of performance data.

In this article, we'll explore another monitoring use case. This particular use case is exciting– it's MetricFire's use case with Kubernetes and Linode! We'll examine how our company uses our platform to monitor our K8s clusters hosted on Linode. Let's get started!

Prometheus and its querying language, PromQL, have several functions that perform various calculations on their data. One of the most widely used functions is rate(); however, it is also one of the most misunderstood.

Monitoring is the most important aspect of infrastructure operations. Effective monitoring strategies help optimize infrastructure usage, improve planning, and resolve incidents quickly. While monitoring preceded DevOps, DevOps has further transformed the software development process to the extent that monitoring also has to evolve.

In this article, we will be looking into Kubernetes monitoring with Graphite and Grafana. Specifically, we will look at how your whole Kubernetes set-up can be centrally monitored through Hosted Graphite and Hosted Grafana dashboards. This will allow Kubernetes Administrators to centrally manage all of their Kubernetes clusters without setting up any additional infrastructure for monitoring.

Monitoring is the most important aspect of infrastructure operations. Effective monitoring strategies help optimize infrastructure usage, improve planning, and resolve incidents easily. While monitoring preceded DevOps, DevOps has further transformed the software development process to the extent that monitoring has to evolve as well.

The growing adoption of microservices architecture also drives the adoption of containers to package, distribute and run the microservices. This requires orchestrators to handle the availability, performance, and deployments of those containers on the server. However, the entire setup around microservices, containerization, and orchestrators complicates logging and monitoring since various distributed and diversified applications interact with each other.

Kubernetes is now the industry standard for cloud-based organizations. Slowly, many enterprises and mid-level companies are adopting it as the default platform for managing their applications. But we all know Kubernetes adoption has its challenges, as well as its associated costs. How do we decide when and what to migrate to Kubernetes? Does migrating to Kubernetes mean overhauling all DevOps processes? Adopting K8S should not lead to an overhaul of your DevOps process - it should complement it.