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Why is monitoring Kubernetes hard?

Kubernetes has taken the container ecosystem by a storm and for a good reason too. Kubernetes acts as the brain for the distribution of distributed containers. It is designed to manage service-oriented applications using containers distributed across the host cluster.

Kubernetes provides a mechanism for the spread of applications, scheduling, updates, service discoveries, and scales. You can know about useful kubernetes monitoring tools from various online sources.

While Kubernetes has the potential to dramatically simplify the spread of your application in the container – and throughout the cloud – it also adds a series of new complexity to your daily tasks, manage application performance, get visibility to service, and your typical monitoring -> warning – > Troubleshooting workflow.

1) Kubernetes increases infrastructure complexity

The coating of the complexity of new infrastructure appears in the hopes of simplifying the application of applications: Dynamic provision through IAAS, automatic configuration with configuration management tools, and lately, the orchestration platform such as Kubernetes, which sit between naked metals or your virtual infrastructure and services that empower the application. This is why monitor Kubernete's health in the control field is part of work.

5 Top & Useful Kubernetes Monitoring Tools

2) Microservices Architecture

In addition to increasing infrastructure complexity, new applications are being designed for microbead services, where the number of components that communicate with each other has increased in the order of magnitude. Each service can be distributed in various examples, and the container moves across your infrastructure as needed. This is why monitoring the state of the Kubernetes orchestration is the key to understanding whether Kubernetes does its work.

3) Blast requirements and the original cloud scale

While we adopt the original cloud architecture, the changes they carry to increase the number of smaller components. How does this affect Kubernetes monitoring methodology and tools? As explained on the engineering of site reliability – how Google runs a production system, "We need a monitoring system that allows us to warn for high-level service purposes, but maintain granularity to check individual components as needed."