Managing Kubernetes Cluster

Understand how to handle Kubernetes resource management.

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Operating and managing a Kubernetes cluster involves resource management. This aids in the optimal performance of applications. It’s necessary to take this into consideration because doing so helps us maximize our cluster and avoid downtimes while our application is running.

Resource management

Resource planning and capacity management in Kubernetes involves determining the resource requirements of our applications, appropriately sizing the cluster, and efficiently managing resources to meet performance and scalability demands.

  1. Resource requirements analysis: Before deploying applications to the cluster, it’s crucial to analyze the resource requirements of each application. This analysis helps us determine how much CPU, memory, and storage each application needs to run optimally.

  2. Estimate cluster resources: Once we have the resource requirements for all applications, we estimate the total resources needed to run them concurrently. This estimation helps us size the cluster appropriately. We consider factors like application growth, expected traffic spikes, and the number of replicas for each application.

We demonstrate resource planning and capacity management by deploying two applications with different resource requirements. We use the following appA.yaml file for that:

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