Introduction – Cost Analysis with Kubernetes Monitoring
As Kubernetes is becoming the leading container orchestration tool over the last couple of years, many companies are switching on it despite having a steep learning curve. When it comes to the cloud, many cloud providers are providing and helping small as well as big organizations to leverage the Kubernetes support. Companies are now transitioning their production environment on Kubernetes with cloud or on-premise infrastructure. The challenge they encounter firstly is that how the Kubernetes resources are allocated accurately to the different applications, services, teams, departments in the organization.
To understand why cost analysis of resources is important for an organization, let go back in the time of one to one deployments, having a single application running on a single server and the cost of that server would be effectively the cost of that application, so there is no confusion all resources are properly allocated. But as the containers came into the picture, we are getting out of this era. Multiple pods/containers are running per server which lowers the server fleet footprint, by this cost of running application improves and Kubernetes orchestrates those containers into logical blocks that maintain the level of abstraction which manages the low-level complexity such as the environment
Cost Analysis in Kubernetes
Based on the different resource category
- Compute- defines the charges for the nodes.
- Storage- defines the cost of Persistent disks and EBS volumes.
- Networking- defines external traffic charges, load balancing and so on.
And the logical components of Kubernetes cluster are categorized as:
- Admin includes API server, etcd, scheduler and everything you can find in the Kube-system namespace.
- Monitoring includes the stack of metrics- Prometheus.
- Logging- ELK stack.
- Applications- all the pods which handling the workload of the user.
- Idle- resources like CPU, memory, network.
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