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You have to efficiently use resources such as memory and storage to avoid overprovisioning, which leads to unnecessary expenses. You can use rightsizing workloads, cost-effective instances, and auto-scaling approaches to ensure you only pay for what you need. Let us look at both architectural and non-architectural best practices to optimize Kubernetes cost.
Architectural Best Practices
Reduce Nodes
Using the architectural view, the most effective way to lower Kubernetes costs is to minimize the number of nodes that run. While you can implement many other ways to achieve some improvements, real cost savings come from using fewer resources. Effective Kubernetes cluster management can help you save significant costs. You will monitor and control clusters, including creating, updating, and deleting what you don't need. The objective is to only use the nodes you need without interfering with the performance or having extra resources.
Minimize Traffic
You can minimize costs by reducing or eliminating traffic between availability zones and regions. This eliminates unnecessary data charges. In some cases, Kubernetes nodes have more than one geographical region, and this involves communication over a reasonably long distance. This can increase data charges rapidly. If possible, separate nodes or clusters into their own regions to ensure information transfer stays within one region rather than multiple regions. Although regional costs are the priority, availability zone costs should also not be overlooked. Using a single namespace for each availability cone can help you end up with a single zone namespace deployment.
Non-architectural best practices
Get Deep Visibility
Avoid being caught up in a disaster by having complete visibility of Kubernetes. One of the ways to optimize costs related to running Kubernetes is by using platforms like CloudZero to gain deeper visibility into how Kubernetes influences costs. When you understand the total cost of running the application, you can start making changes that can reduce costs. It is important for a company to access all information about Kubernetes deployment, including memory and disc usage, cost of everything, what jobs are running at any given moment, complete cost on an hourly basis, and a map of how things run on the cluster. This information can help businesses make informed decisions in order to reduce costs without impacting performance.
Measure Before and After Costs
Organizations need to consider costs as one of the operational metrics to track as part of the engineering process. Start measuring operational efficiency, performance, and uptime prior to and after a major change. For example, organizations should have service-level objectives associated with performance and availability, and they should have internal guidelines outlining the maximum cost of running an application. They should be able to measure and understand costs after application changes to know whether they should accept the changes or not.
Kubernetes can be costly, but there are ways a business can optimize those costs by reducing unnecessary costs. Understand the application deeply to know which areas cost more and how to reduce them. Asses all costs before any application changes to know if they are worth it. You should also reduce the number of nodes and minimize traffic to reduce technical costs.
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