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This article will explain in detail what are the nine ways to optimize the cost of Kubernetes. The content of the article is of high quality, so the editor will share it with you for reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

Kubernetes dominates the container market. According to a survey by CNCF, the utilization rate of Kubernetes in the production environment will be 93% by 2020, up from 78% in 2019.

Due to the adoption of Kubernetes by the DevOps team, and encouraged by the open source community, this number is likely to grow, and if maintained at current costs, there will be an increase in networking, storage, monitoring, and other costs.

Running Kubernetes can be very expensive, especially when organizations use Kubernetes for the first time, they usually use unoptimized architectures and settings, which will slowly increase the organization's network, storage, monitoring, and other costs. In order to save a lot of unnecessary costs, we need to form good habits from the beginning.

In this article, we will introduce nine ways to control and reduce the cost of Kubernetes.

1. Kubernetes cost monitoring

Cost monitoring: should show you the expenses related to Kubernetes. This is the most logical step to effectively manage Kubernetes costs.

Cloud providers provide billing information, but they are usually just a simple overview, which, while useful for multi-tenant Kubernetes clusters, is not accessible in the private cloud. Therefore, we need to use external software to monitor Kubernetes usage. Prometheus,Kubecost,Microtica and Replex are some useful tools in this field.

Choose the tools you will use and how to monitor Kubernetes costs. Then, implement more specific measures for Kubernetes cost optimization.

two。 Restrict resources

Effective resource constraints can ensure that the use of resources in the Kubernetes system will not exceed the cost budget.

The resources used by the container cannot exceed the resource limit you set. When a process in the container attempts to use memory beyond the allowed range, the system kernel aborts the process due to an out-of-memory (OOM) error.

Limiting resources is critical, especially when many developers have direct access to Kubernetes. They ensure the fair sharing of available resources, thereby reducing the size of the entire cluster. If there is no limit, one person may consume all resources, which will affect the normal work of others, resulting in the overall need for more computing resources.

However, please be careful not to limit your resources indefinitely. If the resource limit is too low, engineers and software will not function properly. Some Kubernetes cost optimization tools, such as Prometheus and Kubecost, can help you balance your resources.

For more information about limiting container resources, check the Kubernetes documentation.

3. Automatic expansion and contraction

Automatic extension means paying for what you need. You can allow Kubernetes to automatically scale to accommodate rapid changes.

Horizontal and vertical automatic expansion and contraction are two available types of automatic expansion and contraction. In short, horizontal automatic scaling involves adding and removing Pod based on whether the load is above or below a specified level. The proportion of each Pod is balanced with the vertical automatic expansion and contraction ratio.

Both automatic expansion and contraction methods can use computing power to dynamically adapt to your actual needs. However, this approach is not necessarily ideal because it does not apply to all use cases.

4. Select the appropriate instance

For example: the cost of AWS Kubernetes is directly affected by managing AWS instances. Instances appear in many different forms and have different combinations of memory and computing resources. Although Kubernetes Pod is used in the same way, the resource allocation is different. The key to controlling AWS Kubernetes costs is to ensure that Pod increases or decreases effectively on your AWS instance. The AWS instance should match the size of your pod.

The size, number, and historical resource utilization trends of Pod all play a role in determining which AWS instance to use. Applications may have different storage or CPU requirements, which can affect the type of instance to be used.

Ensuring that Kubernetes Pod's resource consumption is associated with CPU and memory consumption on the AWS instances it uses is critical to optimizing resource usage and reducing AWS costs.

You can check the Amazon EC2 instance type here and choose the one that best suits your needs.

Using Spot instances in 5.AWS

Currently, there are three forms of AWS instances: on-demand instances, reserved instances and Spot instances. On-demand instances have the highest cost but the highest flexibility. Compared with the price of on-demand instances, you can enjoy a discount of up to 90% when using Spot instances. You can also get reserved instances within a certain period of time to save costs. Therefore, the choice of instance form directly affects the cost of running Kubernetes on AWS.

You can use Spot instances for a variety of stateless, fault-tolerant, or flexible applications such as big data, containerized workloads, CI/CD, Web servers, high-performance computing (HPC), and test and development workloads.

6. Set a sleep schedule

Whether you are running a Kubernetes cluster on an on-demand instance, a retained instance, or a Spot instance, ensuring that the cluster is fully utilized is critical to cost management. You can calculate the cost of AWS EC2 according to the time period in which they are configured.

In short, if the development team uses a cloud-based Kubernetes environment, they only use it during business hours. If they work 40 hours a week and the environment is still working the rest of the time, there is no need to pay for the remaining 128 hours when they are not in use. Of course, this is not the case for every team, especially if their working hours are flexible, but shutting down the environment when no one is working can greatly improve Kubernetes cost optimization.

Developers can do this by automatically setting sleep schedules and waking up the environment only when needed. Setting this plan means that the system will automatically reduce unused resources. This ensures that environmental conditions are preserved. In addition, when the engineer needs it again, the environment will easily and automatically "wake up", which means that the workflow will not be interrupted.

7. Regular Kubernetes cleanup

If you give engineers the right to build namespaces on demand, or to build CI/CD pipelines, you may end up with many unused objects or clusters, but these still cost money. Even if your sleep mode can reduce the consumption of computing resources, it only applies to resources that are temporarily inactive.

Therefore, when you find that some resources have been inactive for a long time, it will be wise to delete them.

8. Determine the size of your Kubernetes cluster

The method of managing Kubernetes clusters is also different in different situations. As a programmer, you need to often think about the specifications of the applications that will run on the cluster before building the cluster.

When designing scalable applications, it is important to resize nodes correctly. A large number of small nodes and a small number of large nodes are two distinct things. The best way is to find the right balance between the two.

However, different requirements of your application require different numbers and sizes of nodes. For more information, please refer to "techniques for resizing Kubernetes clusters" to understand the size and quantity required for various applications.

9. Tag resources

In any environment, whether it's a cloud or a locator, it's a smart idea to tag resources. In multiple test, development, and production environments, organizations should use tags to ensure that all services are controlled.

AWS provides a powerful tagging scheme that can be used to tag services that belong to Kubernetes. Effective tagging allows you to easily classify and manage unused services. By enabling these tags in the AWS Billing dashboard, you will be able to allocate costs and view the cost details of various services.

Conclusion

The first step in Kubernetes cost optimization is to monitor them. Then, to avoid overuse of computing resources, you can set limits, which will make costs easier to manage.

Determining the size of the best resources and automatic expansion also help to reduce costs. If you use AWS, you can check its lower-priced options, such as Spot instances. Ways to delete free resources, including automatic sleep scheduling and cleaning up unused Kubernetes resources. Finally, resize the container and implement resource tagging to achieve better Kubernetes cost optimization.

Nine ways to optimize the cost of Kubernetes are shared here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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