First, Kubernetes (K8s) is a very exciting tool. As a state-of-the-art container orchestration system, it completely transforms application management. It’s seamlessly scalable to applications of any size, prioritizes security with built-in features like RBAC, and is easy to use through tools like GCP’s Kubernetes engine.
In short, what’s not to love?
Now, Fee,The first one. If you’re not careful and deploy Kubernetes in production without proper consideration, you could end up paying a hefty bill.No one likes large banknotes [citation needed] So people can be nervous about K8 (and, you know, cloud computing in general).
But don’t let that discourage you. Kubernetes can give you and your organization a competitive edge and help future-proof your development process. Also, price is not an unsolvable problem. As long as you understand the costs associated with Kubernetes and take steps to proactively reduce them, you can make the most out of this powerful container orchestration system, widely adopted by industry giants like Google, Netflix, and Spotify. It can be used to a limited extent.
This article describes six ways to avoid expensive Kubernetes clusters.
If you want to learn more about Kubernetes in general, check out Nigel Poulton’s article, “What is Kubernetes and why should I learn it?”
Why is Kubernetes expensive?
Kubernetes is free and open source, so there are no licensing costs. However, running Kubernetes is expensive. This can be thought of as follows.
- Number of nodes in the cluster
- Type and size of storage used
- Amount of traffic handled
- Underlying infrastructure costs
All of this adds up. Another problem is that costs are difficult to predict. Kubernetes is an orchestrator, so you can scale up or down your compute usage on demand. This can make the cost of running Kubernetes a little harder to predict, especially in public clouds where you deal with virtual server options and pricing regulations.
How to build cost-effective Kubernetes clusters in the cloud
Now that we’ve talked about why K8s are expensive, let’s talk about how to make them less expensive. By implementing the following strategies, you can optimize your Kubernetes deployment and achieve significant cost savings without sacrificing performance.
1. Choose a managed Kubernetes service
Choosing a managed K8s service reduces the burden of infrastructure management, leading to significant cost savings. Honestly, how about making it someone else’s problem?
If you require persistent storage, you may also benefit from using managed Kubernetes services, which provide cost-effective storage options.
2. Scale your cluster on demand
Dynamically scaling your cluster based on actual demand ensures resource utilization matches your actual requirements.
3. Get the most out of Spot Instances
By leveraging Spot Instances, which offer unused EC2, GCE instances, or Azure virtual machines at discounted prices, you can significantly reduce the cost of your underlying infrastructure.
4. Use cost optimization tools
Kubernetes provides a number of cost optimization tools that allow you to effectively fine-tune your costs. The most popular tools are:
Cube cost: This cloud cost optimization tool provides real-time insights into the costs and utilization of your Kubernetes clusters and helps you identify opportunities to optimize resource usage and save money.
Cloud Zero: CloudZero, a specialized cloud cost intelligence platform, excels in monitoring and optimizing Kubernetes costs. Its robust feature set includes cost visualization, Kubernetes cost analysis, and optimization recommendations.
Customization: KusTOMize is a Kubernetes configuration management tool that allows you to create and manage multiple Kubernetes configurations. This flexibility can prove useful for cost control by allowing different configurations for separate environments such as development, staging, and production.
Argo CD: ArgoCD, which automates application deployment and management, serves as a continuous delivery tool for Kubernetes. Eliminating the need for manual deployment reduces costs and streamlines the deployment process.
Reported by: Powering progressive delivery for Kubernetes, Flagger helps you deploy and manage changes to your applications in stages, minimizing the risk of unexpected changes causing performance or cost issues.
These tools are simply fraction List of cost optimization solutions available for Kubernetes. You can also use your cloud service provider’s monitoring and cost optimization tools.
Even if you had unlimited money (which is unlikely), these cost optimization tools give you visibility into the resources and configurations that impact service reliability and availability.
5. Make sure you are using the correct instance type for your job
Kubernetes offers a variety of instance types, each with their own advantages and disadvantages. Common options include:
- Generic instance type: They balance CPU, memory, and storage and are suitable for workloads without specific requirements.
- Compute-optimized instance types: They increase CPU power and are a great choice for demanding workloads.
- Memory-optimized instance type: These address memory-intensive workloads.
- Storage-optimized instance type: These are excellent for scenarios where sufficient storage space is essential.
6. Select the appropriate number of notes for your cluster
The number of nodes you need depends on the number of pods and their resource needs. Note that cluster scalability is flexible and nodes can be added or removed based on performance and cost considerations.
This dynamic approach ensures that your applications run smoothly and efficiently within your Kubernetes environment. By following these guidelines, you can confidently choose the right instance type for your Kubernetes cluster, promoting optimal application performance and resource utilization.
Want to try out Kubernetes clustering safely?
If you want to practice deploying Kubernetes on popular cloud providers like AWS, Azure, and GCP without worrying about cost, check out my course, Hands-on Kubernetes Clustering for Cloud. In this hands-on lab, you will learn how to deploy an app and test high availability features on your cluster.
