Kubernetes can be an invaluable tool for your business operation. Kubernetes can seem tricky to get running at peak performance, but if you use some strategies, you can do it. Most Kubernetes deployments aren’t performance-optimized out of the box, and if they were, chances are they wouldn’t be adjusted in a way that works best for your setup.
Whether you are just beginning to design your cluster or have an operational production system, the strategies explained in this article will help you enhance Kubernetes performance.
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Add resources to the existing worker nodes before creating new worker nodes.
Increasing the number of worker nodes improves availability and resources for better Kubernetes performance. However, it is more economical to optimize current nodes with additional RAM and CPU than to add new nodes.
This method lessens the strain on components such as the scheduler and kube-proxy and decreases the overhead from the host operating system.
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Use multiple master nodes.
In a Kubernetes cluster, using several masters is mostly done for high availability. The likelihood that a master will fail and bring down your cluster decreases with the number of masters you have.
Adding more masters has its advantages in terms of performance. It gives extra hosting resources to important parts of Kubernetes, such as the scheduler, API server, and Etcd, which are all hosted on the masters. These components will be powered by Kubernetes using the combined resources of all master nodes.
Set worker node scoring limits
The Kubernetes scheduler’s role includes “scoring” the worker nodes, i.e., figuring out which of them can manage a given workload. When there are several dozen or more worker nodes in a cluster, the scheduler may find itself wasting time verifying each worker node.
You can specify a percentage less than 100 for the percentageOfNodesToScore argument to prevent this inefficiency. Then, the scheduler will only look at the percentage of nodes you choose.
Set resource quotas
Resource quotas place restrictions on how much memory, CPU, and storage a specific namespace is allowed to use.
To guarantee that every task receives an equal share of resources, you can partition your cluster into namespaces, assign a namespace to each team, and establish resource quotas for each namespace.
In essence, resource quotas address the noisy-neighbor problem rather than improving performance. You can learn job-ready Kubernetes techniques if you enrol in online Kubernetes courses.
Set limit ranges
How can you restrict the amount of resources used by a workload that shares a namespace with other workloads? You can do it by limiting ranges.
Resource quotas place restrictions on the amount of resources that each namespace is allowed to use. Limit ranges, on the other hand, apply the same restrictions per pod or per container.
In most cases, dividing up tasks using namespaces and resource quotas is a best practice for simplicity’s sake. However, limit ranges will let you make sure that each pod or container has the resources it needs to operate as intended in cases where that strategy is impractical.
Set up endpoint slices.
With Endpoint Slices, a little-known Kubernetes feature, you can organize network endpoints according to port and service combinations. Kube-proxy makes reference to them when determining the traffic routing configuration.
Endpoint Slices can boost performance in setups with many endpoints by reducing the tasks that kube-proxy needs to do in order to manage traffic within the cluster.
Use a minimalistic host OS
Finally, make sure that a minimalistic operating system is used to host your Kubernetes clusters. The performance of your cluster is lowered by any additional components that aren’t absolutely required to run Kubernetes because they waste resources.
You can guarantee optimized performance if you follow these Kubernetes strategies, but you can learn even more techniques and concepts if you enrol in online Kubernetes training courses. The best kubernetes training also gives you a competitive edge when it comes to job interviews.