Kubernetes Cost Optimization with Magalix. We need to ensure that our system is performant and meets our internally mandated SLAs. Here are multiple factors and considerations when trying to reduce your cluster cost. Going through the whole process can bring you huge savings.
I woke up one day to see this email from our CEO in my mailbox. I knew this would happen at some point as we had not been paying attention to our infrastructure spending. The time had finally come to deal with our problem.
We need to ensure that our system is performant and meets our internally mandated SLAs. However, we also need to ensure that we are using our infrastructure efficiently and eliminate any unwarranted waste. The bottom line is just as important as the top line in any business. In a SaaS business like ours, the bottom line is mainly driven by our infrastructure spending
Running Kubernetes on the cloud isn’t expensive- we can roll out a Kubernetes cluster with an average cost of $70 per month. What drives the cost up is running worker nodes to host and run our workloads. Many considerations that contribute to the cost, but most importantly is how much your cluster is utilizing the resources you’re actually running. We discussed various techniques to improve your cluster utilization in “Kubernetes Cost Optimization 101”
In this article, we will discuss how Magalix can help you better utilize your resources and pay less to run the same cluster.
Kubernetes manages and schedules pods based on container resource specs:
Resource requests and limits are container-scoped specs, while multi-container pods define separate resource specs for each container.
Kubernetes schedules pods based on the resource request and other restrictions without impairing availability. It uses CPU and memory resource requests to schedule workloads in the right nodes, while controlling which pod can work on which node and if multiple pods can schedule together on a single node
Every node type has its own allocatable CPU and memory capacities. Assigning unneeded CPU or memory resource requests can leave you with underutilized pods on each node, which leads to underutilized nodes
In this section, we will use the Container Resource Advisor (a Magalix built-in advisor) to right-size the containers in our cluster.
This is the Cluster Dashboard in Magalix console, In the “CPU Usage Distribution” and “Memory Usage Distribution”, I can view what workloads are utilizing my cluster the most. Right-sizing these workloads can save money by eliminating wasted capacity.
Our original Kubernetes tool list was so popular that we've curated another great list of tools to help you improve your functionality with the platform.
This in-depth analysis, we take a look at how to implement some of AWS's cost management tools to keep the price down.
If you’re looking forward to using AKS in your environments, maybe for Dev/Test or Production, here are few observations from my end. It may help you to reduce costs for your AKS Cluster.
In this article, I will discuss the top five techniques we used to better utilize our Kubernetes clusters on the cloud and eliminate wasted resources, thus saving money. In the end, we were able to cut our monthly bill by more than 50%!
Reducing the number of clusters can save a lot of cost without affecting the stability of your system. Finding the right answer to this question is as not easy as having many clusters has advantages and disadvantages compared to running only one or a few clusters, as discussed in this article.