8 Steps for Effective Kubernetes Cost Optimization

The growth of containerization and especially Kubernetes in recent years has been nothing short of extraordinary. A CNCF survey points out that Kubernetes in production witnessed a robust 93% growth in 2020 compared to 2019. 

Written by TAFF Inc 12 Oct 2021

The same survey shows that containers used in production had a growth of 300% in 2020 compared to 2016. 

One of the key reasons why companies switch to the cloud is to save cost, but in some cases, businesses have seen costs going up further. A potential cause for this cost increase could be over-provisioning and improper asset allocation. 

Running Kubernetes for the first time can be expensive if the setup is not efficient. Here are 8 ways by which our engineers optimize Kubernetes to reduce costs for the business.


1. Cost Monitoring

 The first rational step in Kubernetes cost reduction is to monitor and track the usage. With monitoring, you can identify opportunities and areas where costs can be reduced or optimized. Though most of the cloud providers offer a billing and usage summary of Kubernetes that is not sufficient for in-depth monitoring. We recommend using a dedicated third-party tool developed especially for Kubernetes monitoring. 

Here are some of the tools namely Prometheus, Kubecost, Microtica, and Replex. Once you install the apt tool for your system, you should be able to monitor usage and reduce costs. 


2. Set Resource limits

 It is critical that the developers set and restrict resource usage upfront for each and every program. This will ensure proper consumption of resources and will never throw any shocks with respect to billing change. Setting resource constraints will ensure that no program of the Kubernetes can use extra processing power that might result in inflated costs. Just a word of caution, don’t be over-conservative and impose very low restrictions, this might degrade the performance of the software.


3. Autoscaling

 One of the key advantages of Kubernetes is that it offers automated scaling dynamically based on the quick variations. This type of on-demand autoscaling enables Kubernetes to adjust quickly to a sudden surge of traffic without human intervention. Kubernetes offers 2 types of autoscaling.


Horizontal autoscaling will add or remove a pod based on the load. If the load goes above the specified level, then a pod is inserted and if the load goes below the specified level, a pod is removed. The scaling of individual pods is vertical autoscaling. Both the methods can be used simultaneously, but it largely depends on the requirements. 


4. Choosing the Right Instance Type

 Whether you’re using AWS or GCP, the key thing is to choose the suitable instance type for your Kubernetes implementation. Similar to a compute engine, Kubernetes pods too come in various configurations and you need to pick the right one where you should strike a balance between the cost and resources. The instance should match the size of your pod.


5. Opt for Spot Instances 

If you’re using AWS, then for Kubernetes implementation, spot instances are a better choice than on-demand instances. Spot instances have the lowest cost and can be terminated easily. Spot instances are best suited for scenarios where you don’t need permanent resource allocation and can take interruptions. According to AWS, spot instances can reduce your cost by 90% if used efficiently. Again a note of caution, spot instances are Kubernetes is not applicable on all use cases and should be used wisely.


6. Set Sleeping Schedule

 It is highly recommended to terminate underused instances and also put to sleep those instances which run only for a specific period of time. Let’s assume a Kubernetes instance is required only during business hours and is not used after that. Considering a business works 10 hours a day and 5 days a week, the total business hours will be 50 hours. Now instead of running the instance throughout the week, you can pre-set a sleeping schedule to make them available only 50 hours a week and save around 120+ hours each week. This will result in a big cost reduction for the business. 


7. Regular Kubernetes Clean-up

 It is important to maintain a routine Kubernetes clean-up schedule for reducing the cost. When Kubernetes is used for CI/CD, it is highly likely that the Kubernetes will be left with a lot of unused objects. These clusters though unused will cost you a lot of money. Once a week or depending on your requirements, you should track unused assets and clean them up to reduce costs.


8. Tag Resources

 It is obvious that some services might go unnoticed in enterprise-level Kubernetes considering the number of environments involved like staging, test, development, etc. These resources can increase your billing and hence it is critical to tag all the resources at the time of creating them so that they are not missed over time. 


The Bottom Line: 

Cost management is often overlooked until the costs truly explode. However, even before reaching that point, more transparency and insights are helpful. Optimizing costs whenever it occurs is still one of the easiest ways to save a lot of money in the long run.

Whether it’s answering a question about why something is set up the way it is, or validating optimization opportunities, TAFF has got you covered. We have extensive experience in implementing Kubernetes and Docker in all cloud platforms like AWS, GCP, Azure, etc and we have also implemented on-premise Kubernetes. 

If you’d like to see how easy analyzing and managing your Kubernetes (and other cloud) costs can be, Schedule a free consultation today.

Written by TAFF Inc TAFF Inc is a global leader and the fastest growing next-generation IT services provider. We create customized digital solutions that help brands in transforming their vision into innovative digital experiences. With complete customer satisfaction in mind, we are extremely dedicated to developing apps that strictly meet the business requirements and catering a wide spectrum of projects.