Kubernetes is quickly becoming one of the most in-demand skills for DevOps worldwide as many enterprises look to adopt a strategy that modernizes their topology and legacy systems.

Drawing on years of production workloads at Google, Kubernetes is an ever-evolving open-source platform that is location-agnostic and scales easily. With such a vital tool at your fingertips, it can quickly become overwhelming if you and your team are looking to optimize its structure better and tailor it to your needs.

The Structure of Kubernetes

Kubernetes is an open-source container orchestration platform designed to automate containerized applications’ deployment, scaling, and management. 

Some key features of Kubernetes Include:

1. Container Orchestration: Through automation, Kubernetes can guarantee that many applications run across various environments with little manual intervention.
2. Scaling and Load Balancing: Kubernetes automatically scales applications by reviewing demand. This information is then taken and turned into an accurate network traffic distribution so you can get more performance out of it.
3. Rolling Updates and Rollbacks: The open-source platform is well known for providing mechanisms for deploying updates without any downtime, making sure that there are no business setbacks. This is done by replacing old containers with new ones and will rollback in case of significant issues.
4. Self-healing: Kubernetes automatically replaces failed containers and reschedules them to healthy nodes to maintain application availability.
5. Portability: Applications packaged as containers within Kubernetes can run on various cloud providers or even on-prem, which gives you flexibility and balance with your staff, while also providing peace of mind about possible vendor lock-in.

In short, Kubernetes provides a flexible and scalable solution for managing containerized workloads.

What Exactly are Containers?

Containers are lightweight, portable, consistent environments representing an application and its dependencies. Kubernetes does an outstanding job as a container orchestration tool, which helps you deploy, manage, and scale both on an enterprise level and maintain this level of service even when getting more granular.

A full explanation of the architecture and components of Kubernetes can be found here.

Rightsizing at the Micro (Pod) Level

The goal of rightsizing is always challenging but must be done continuously to make it more effective. Allocating your computing resources to reach an intersection of cost and performance best is not just one thing but a series of steps and regular reviews to make it truly synchronous.

Rightsizing at the pod level means optimizing allocating these resources for individual containers within Kubernetes pods.

You will know this was done correctly when each container receives the appropriate resources to run efficiently while costs are reasonable without over (or under!) provisioning.

When you’ve right-sized at the pod level, here are some benefits you can enjoy:

1. Better Resource Usage: Each container within a pod is allocated the right amount of CPU and memory resources by simply setting Requests and Limits for each individual container. This prevents containers from getting more resources than necessary, increasing costs and resource wastage.
2. Optimize Performance: Allocating resources efficiently is not just about making more with less but will improve the overall performance of containerized apps. Improved response times and reduced latency are just examples of the correct provisioning accorded to the container.
3. Save on Unnecessary Costs: Cost savings are almost guaranteed as you will be paying only for what you need. This is extremely important in a cloud environment where resource costs are based on actual consumption rather than a fixed plan.
4. Support Autoscaling Efforts: Avoid more manual work and re-work as rightsizing aligns with autoscaling strategies, allowing it to scale dynamically based on demand. You’ll want to properly rightsize so that your apps can handle varying workloads without any over-allocation during lower demand (and vice versa)
5. Customize Specifically: Rightsizing can be customized at a granular level, considering the specific resource requirements of each container. Customizing resource usage is very helpful when you have diverse workloads or are working on simultaneous projects of different urgencies.
6. Provides Continuous Benefits: Rightsizing is not a one-time task; it requires ongoing monitoring and some adjustment. Make it a habit of reassessing the resource needs of containers and making adjustments (if any) based on usage patterns and shifting priorities.

Rightsizing at the Instance Level

Rightsizing at the Instance level indeed shares some of the same benefits of pod rightsizing, but to a higher degree, given the ability to run multiple instances within a cluster. It’s always best to start off with individual nodes and containers first to confirm that they are running optimally. 

Instances form the underlying infrastructure of a cluster, which makes it a scalable way to allocate resources. Instance types can be broken down into worker and master nodes, each tasked with carrying out a different service. Worker nodes execute tasks assigned by the control plane to manage scaling and deployment. 

Master nodes allow a specialized instance that manages cluster states. Global decisions are made possible to schedule and detect failures, making it possible to optimize at scale.

Here are some specific advantages you can enjoy by rightsizing instances:

1. Efficient Infrastructure: When you confirm that each instance is allocated the appropriate amount of CPU and memory resources, this prevents over-provisioning, optimizing resource utilization across the entire Kubernetes environment – not just at a micro level.
2. Optimize Node Performance: Rightsizing at the instance level contributes to the overall performance of the Kubernetes cluster. Allocating resources prevents instances from being overwhelmed (or identifying when they are underused/idle), leading to improved response times and reduced latency for containerized applications.
3. Save on Unnecessary Costs At Scale: With rightsizing, you pay only for the resources you need. Each instance has its own compute resources, including CPU, memory, and storage—the benefits scale with the rightsizing efforts, which reduces costs effectively.
4. Supports Your Autoscaling Efforts: Rightsizing instances have a profound effect when looking at them on a macro level. Kubernetes clusters can scale horizontally by adding or removing instances to handle varying workloads. You can also scale vertically by adjusting resources as needed instead.
5. Customize Specifically: Instances are provisioned during the setup of a Kubernetes cluster, and their number can be adjusted up and down as needed. They can also be removed entirely when there are periods of low demand. This level of customization is great for managing diverse workloads or concurrent projects with different urgency levels. 

The Verdict? Do Both!

Ultimately, rightsizing at both levels is important to allocating the proper costs and resources to your workloads, apps, and environments to ensure a balance between running effectively and being efficient with your budget.

Starting with appropriate resource requests is one of the fundamental ways of understanding your usage of Kubernetes pods and clusters and developing a strategy over time.

Kubernetes is a powerful tool but needs to be used to its fullest potential to maximize the positive impact on your department, teams, and organization. 

The traditional approach towards rightsizing is challenging and time-consuming. It requires manual analysis and human intervention and does not leave room for automation support.

Improve Kubernetes Performance at Scale

Seek opportunities to rightsize pod resources effectively, at scale, with Intel Tiber App-Level Optimization. Through AI-driven automation, real-time adaptation, intelligent insights and smooth deployment, you can be sure you are receiving the best possible guidance for your unique situation. 

An auto-pilot functionality has recently been enabled for the Intel Tiber App-Level Optimization Capacity Optimization solution. This enhancement for Kubernetes users across all environments revolutionizes how DevOps professionals optimize their workloads and effortlessly eliminates over-provisioning by intelligently rightsizing workloads and ensuring cost-effective resource utilization.

Users can tap into a new level of performance optimization, combining autonomous runtime enhancements with Kubernetes rightsizing. The solution also offers full visibility of cluster resource utilization and the ability to tailor settings to your application’s needs, either per cluster or label, to discover key opportunities for CPU, memory, and cost reductions.