Kubernetes Guide: The Stages of Optimization

Kubernetes, the leading container orchestration platform, offers flexibility and scalability for deploying applications. However, despite out-of-the box flexibility and scalability - maintaining optimal balance between performance, resiliency and cost effectiveness remains an ongoing and continuous challenge.
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To effectively and continually optimize you environment, a structured strategy is vital. It comes in three stages: Gaining Visibility, Taking Owner-led Actions, and Allowing Autonomous Rightsizing. By following this method, you'll create and maintain a finely-tuned Kubernetes setups that efficiently uses resources and saves costs.

Stage 1: Gaining Visibility

In this early stage, you're just starting to explore the landscape of resource utilization and efficiency. One thing you may find is that gaining the visibility you need is easier said than done. Especially if you are running multiple environments and your development teams continuously introduce new changes and product features.  However, I must stress that getting comprehensive visibility is extremely important, and any gaps could impact the effectiveness of later stages.
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Here are the levels of visibility you need:

• Infrastructure Cost and Utilization Data: Gather information from cloud billing data, infrastructure monitoring tools, data efficiency tools, and any insights provided by your cloud provider. These are foundational data points required for your optimization journey.
• Business Efficiency Metrics: Identify metrics that directly align with your business goals. For instance, if you're running an e-commerce platform, a relevant metric might be "transactions per second" or "revenue per user." This metric will help you gauge the impact of optimization on your business and on your customers.

Stage 2: Taking Owner-lead Actions

Now you have the data point you begin to put tangible values on the optimization efforts. You can think of this as the return on investment (ROI) of optimization.  This involves quantifying costs and measuring the impact of optimization actions:

• Quantify the Impact: In this step, you determine the costs that can be avoided by right-sizing underutilized or inefficient resources. This will help you better understand your potential savings and prioritize the actions you take based on monetary values.
  Note: You can also use these steps to evaluate under-provisioned resources, for example, maintaining 99,99% SLA is not necessarily required for the pre-production environments, so it can be okay to run them a little leaner.
• Cost of Action: Calculate the cost required to perform optimization actions. This includes evaluating the time, effort, and resources needed. For example, calculate the hours required to implement a change and the associated hourly rate. You can now subtract your cost of action from your potential savings to get a preliminary ROI on your optimization efforts. 
• Manual Review and Action: Review optimization recommendations generated either manually or by a specialized tool(s). These recommendations could range from resizing resources to adjusting storage classes, HPA or ClusterAutoscaler thresholds. Start taking the appropriate manual actions based on these suggestions, monitor the results, and compare them to your preliminary ROI projections to determine if you are driving the optimal results. 

Depending on the scope of the work needed to optimize your Kubernetes environment, manual efforts could drastically reduce your ROI, and impact other projects and initiatives your teams have.  If this is the case, you are ready for stage 3, automating the optimization process. 

Stage 3: Automated Efficiency

In this stage, continuous optimization becomes a well-oiled machine driven by data and automation. Here's how to achieve this advanced level of optimization:

• Automated Processes: Utilize cost and utilization data to automate optimization processes. Develop scripts or use specialized tools that process this data and trigger actions based on predefined thresholds.
• Automated Alerts: Implement alert mechanisms that notify you when anomalies or suboptimal conditions are detected. These alerts can prompt humans to analyze the situation or trigger automated actions.
• Automated Actions: Set up processes to automatically resize or stop/start compute resources based on real-time data. Apply tailored storage class and data efficiency changes to match workload requirements.
• Continuous Improvement: Continuously monitor and evaluate the efficiency improvements. Use the business efficiency metric defined in the Crawl phase to measure the impact of your optimizations on your business goals.

As you can see, Kubernetes optimization is a journey that progresses from the initial stage of gathering data to the advanced level of automated efficiency. By following the above stages, you'll transform your Kubernetes environment into a finely tuned system that maximizes resource utilization, minimizes costs, and aligns with your business objectives. 

It is important to note that the above stages can be complex, time-consuming, and can be subject to human error that can risk the resiliency and availability of applications. If you are looking to accelerate the optimization process, PerfectScale's Optimization and Automation Platform can take you to Stage 3 in a matter of days. Our platform continuously evaluates the efficiency of your environment and performs automated actions that ensure peak Kubernetes performance at the lowest possible cost. Additionally, our effortlessly adapts to the changing needs of your application, providing a safeguard that sustains the success of your Kubernetes journey.