Cost Optimization Principles
Cost optimization, for any and all workloads, is a continuous process of refinement and improvement. This section will discuss some key design principles that all solutions architects as well as cloud FinOps (which stands for financial operations) teams should keep in mind when optimizing costs for their workloads:
- Consumption-based pricing model: Unlike traditional hosting solutions that require large upfront payments, the cloud simplifies the pricing of resources based solely on their consumption. This method of pricing helps reduce the unwanted sprawl of resources and helps teams design more optimal solutions that can scale in and out based on specific requirements. A typical example of this would be dev and test workloads that do not need to run 24×7. Such workloads can easily be spun up in the cloud, utilized, and then terminated once the tasks are over.
- Setting up FinOps CoEs: FinOps is all buzz nowadays in most organizations, and it should be as well, considering the fact that it aims to bridge the gap between IT operational and financial teams within an enterprise. Setting up FinOps CoEs (meaning financial operations centers of excellence) enforces collaboration and a sense of shared responsibility between teams when it comes to IT resources and costs to procure, run, and manage them. The primary goal of such CoEs is to promote cost optimization best practices, define controls, and implement cost awareness across the organization, as well as enforce guardrails for cost monitoring and management.
- Attribute expenses with owners: A FinOps CoE can define, as well as put in place, controls to monitor cost expenditure across the cloud by attributing each resource to a particular team, project, or user. This not only ensures ownership of the resources but also provides a better understanding and awareness of where costs are actually spent, and how they can be optimized in the future.
- Continuous measurement and monitoring: As mentioned at the beginning of this chapter, cost optimization is not a one-stop process but rather a continuous operation that involves constant measurement and monitoring of resources and usage patterns. Analyzing these metrics proactively on a regular basis ensures that individual workloads are constantly optimized by either redesigning applications to leverage more cloud-native services or modifying the underlying resources of an application, such as CPU, memory, storage, and so on, based on actual utilization patterns.
- Adopting cloud native: A key design principle of cost optimization is to look for opportunities to leverage as many cloud-native services as possible. Why is this so important? Well, in most traditional scenarios, the majority of the costs required to run an application sprout from operational teams that are required to manage and maintain the underlying hardware, ensure its uptime, monitor it, and patch it, all manually. Cloud storage takes over the responsibility of such operational tasks from your IT teams, so they can focus on what is important from a business perspective, such as creating and rolling out new application functionalities and so on, without having to manage any of the underlying, undifferentiated tasks of maintaining infrastructure, such as server maintenance and patching or storage management. This can only be made possible if applications and workloads are constantly monitored and optimized to leverage as much of the cloud’s native services as possible.
Having explored the key cost optimization principles, you are now ready to examine some of the mechanisms using which you can implement cost governance across your organization, starting with tagging.
