Author: Sreekanth Iyer

In the first two parts of this series, we understood the importance of cost models and how to create and refine cost models. In the subsequent parts, we learned how to optimize our workload components across infrastructure, applications, and data. In this final part, we will present the impact and results related to applying the cost optimization and ShiftLeft FinOps techniques for a cloud-native application. We will use the sample application or workload introduced in the initial post.  

Reference (Part 1 of this series): The Workload

In the previous parts of this series, you learned the techniques to optimize the cost for Infrastructure and Application components. In this part, we will look at the ways to review the design and optimize the cost for components in your data layer.

  Key architecture components for a cloud-deployed workload.

Now that we have understood the importance of cost models and how to create and refine cost models, it's time to start to optimize our workload components. Any workload deployment and architecture contains the key components that are depicted in the architecture diagram given below. All the layers of the architecture provide opportunities for cost optimization. In this post, we will look at cost optimization techniques for infrastructure (layer highlighted in blue).

Key architecture components for a cloud-deployed workload 

In Part 1, we looked at the overview of FinOps as an evolving practice to deliver maximum value from investments in the cloud.  We also discussed the challenge or the need for shifting left FinOps for better optimization of your cloud usage and cost. In part 2 of the series, we will walk you through the steps on how you go about creating the FinOps cost model for an example solution.

There are 3 steps to creating and implementing the cost model: