Book Image

AWS FinOps Simplified

By : Peter Chung
Book Image

AWS FinOps Simplified

By: Peter Chung

Overview of this book

Much like how DevOps is a combination of cultural philosophies, practices, and tools that advocate a collaborative working relationship between development and IT operations, FinOps encourages the same collaboration between technology and finance team, making it key relationship to establish and maintain for any thriving business. This book will help you understand how organizations with a mature FinOps practice can decentralize cost ownership to developer teams and encourage cross-functional collaboration between business, finance, and technology, enabling speed, innovation, and business growth. You’ll focus on structuring your organization to form the right FinOps team, including a Cloud Center of Excellence, and learn how to implement practical cost savings measures with AWS tools to optimize costs in both the short as well as long term. By the end of this cloud FinOps book, you’ll be ready to implement a successful Cloud FinOps practice for your organization to get the best value from the AWS cloud for your workloads.
Table of Contents (18 chapters)
Free Chapter
2
Part 1: Managing Your AWS Inventory
7
Part 2: Optimizing Your AWS Resources
12
Part 3: Operationalizing FinOps

Summary

In this chapter, we unpacked the different manifestations of data transfer on AWS. We learned about the data transfer flow within an AZ, within a Region, across AZs, and across Regions. We also looked at hybrid architectures and the implications they have for data transfer.

We used Cost Explorer to understand and visualize our data transfer costs. Tools such as Cost Explorer can help interpret the sometimes mysterious data transfer charges by identifying where these charges occur. We also mentioned how VPC Flow Logs can uncover the why behind data transfer through the logs it provides.

Lastly, we saw how AWS services such as CloudFront and load balancers can minimize data transfer charges. Application architecture can also minimize data transfer charges by prioritizing network communication within an AZ.

We’ll conclude our discussion on cost optimization tactics in the next chapter, in which we’ll explore ways to optimize the machine learning and analytics...