As spending on the public cloud is increasing globally, companies are looking for ways to reduce cost and increase efficiency. Financial Operations, or FinOps, is similar to DevOps, which enables companies to accelerate technology delivery. FinOps is a new operating model that maximizes the value of an organization's cloud investment.
In this course, you are going to learn about FinOps Principles and how to build FinOps Teams, as well as the three phases of the FinOps Lifecycle. Specifically, you will learn how to apply FinOps processes and practices to reduce rates and avoid unnecessary cloud costs.
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Learning Objectives
- Understand what makes the cloud so powerful and why it is changing how businesses operate
- Understand what makes cloud challenging from a technology, management, and financial perspective
- Learn about the six FinOps Principles and how to build successful FinOps Teams
- Learn about FinOps capabilities and how to build a common language within your organization
- Learn about the anatomy of a cloud bill and how to take advantage of the Basic Cloud Equation
- Learn about the three phases of the FinOps Lifecycle and how to build successful processes and practices to reduce rates and avoid cost
Intended Audience
This course is for engineers, operations, and Finance people looking to understand how to improve efficiency and reduce cost in the cloud.
Prerequisites
to get the most out of this course, you should have a foundational understanding of cloud concepts, specifically how compute and storage are provisioned and billed in the cloud. Some familiarity with rate reduction and cost avoidance methods in the cloud would also be helpful but are not essential.
References
The FinOps Lifecycle section of this course references materials from:
The Anatomy of a Cloud Bill lecture references materials from:
- Cloud FinOps: Collaborative, Real-Time Cloud Financial Management, O'Reilly Media; 1st edition (January 7, 2020)
Even medium-size businesses will have tens of millions of rows in their cloud bill and cloud vendors typically have millions of stock-keeping units or SKUs. For example, Amazon Web Services Elastic Compute Cloud has over four million SKUs, and that is just for one out of over 175 cloud services they offer.
This goes beyond the capabilities of keeping track of cloud spend in spreadsheets. We will need to leverage tools and automation as much as possible. Fortunately, cloud vendors provide many billing attributes we can leverage to identify the dimensions of cost like the service, the account or project, the region, the usage type, and many more.
Unfortunately in my experience, it is not enough to rely only on the cloud vendor data. We will need to build a tagging taxonomy to map the cloud spend to the business. Common cost allocation tags are the business unit, the application or service, the environment, and the engineering team or owner.
The basic cloud equation is Usage times Rate equals Cost. The usage can be a duration in time or a quantity of usage while the rate is a financial number in the local currency. For example, one hour of m5.large AWS EC2 general-purpose compute cost 9.6 cents at the time this was recorded.
Earlier I explained that Rate Reduction and Cost Avoidance are the primary tools FinOps uses to reduce cloud spend. In the example above we can reduce the rate by buying a Reserved Instance or we can avoid cost by using the EC2 instance for less than one hour.
To summarize the Anatomy of a Cloud Bill: To view cloud spend we will need to use tools other than spreadsheets. To allocate cloud spend to the business we will need to use a combination of vendor-provided billing attributes and customer-defined tags. Cloud spend follows the formula Usage times Rate equals Cost which allows us to apply Rate Reduction and Cost Avoidance methods to reduce spend.
Please note: this lecture references materials from:
- Cloud FinOps: Collaborative, Real-Time Cloud Financial Management, O'Reilly Media; 1st edition (January 7, 2020)
Dieter Matzion is a member of Intuit’s Technology Finance team supporting the AWS cost optimization program.
Most recently, Dieter was part of Netflix’s AWS capacity team, where he helped develop Netflix’s rhythm and active management of AWS including cluster management and moving workloads to different instance families.
Prior to Netflix, Dieter spent two years at Google working on the Google Cloud offering focused on capacity planning and resource provisioning. At Google he developed demand-planning models and automation tools for capacity management.
Prior to that, Dieter spent seven years at PayPal in different roles ranging from managing databases, network operations, and batch operations, supporting all systems and processes for the corporate functions at a daily volume of $1.2B.
A native of Germany, Dieter has an M.S. in computer science. When not at work, he prioritizes spending time with family and enjoying the outdoors: hiking, camping, horseback riding, and cave exploration.