FinOps : RoadMap to Cloud Efficiency: Mentoring Cloud and Finance Professionals to Drive Cloud Productivity

by Amit Aggarwal, Navin Sabharwal, Piyush Pandey

Length: 220 pages
Edition: 1
Language: English
Publisher: BPB Publications
Publication Date: 2022-10-21
ISBN-10: 9355512635
ISBN-13: 9789355512635
Sales Rank: #0 (See Top 100 Books)

0 ratings

Print Book Look Inside

Accelerate Business Value Realization and Drive Financial Accountability for Cloud Infrastructure

Key Features

In-depth knowledge of establishing and operating the FinOps model.
A collection of use cases examining the adoption and benefits of FinOps.
Includes Cloud cost optimization solutions such as waste elimination, appropriate sizing, and purchasing strategy.

Description

FinOps is a novel cloud operating model that uses interdisciplinary teams to manage cloud expenditures in concert. With the help of the tools, best practices, and culture introduced in this book, businesses can analyze cloud expenses and make strategic decisions in a better way. The book’s ultimate objective is to teach companies how to establish a reasonable cost, speed, and quality balance in the cloud.

The book begins with an overview of why FinOps exists, the problems it solves, the principles it is based on, and how it fits into the history of financial management. The subsequent chapters of this book explain the three stages—inform, optimize, and operate—and the best methods to use in each stage. The book then explains in depth, with examples, how to maximize efficiency while minimizing expenses for each of the three major public cloud providers: Google, Amazon, and Microsoft.

The book also covers cost optimization techniques for the public cloud, FinOps operations management, cloud cost visibility, and forecasting.

What you will learn

Highlights of the evolution and demand of FinOps by prominent organizations.
Learn the ins and outs of the cloud billing system.
Utilization of regression methods to extract insights from the FinOps data.
Gain a thorough understanding of running all the FinOps processes.
Investigate and test several ways to optimize your cloud spending.
Learn about the various cloud benefits provided by Azure, AWS, and GCP.

Who this book is for

If you are a finance, DevOps, or IT professional looking to collaborate on decision-making and cost control in the overall cloud financial operations, this is the only knowledge book you need. In addition, multiple teams, including Procurement, Service Delivery, and Platform Engineering, can read this book to inspire curiosity and exploration.

Cover Page
Title Page
Copyright Page
Dedication Page
About the Authors
About the Reviewer
Acknowledgement
Preface
Errata
Table of Contents
1. Introduction to FinOps
    Introduction
    Structure
    Objectives
    Rise of Cloud Economics
    What is FinOps
    Key principles of FinOps Adoption
    Why FinOps?
    FinOps Challenges
    FinOps Stakeholders
    FinOps Adoption Phases
    FinOps Maturity Model
    FinOps Platform Capabilities
    Well Architected Framework
    Technology Ecosystem Overview
    Conclusion
2. Inform Phase of FinOps Lifecycle
    Introduction
    Structure
    Objectives
    Overviewing of Cloud computing terminologies
        Infrastructure as a Service
        Platform as a Service
        Software as a Service
    Understanding cloud bill
        AWS
        Azure
            Azure agreement types
            Amortized versus actual cost
            Azure charge types
        GCP
    Budgeting, trending, and forecasting
        Budget allocation
        Forecasting
        Trending
            Current versus budgeted
            Budgeted versus forecasted
    Tag governance
    Anomaly detection
        Setting up of thresholds for anomalies
    Conclusion
3. Optimize Phase of FinOps Lifecycle
    Introduction
    Structure
    Objectives
    Overview of Optimization strategies
        Usage Optimization
        Anomaly detection
        Spend optimization
            Spot usage
            Reserved Instances
            Sustained Use Discounts
            Offers and free trial usage
            Cost optimization approach for Disaster Recovery
            Recovery Time Objective and Recovery Point Objective
    Wastage elimination
        What is waste?
        Security implications
    Scheduling of resources
    Rightsizing
    Selecting right purchase model
    Container Cost Optimization
    Evergreening or upgrading to latest generation
    Asset management and License Optimization
    Conclusion
4. Cost Optimization Techniques for AWS
    Introduction
    Structure
    Objectives
    AWS Native Optimization Services overview
    Wastage elimination
    Scheduling service
        AWS Instance Scheduler Flow
        Right sizing based cost optimization
        Right size by instance family and size
    Reserved Instances and Savings Plan
        AWS Reserved Instances
        AWS Savings Plan
        Comparing RIs and Savings Plan
    Sustainability
    Conclusion
5. Cost Optimization Techniques for Azure
    Introduction
    Structure
    Objectives
    Azure native optimization services overview
    Wastage elimination
    Scheduling services
    Right Sizing based cost optimization
    Reserved Instance (RI) based Cost Optimization
    Sustainability
    Conclusion
6. Cost Optimization Techniques for GCP
    Introduction
    Structure
    Objectives
    GCP Native Optimization Services overview
    Wastage elimination
        Shutting down the Virtual Machines
        Deleting underlying disks
        Reduce GKE Waste
        Reduce waste in BigQuery
        Delete obsolete storage object versions
        Deleting abandoned Kubernetes clusters and nodes
    Scheduling services
    Right Sizing based cost optimization
        How Rightsizing recommendations work
        Rightsizing limitations
    Sustained and committed use discount-based cost optimization
        Committed use discounts (CUDs)
            How Committed Use Discounts work
            Commitment types
            How Committed Use Discounts are different than Reserved Instances
        Sustained Use Discounts (SUDS)
    Sustainability
    Conclusion
7. Leveraging Algorithms for Analyzing FinOps Data
    Introduction
    Structure
    Objectives
    Need for utilization cost analysis
    Supervised machine learning
    Environment setup for cloud cost analysis
        Software installation
        Launch application
    Performance analysis of models
        Mean Square Error (MSE) \ Root Mean Square Error (RMSE)
        Mean absolute error
        Mean absolute percentage error
        Root mean squared log error
        Coefficient of determination - R2 score
    Regression
        Linear regression
    Time series models
        Time series data
        Stationary Time Series
            Lag variable
            ACF & PACF
            ARIMA
            SARIMA
            Implementation of ARIMA and SARIMA
    Conclusion
8. Managing FinOps Operations
    Introduction
    Structure
    Objectives
    FinOps operations operating model overview
        Key personas in FinOps operation model
        Strategy
        Planning
        Operational Readiness
    Operations adoption, governance, and continuous improvement
    Leveraging AI-Ops for managing FinOps Operations
    Conclusion
Index