Sustainable Cloud Development : Optimize cloud workloads for environmental impact in the GenAI era

Reduce cloud costs and carbon footprint with sustainable design, GenAI, and green architecture principles

Key Features

• Discover sustainable cloud practices, including carbon footprint analysis, optimization, and security
• Explore best practices, insights, and case studies for implementing sustainable solutions like generative AI workloads
• Learn cost-saving strategies through efficient resource use and business alignment
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Written by three seasoned AWS solution architects, sustainability mentors, and thought leaders, Sustainable Cloud Development equips cloud professionals with actionable strategies to design, build, and optimize workloads that minimize environmental impact, while maintaining performance and scalability.

This book combines practical insights, best practices, and case studies to help you align your cloud operations with global sustainability goals. From foundational concepts such as carbon footprint measurement to advanced techniques such as sustainable software architecture, generative AI lifecycle optimization, and cost-efficient cloud practices, this book covers every aspect of sustainable cloud development. You’ll get to grips with key tools, including AWS Cost Explorer, for analyzing costs and usage over time to right-size deployments; auto scaling for automatically scaling compute resources dynamically based on demand; Amazon Trusted Advisor for reviewing optimization recommendations across critical areas such as cost, performance, and security; and Amazon CloudWatch for detailed monitoring and threshold-based alerting around all resources and applications.

This book serves as a practical blueprint for optimizing your cloud workloads for both high performance and a minimal environmental footprint.

What you will learn

• Explore the principles of sustainable cloud computing and application performance analysis
• Discover best practices for data lifecycle management, storage optimization, and networking efficiency
• Understand and analyze the carbon footprint of cloud applications
• Implement sustainable software architecture and coding patterns
• Optimize the lifecycle and consumption of generative AI models
• Align cloud services with sustainability goals and global regulations
• Explore eco-friendly generative AI practices, including efficient model deployment

Who this book is for

This book is for cloud architects, engineers, DevOps professionals, and IT sustainability specialists who want to align their cloud practices with environmental goals. It also caters to software developers eager to build green, efficient solutions. A basic understanding of cloud services and IT infrastructure is necessary.

Table of Contents

1. Foundations of Sustainable Cloud Computing and Carbon Footprint Analysis
2. Energy and Compute Efficiency in Cloud Infrastructure
3. Sustainable Data Management and Storage Optimization
4. Network Optimization for Sustainability
5. Security, Observability, and Monitoring in Sustainable Cloud Development
6. Sustainable Software Architecture and Design Patterns
7. Sustainable DevOps and CI/CD Practices
8. Sustainable DevOps, Container, and CI/CD Practices
9. Cost Optimization through Sustainable Operation
10. Optimizing the GenAI Lifecycle for Sustainability
11. Optimizing the Consumption of GenAI Foundational Models
12. Case Studies and Best Practices
13. Pillars of a Sustainable Technology Future

Parth Girish Patel is a seasoned architect with 17 years of experience in management consulting and cloud computing. At AWS, he specializes in AI/ML, generative AI, sustainability, and cloud-native solutions. His career journey from software engineering to consulting at Deloitte has given him a unique blend of business and technical expertise. As an AWS solutions architect, Parth guides customers through cloud adoption and AI implementation, offering insights into scalable architectures and end-to-end ML solutions. Proficient in AWS, Azure, GCP, and various ML skills, he tackles diverse technical challenges. Parth is passionate about sustainable and ethical AI, emphasizing transparency and environmental consciousness. He mentors teams and individuals, fostering innovation and driving positive impact across organizations and society.

Ishneet Kaur Dua is a seasoned solutions architect with over a decade of experience in generative AI, machine learning, environmental sustainability, and cloud computing. She excels in designing resilient systems on major cloud platforms such as AWS, GCP, and Azure. Ishneet's expertise spans low-code ML, computer vision, NLP, and predictive analytics. As an advocate for ethical AI, she ensures fairness and transparency while promoting accessibility through open source initiatives. A thought leader in AI/ML, cloud architecture, and sustainability, Ishneet speaks at global tech conferences and mentors women in STEM. Her vision is to harness technology for positive change, addressing real-world challenges and creating opportunities for all.

Steven David has over 25 years of experience in the technology industry, spanning sectors such as energy, retail, financial services, and manufacturing. His expertise lies in adopting cutting-edge technologies to drive business value, leading to extensive hands-on experience in designing and implementing custom solutions integrated with third-party products. At AWS for the past seven years, Steven has specialized in application modernization and sustainability, shaping containerization strategies and leading initiatives in the western Americas region. Passionate about mentoring emerging talent, he supports diverse perspectives and believes sustainable IT will significantly impact future generations by laying the groundwork for innovative design patterns in technology.