May 1, 2024
Updated June 3, 2025
25 minute read
Auto Scaling: Dynamically Adapting to Your Application's Needs
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Find a path to becoming a Auto Scaling. Learn more at:
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Reading list
We've selected 29 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Auto Scaling.
An updated edition of the highly regarded book, this version continues to provide deep insights into the challenges of data-intensive systems and patterns for building reliable and scalable applications. It's an essential reference for anyone seeking to master the complexities of systems that require robust auto scaling capabilities.
Cornerstone for understanding the underlying principles of building scalable and reliable systems, which are fundamental to auto scaling. It delves into various data systems and their trade-offs, providing essential background knowledge for anyone working with distributed systems. While not solely focused on auto scaling, its comprehensive coverage of scalability patterns makes it a must-read reference.
If you are a DevOps professional, architect, or developer working in AWS, Google Cloud, or Microsoft Azure, and you want to implement auto scaling for your applications, this is the book for you.
Microservices architecture is often employed in systems that require auto scaling due to its focus on independent, scalable services. provides a thorough understanding of designing and implementing microservices. It covers concepts like decomposition, integration, and testing, which are crucial for building systems that can be effectively auto scaled. The second edition includes updated content on contemporary topics like container orchestration and serverless.
Authored by members of Google's SRE team, this book offers invaluable insights into operating large-scale, reliable systems. Auto scaling key practice in SRE for managing load and ensuring availability. provides practical approaches and philosophies for achieving high reliability and efficiency in production environments, making it highly relevant for understanding the operational context of auto scaling.
A companion to the 'Site Reliability Engineering' book, this workbook provides practical exercises and examples for implementing SRE principles. It includes real-world scenarios related to managing system load, performance, and reliability, which are directly addressed by auto scaling strategies. It's a valuable resource for applying SRE concepts in practice.
Given the prevalence of AWS in the course titles, this study guide is highly relevant for understanding how auto scaling is implemented and managed within the AWS ecosystem. It covers AWS services like EC2 Auto Scaling, Elastic Load Balancing, and related concepts necessary for designing scalable solutions on AWS. It's a practical resource for those focusing on AWS.
This book, authored by a co-creator of Kubernetes, focuses on design patterns for building scalable and reliable distributed systems. It covers concepts and patterns that are directly relevant to implementing and managing auto scaling in modern containerized environments. It's a valuable resource for understanding contemporary approaches to distributed system design.
Provides a catalog of patterns for designing and implementing microservices, a common architectural style for scalable applications. It covers patterns related to communication, data management, and deployment, all of which have implications for how auto scaling is applied and managed within a microservices architecture.
Offers a more contemporary perspective on distributed systems for developers. It covers practical aspects of building and maintaining distributed applications, including considerations for scalability and resilience. It serves as a good bridge between theoretical concepts and real-world implementation, making it relevant for understanding how auto scaling fits into modern application development.
This foundational book on DevOps culture and practices is essential for understanding the organizational and procedural aspects that enable effective auto scaling. It emphasizes principles like flow, feedback, and experimentation, which are critical for building and operating scalable systems. While not technical deep dive into auto scaling mechanisms, it provides the necessary context for why auto scaling is important in modern IT.
Based on extensive research, this book identifies the practices that drive high performance in technology organizations, including continuous delivery and a focus on reliability and scalability. It provides the data and analysis supporting the importance of concepts like auto scaling in achieving organizational goals and improving software delivery performance.
Provides a vendor-neutral, comprehensive overview of cloud computing concepts, models, and architectures. Understanding the fundamentals of cloud infrastructure is crucial for grasping how auto scaling operates within a cloud environment. It serves as a solid reference for gaining a broad understanding of the technologies that underpin auto scaling.
Auto scaling in cloud environments is often managed using Infrastructure as Code (IaC) tools like Terraform. provides a practical guide to using Terraform for provisioning and managing infrastructure across various cloud providers. It's highly relevant for professionals who need to implement and automate auto scaling solutions.
Another widely recognized classic in distributed systems, this book explores various paradigms and theoretical underpinnings. It covers topics such as consistency, replication, and fault tolerance, which are essential for designing systems that can leverage auto scaling effectively. is valuable for deepening one's understanding of the core concepts behind scalable distributed applications.
A classic textbook in the field of distributed systems, this book covers fundamental concepts like communication, processes, naming, synchronization, and fault tolerance. These principles are directly applicable to understanding how auto scaling works in distributed environments to maintain system health and performance. It provides a strong theoretical foundation.
Explores patterns and best practices for developing applications in a cloud-native way. It covers architectural styles and design considerations that are conducive to auto scaling and operating efficiently in the cloud. It provides practical guidance for developers building applications intended to run on scalable cloud infrastructure.
Explores common patterns and practices for designing applications specifically for cloud environments. It discusses concepts related to building scalable and resilient applications, which are directly supported by auto scaling. It provides valuable insights into how to architect systems to take full advantage of cloud elasticity.
Explores the patterns and practices for transforming organizations and systems to be cloud-native. Cloud-native architectures heavily rely on principles like elasticity and auto scaling to achieve agility and resilience. This book provides context on how auto scaling fits into a broader cloud-native strategy.
While aimed at interview preparation, this book provides practical examples and frameworks for designing scalable systems. It covers various components and techniques used in large-scale applications, including strategies for handling load and ensuring availability. Understanding these design patterns is beneficial for comprehending the role of auto scaling in system architecture.
Offers a comprehensive introduction to cloud computing, focusing on fundamental concepts and principles rather than specific vendor offerings. It includes chapters on automation, orchestration, and cloud-native software design, all of which relate to building scalable and elastic systems that utilize auto scaling. It's a good resource for gaining a broad understanding.
While a novel, this book effectively illustrates the principles of DevOps and their impact on IT performance. It highlights the importance of flow, feedback loops, and a culture of improvement, all of which are relevant to optimizing systems for scalability and reliability through practices like auto scaling. It's a good introductory read for understanding the 'why' behind modern IT practices.
This textbook provides a comprehensive foundation in cloud computing principles and programming models. It covers topics such as virtualization, parallel programming, and data-intensive computing, which are relevant to understanding the context in which auto scaling is applied. It's suitable for undergraduate and graduate students seeking a deeper academic understanding.
Provides a foundational understanding of the AWS Cloud, including core services and concepts. It introduces the basics of scalability and elasticity within AWS, setting the stage for understanding EC2 Auto Scaling at a higher level. It's a good starting point for those new to AWS and cloud computing.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/1zvxp7/auto
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