In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively.

Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems.

You will focus on:

Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs
Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices
Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency
Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing

� propos de l?auteur

Ian Gorton has 30 years experience as a software architect, author, computer science professor and consultant. He has focused on distributed technologies since his days in graduate school, and has worked on large scale software systems in areas such as banking, telecommunications, government, health care and scientific modeling and simulation. During this time, he has seen software systems evolve to the massive scale they routinely operate at today.

Ian has written 3 books, including "Essential Software Architecture" and "Data Intensive Computing", and is the author of 200+ scientific and professional publications on software architecture and software engineering. At the Carnegie Mellon Software Engineering Institute he led R&D projects in big data and massively scalable systems, and has continued working, writing and speaking on these topics since joining Northeastern University as a Professor of Computer Science in 2015. He has a PhD from Sheffield Hallam University, UK and is a Senior Member of the IEEE Computer Society.

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