Scalability Patterns

Best Practices for Designing High Volume Websites

Chander Dhall

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Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

In this book, the CEO of Cazton, Inc. and internationally-acclaimed speaker, Chander Dhall, demonstrates current website design scalability patterns and takes a pragmatic approach to explaining their pros and cons to show you how to select the appropriate pattern for your site. He then tests the patterns by deliberately forcing them to fail and exposing potential flaws before discussing how to design the optimal pattern to match your scale requirements. The author explains the use of polyglot programming and how to match the right patterns to your business needs. He also details several No-SQL patterns and explains the fundamentals of different paradigms of No-SQL by showing complementary strategies of using them along with relational databases to achieve the best results. He also teaches how to make the scalability pattern work with a real-world microservices pattern. 

With the proliferation of countless electronic devices and the ever growing number of Internet users, the scalability of websites has become an increasingly important challenge. Scalability, even though highly coveted, may not be so easy to achieve. Think that you can't attain responsiveness along with scalability? Chander Dhall will demonstrate that, in fact, they go hand in hand.

What You'll Learn

  • Architect and develop applications so that they are easy to scale. 
  • Learn different scaling and partitioning options and the combinations. 
  • Learn techniques to speed up responsiveness. 
  • Deep dive into caching, column-family databases, document databases, search engines and RDBMS. 
  • Learn scalability and responsiveness concepts that are usually ignored.
  • Effectively balance scalability, performance, responsiveness, and availability while minimizing downtime.

Who This Book Is For

Executives (CXOs), software architects , developers, and IT Pros

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Schlagwörter

SQL, cloud computing`, architecture, NoSQL, failover, performance, reliability, distributed computing, best practices