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Serverless Design Patterns and Best Practices

You're reading from   Serverless Design Patterns and Best Practices Build, secure, and deploy enterprise ready serverless applications with AWS to improve developer productivity

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788620642
Length 260 pages
Edition 1st Edition
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Author (1):
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Brian Zambrano Brian Zambrano
Author Profile Icon Brian Zambrano
Brian Zambrano
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Table of Contents (12) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. A Three-Tier Web Application Using REST 3. A Three-Tier Web Application Pattern with GraphQL 4. Integrating Legacy APIs with the Proxy Pattern 5. Scaling Out with the Fan-Out Pattern 6. Asynchronous Processing with the Messaging Pattern 7. Data Processing Using the Lambda Pattern 8. The MapReduce Pattern 9. Deployment and CI/CD Patterns 10. Error Handling and Best Practices 11. Other Books You May Enjoy

Introduction to MapReduce


MapReduce as a pattern and programming model has been around for many years, arising from parallel computing research and industry implementations. Most famously, MapReduce hit the mainstream with Google's 2004 paper entitled MapReduce—Simplified Data Processing on Large Clusters (https://research.google.com/archive/mapreduce.html). Much of the benefit of Google's initial MapReduce implementation was:

  • Automatic parallelization and distribution
  • Fault-tolerance
  • I/O scheduling
  • Status and monitoring

If you take a step back and look at that list, it should look familiar. FaaS systems such as AWS Lambda give us most of these benefits. While status and monitoring aren't inherently baked into FaaS platforms, there are ways to ensure our functions are executing successfully. On that same topic, MapReduce systems were initially, and still are, very often, managed at the OS level, meaning operators are in charge of taking care of crashed or otherwise unhealthy nodes.

Note

The preceding...

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