Serverless Design Patterns and Best Practices [Video]

More Information
  • Understanding of the microservices pattern and the architectural choices
  • Use command pattern, messaging pattern, priority queue pattern, fan-out pattern, pipes and filters pattern in real-life use cases.
  • Create vendor independent serverless functions

This course describes reusable serverless patterns for event-driven data processing, web applications, mobile and IoT applications, application ecosystems, and event workflows. You will learn about the various patterns such as the command pattern, messaging pattern, priority queue pattern, and fan-out pattern, and gain insights into when to use which one. Patterns related to authentication, automation, data management, and error handling will also be covered. We also delve into DevOps concepts and take you through CI and CD. Finally you'll master patterns involved in testing, securing, and scaling your cloud-native applications

The codes of this course are placed on GitHub:

Style and Approach

This course will show you how to use the most popular serverless patterns to build robust and rich applications.

  • Build efficient, scalable, and high-performance serverless applications
  • Understand the patterns and best practices involved with serverless architecture
  • Get to grips with architectural patterns involved in microservice and serverless computing
Course Length 4 hours 21 minutes
ISBN 9781788623582
Date Of Publication 29 Aug 2018


Luca Bianchi

Luca Bianchi with 10+ years' expertise in software development and architectures, serves as the CTO and Principal Product Engineer at Neosperience, shaping the future of the digital customer experience with a microservice- and 100% serverless-product architecture, taken from project to production and actively maintained constantly by adopting cutting-edge technologies.

Software architectures and serverless technologies are the main component of Luca's everyday activities both as a programmer and a researcher evaluating best solutions for a given set of constraints.