Designing Fast Data Application Architectures

Gerard Maas, Senior Engineer, Lightbend, Inc.

Stavros Kontopoulos, Senior Engineer, Lightbend

Sean Glover, Principal Engineer, Lightbend, Inc.

Audience: Architects and Developers

Technical level: Introductory

Today’s digital companies demand real-time insights and immediate action for everything from purchase to fulfillment, recommendation, and more. As a result, many organizations are adopting fast data applications to accelerate the value they extract from data as it flows into the system. With this practical ebook from Lightbend and O’Reilly, you’ll learn the common architectural patterns that form the foundation of successful Fast Data deployments.

In this book, we identify the key characteristics of Fast Data architectures, separate them into functional blocks, and show you how to implement those functions using components like those in the SMACK stack—Spark, Mesos, Akka, Cassandra, and Kafka, as well as others. Architects will learn how to choose, combine, and run SMACK stack technologies to build resilient, scalable, and responsive systems that your company requires. This eBook examines:

  • The anatomy of Fast Data applications: the application model, streaming data sources, processing engines, and data sinks
  • Functional composition of the SMACK stack and extensions
  • The event backbone that connects all the major components of a Fast Data system together
  • Compute engines for transforming data into valuable insights
  • Storage systems that form the transition between the Fast Data domain and client applications
  • Patterns you can use in the data serving layer, including data-driven microservices
  • Container orchestration tools in the substrate layer that provide resources to services, frameworks, and applications

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About Author(s)

Gerard Maas, Senior Engineer, Lightbend, Inc.

I'm working on the Fast Data Platform engineering team. We are building the best-in-class,integrated streaming data platform to accelerate developer velocity and shorten time-to-market of new reactive data services. My current focus is on streaming technologies on Apache Spark.

Stavros Kontopoulos, Senior Engineer, Lightbend

Stavros is a senior engineer on the fast data systems team at Lightbend, where he helps with the implementation of the Lightbend's fast data strategy. He has worked for several years building software solutions that scale in different verticals like telecoms and marketing. His interests among others are: distributed system design, streaming technologies, and NoSQL databases.

Sean Glover, Principal Engineer, Lightbend, Inc.

Sean Glover is a Principal Engineer on the Pipelines team at Lightbend where he specializes in data stream processors, Kubernetes, Apache Kafka and its ecosystem. Sean enjoys building data streaming platforms, reactive distributed systems, and contributing to open source projects.

About Lightbend

Lightbend (@Lightbend) is leading the enterprise transformation toward real-time, cloud-native applications. Lightbend Platform provides scalable, high-performance microservices frameworks and streaming engines for building data-centric systems that are optimized to run on cloud-native infrastructure. The most admired brands around the globe are transforming their businesses with Lightbend, engaging billions of users every day through software that is changing the world. For more information, visit lightbend.com.

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