Serverless Data Processing with Dataflow: Foundations

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  • Introduction
    • This module covers the course outline and does a quick refresh on the Apache Beam programming model and Google’s Dataflow managed service.
  • Beam Portability
    • In this module we are going to learn about four sections, Beam Portablity, Runner v2, Container Environments, and Cross-Language Transforms.
  • Separating Compute and Storage with Dataflow
    • In this module we discuss how to separate compute and storage with Dataflow. This module contains four sections Dataflow, Dataflow Shuffle Service, Dataflow Streaming Engine, Flexible Resource Scheduling.
  • IAM, Quotas, and Permissions
    • In this module, we talk about the different IAM roles, quotas, and permissions required to run Dataflow
  • Security
    • In this module, we will look at how to implement the right security model for your use case on Dataflow.
  • Summary
    • In this course, we started with the refresher of what Apache Beam is, and its relationship with Dataflow.