Serverless Data Processing with Dataflow Course Overview

The Serverless Data Processing with Dataflow course provides a comprehensive guide for learners to master data processing architectures leveraging Apache Beam and Google Cloud Dataflow. This course is designed to equip participants with the knowledge required to build scalable and efficient data processing pipelines that cater to their organization's needs without the overhead of server management.

Throughout the modules, learners will delve into the Beam Portability Framework, enabling them to create versatile pipelines that can run across different environments using custom containers. They will explore how to separate compute and storage, manage IAM permissions, quotas, and understand security best practices. The course also revisits core Beam concepts, dives into handling streaming data challenges with windows and watermarks, and discusses the development of custom I/O transformations.

Advanced topics include the use of schemas for structured data, state and timers for complex processing scenarios, and performance optimization strategies. The course also covers robust testing, CI/CD practices, monitoring, logging, error reporting, and troubleshooting methods. Finally, Flex Templates are introduced as a way to standardize and reuse pipeline code, culminating in a comprehensive summary that solidifies the learner's expertise in serverless data processing with Dataflow.