Serverless Data Processing with Dataflow: Foundations
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow.
What you'll learn
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow.
In this first course, we start with refreshers of:
- what Apache Beam is and its relationship with Dataflow
- Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend
- how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines
Table of contents
Course FAQ
Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem.
Some benefits of Apache Beam are unifying batch and streaming, APIs that raise the level of abstraction, portability across runtimes, and supports multiple runner backends at a time.
The Google Cloud Platform offers computing, storage, networking, big data, machine learning, and IoT Services as well as cloud management, security, and developer tools.
Qwiklabs provides real cloud environments that help developers and IT professionals learn cloud platforms and software.
A private IP is an address that is not routed on the internet and no traffic can be sent to that IP from the internet. It will only work from within the local network.
