Serverless Data Processing with Dataflow: Foundations- Locales
Offered By: Google via Google Cloud Skills Boost
Course Description
Overview
"This course, Serverless Data Processing with Dataflow: Foundations-Locales, is intended for non-English learners. If you want to take this course in English, please enroll in 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. Next, we talk about the 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. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
Syllabus
- Introduction
- Course Introduction
- Beam and Dataflow Refresher
- Beam Portability
- Beam Portability
- Runner v2
- Container Environments
- Cross-Language Transforms
- Quiz
- Separating Compute and Storage with Dataflow
- Dataflow
- Dataflow Shuffle Service
- Dataflow Streaming Engine
- Flexible Resource Scheduling
- Quiz
- IAM, Quotas, and Permissions
- IAM
- Quotas
- Quiz
- Security
- Data Locality
- Shared VPC
- Private IPs
- CMEK
- Setup IAM and Networking for your Dataflow Jobs
- Quiz
- Summary
- Course Summary
- Additional Resources
Tags
Related Courses
Feature EngineeringGoogle Cloud via Coursera Feature Engineering 日本語版
Google Cloud via Coursera Feature Engineering em Português Brasileiro
Google Cloud via Coursera GCP: Complete Google Data Engineer and Cloud Architect Guide
Udemy Modeling Streaming Data for Processing with Apache Beam
Pluralsight