Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Professional Cloud Architect –  Google Cloud Certification Guide

You're reading from   Professional Cloud Architect – Google Cloud Certification Guide A handy guide to designing, developing, and managing enterprise-grade GCP cloud solutions

Arrow left icon
Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781838555276
Length 520 pages
Edition 1st Edition
Arrow right icon
Authors (2):
Arrow left icon
Brian Gerrard Brian Gerrard
Author Profile Icon Brian Gerrard
Brian Gerrard
Konrad Cłapa Konrad Cłapa
Author Profile Icon Konrad Cłapa
Konrad Cłapa
Arrow right icon
View More author details
Toc

Table of Contents (26) Chapters Close

Preface 1. Section 1: Introduction to GCP FREE CHAPTER
2. GCP Cloud Architect Professional 3. Getting Started with Google Cloud Platform 4. Google Cloud Platform Core Services 5. Section 2: Managing, Designing, and Planning a Cloud Solution Architecture
6. Working with Google Compute Engine 7. Managing Kubernetes Clusters with Google Kubernetes Engine 8. Exploring Google App Engine as a Compute Option 9. Running Serverless Functions with Google Cloud Functions 10. Networking Options in GCP 11. Exploring Storage Options in GCP - Part 1 12. Exploring Storage Options in GCP - Part 2 13. Analyzing Big Data Options 14. Putting Machine Learning to Work 15. Section 3: Designing for Security and Compliance
16. Security and Compliance 17. Section 4: Managing Implementation
18. Google Cloud Management Options 19. Section 5: Ensuring Solution and Operations Reliability
20. Monitoring Your Infrastructure 21. Section 6: Exam Focus
22. Case Studies 23. Test Your Knowledge 24. Assessments 25. Other Books You May Enjoy

Cloud Dataflow

Cloud Dataflow is a service based on Apache Beam, which is an open source software for creating data processing pipelines. A pipeline is essentially a piece of code that determines how we wish to process our data. Once these pipelines have been constructed and input into the service, they become a Dataflow job. This is where we can process our data ingested by Pub/Sub. It will perform steps to change our data from one format to another, and can transform both real-time stream or historical batch data. Dataflow is completely serverless and fully managed. It will spin up and destroy the necessary resources to execute our Dataflow job. As an example, a pipeline job might be made up of several steps. If a specific step requires execution on 15 machines in parallel, then Dataflow will automatically scale to these 15 machines and remove them when the job is complete....

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime