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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

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781838555276
Length 520 pages
Edition 1st Edition
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Authors (2):
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Brian Gerrard Brian Gerrard
Author Profile Icon Brian Gerrard
Brian Gerrard
Konrad Cłapa Konrad Cłapa
Author Profile Icon Konrad Cłapa
Konrad Cłapa
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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

Additional considerations

There are other services offered by Google that we wish to highlight.

  • Dataprep: This is a web application that allows us to define preparation rules for our data by interfacing with a sample of the data. Like many of the other services we have discussed, Dataprep is serverless, meaning no upfront deployments are required. It can accept raw data and preprocess this before handing over to Cloud Dataflow to refine the data. Refer to https://cloud.google.com/dataprep/ for more information.
    We recommend that you refer to the Further reading section if you are interested in learning more.
  • Datalab: This is built on Jupyter (formerly IPython), which is an open source web application. Datalab is an interactive data analysis and machine learning environment. We can use this product to visualize and explore data using Python and SQL interactively. This would be...
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