
- 358 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
'Scaling Google Cloud Platform' equips developers with the know-how to get the most out of its services in storage, serverless computing, networking, infrastructure monitoring, and other IT tasks. This book explains the fundamentals of cloud scaling, including Cloud Elasticity, creating cloud workloads, and selecting the appropriate cloud scaling key performance indicators (KPIs). The book explains the sections of GCP resources that can be scaled, as well as their architecture and internals, and best practices for using these components in an operational setting in detail. The book also discusses scaling techniques such as predictive scaling, auto-scaling, and manual scaling. This book includes real-world examples illustrating how to scale many Google Cloud services, including the compute engine, GKE, VMWare Engine, Cloud Function, Cloud Run, App Engine, BigTable, Spanner, Composer, Dataproc, and Dataflow. At the end of the book, the author delves into the two most common architectures-Microservices and Bigdata to examine how you can perform reliability engineering for them on GCP.
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Dedication Page
- About the Author
- About the Reviewer
- Acknowledgement
- Preface
- Errata
- Table of Contents
- 1. Basics of Scaling Cloud Resources
- 2. KPI for Cloud Scalability
- 3. Cloud Elasticity
- 4. Challenges of Infrastructure Complexity and the Way Forward
- 5. Scaling Compute Engine
- 6. Scaling Kubernetes Engine
- 7. Scaling VMware Engine
- 8. Scaling App Engine
- 9. Scaling Google Cloud Function and Cloud Run
- 10. Configuring Bigtable for Scale
- 11. Configuring Cloud Spanner for Scale
- 12. Scaling Google Composer 2
- 13. Scaling Google Dataproc
- 14. Scaling Google Dataflow
- 15. Site Reliability Engineering
- 16. SRE Use Cases
- Index
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