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Google Cloud for DevOps Engineers

You're reading from   Google Cloud for DevOps Engineers A practical guide to SRE and achieving Google's Professional Cloud DevOps Engineer certification

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781839218019
Length 482 pages
Edition 1st Edition
Concepts
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Author (1):
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Sandeep Madamanchi Sandeep Madamanchi
Author Profile Icon Sandeep Madamanchi
Sandeep Madamanchi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Site Reliability Engineering – A Prescriptive Way to Implement DevOps
2. Chapter 1: DevOps, SRE, and Google Cloud Services for CI/CD FREE CHAPTER 3. Chapter 2: SRE Technical Practices – Deep Dive 4. Chapter 3: Understanding Monitoring and Alerting to Target Reliability 5. Chapter 4: Building SRE Teams and Applying Cultural Practices 6. Section 2: Google Cloud Services to Implement DevOps via CI/CD
7. Chapter 5: Managing Source Code Using Cloud Source Repositories 8. Chapter 6: Building Code Using Cloud Build, and Pushing to Container Registry 9. Chapter 7: Understanding Kubernetes Essentials to Deploy Containerized Applications 10. Chapter 8: Understanding GKE Essentials to Deploy Containerized Applications 11. Chapter 9: Securing the Cluster Using GKE Security Constructs 12. Chapter 10: Exploring GCP Cloud Operations 13. Mock Exam 1 14. Mock Exam 2 15. Other Books You May Enjoy Appendix: Getting Ready for Professional Cloud DevOps Engineer Certification

Points to remember

Here are some important points to remember:

  • 100% is an unrealistic reliability target.
  • Log-based SLIs and ingesting telemetry adds latency.
  • App metrics are not good for complex use journeys.
  • SLOs must be set based on conversations with engineering and product teams.
  • If there is no error budget left, the focus should be on reliability.
  • TTD is the time taken to identify that an issue exists or is reported.
  • TTR is the time taken to resolve an issue.
  • To improve the reliability of a service, reduce TTD, reduce TTR, reduce impact %, and increase TTF/TBF.
  • SLIs should have a predictable relationship with user happiness and should be aggregated over time.
  • User expectations are strongly tied to past performance.
  • Setting values for SLIs and SLOs should be an iterative process.
  • Advanced techniques to manage error budgets are dynamic release cadence, setting up error budget exhaustion rates, rainy-day funds, and the use of silver...
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