Book Image

Google Cloud for DevOps Engineers

By : Sandeep Madamanchi
Book Image

Google Cloud for DevOps Engineers

By: Sandeep Madamanchi

Overview of this book

DevOps is a set of practices that help remove barriers between developers and system administrators, and is implemented by Google through site reliability engineering (SRE). With the help of this book, you'll explore the evolution of DevOps and SRE, before delving into SRE technical practices such as SLA, SLO, SLI, and error budgets that are critical to building reliable software faster and balance new feature deployment with system reliability. You'll then explore SRE cultural practices such as incident management and being on-call, and learn the building blocks to form SRE teams. The second part of the book focuses on Google Cloud services to implement DevOps via continuous integration and continuous delivery (CI/CD). You'll learn how to add source code via Cloud Source Repositories, build code to create deployment artifacts via Cloud Build, and push it to Container Registry. Moving on, you'll understand the need for container orchestration via Kubernetes, comprehend Kubernetes essentials, apply via Google Kubernetes Engine (GKE), and secure the GKE cluster. Finally, you'll explore Cloud Operations to monitor, alert, debug, trace, and profile deployed applications. By the end of this SRE book, you'll be well-versed with the key concepts necessary for gaining Professional Cloud DevOps Engineer certification with the help of mock tests.
Table of Contents (17 chapters)
1
Section 1: Site Reliability Engineering – A Prescriptive Way to Implement DevOps
6
Section 2: Google Cloud Services to Implement DevOps via CI/CD
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...