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

Cloud Trace

A trace is a collection of spans. A span is an object that wraps latency-specific metrics and other contextual information around a unit of work in an application. Cloud Trace is a distributed tracing system that captures latency data from an application, tracks the request's propagation, retrieves real-time performance insights, and displays the results in Google Cloud Console. This latency information can be either for a single request or can be aggregated for the entire application. This information helps us identify performance bottlenecks.

Additionally, Cloud Trace can automatically analyze application traces that might reflect recent changes to the application's performance, identify degradations from latency reports, capture traces from containers, and create alerts as needed.

Cloud Trace's language-specific SDKs are available for Java, Node.js, Ruby, and Go. These SDKs can analyze projects running on VMs. It is not necessary for these VMs to...