Google Cloud for DevOps Engineers by Sandeep Madamanchi -- Read -- Imperial Library of Trantor

Index

Google Cloud for DevOps Engineers Contributors About the author About the reviewers Preface

Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews

Section 1: Site Reliability Engineering – A Prescriptive Way to Implement DevOps Chapter 1: DevOps, SRE, and Google Cloud Services for CI/CD

Understanding DevOps, its evolution, and life cycle

Revisiting DevOps evolution DevOps life cycle Key pillars of DevOps

SRE's evolution; technical and cultural practices

The evolution of SRE Understanding SRE SRE's approach toward DevOps' key pillars Introducing SRE's key concepts SRE's technical practices SRE's cultural practices

Cloud-native approach to implementing DevOps using Google Cloud

Focus on microservices Cloud-native development Continuous integration in GCP Continuous delivery/deployment in GCP Continuous monitoring/operations on GCP Bringing it all together – building blocks for a CI/CD pipeline in GCP

Summary Points to remember Further reading Practice test Answers

Chapter 2: SRE Technical Practices – Deep Dive

Defining SLAs

Key jargon Blueprint for a well-defined SLA SLIs drive SLOs, which inform SLAs

Defining reliability expectations via SLOs

SLOs drive business decisions Setting SLOs – the guidelines

Exploring SLIs

Categorizing user journeys SLI equation Sources to measure SLIs SLI best practices (Google-recommended)

Understanding error budgets

Error budget policy and the need for executive buy-in Making a service reliable Summarizing error budgets

Eliminating toil through automation Illustrating the impact of SLAs, SLOs, and error budgets relative to SLI

Scenario 1 – New service features introduced; features are reliable; SLO is met Scenario 2 – New features introduced; features are not reliable; SLO is not met

Summary Points to remember Further reading Practice test Answers

Chapter 3: Understanding Monitoring and Alerting to Target Reliability

Understanding monitoring

Monitoring as a feedback loop Monitoring misconceptions to avoid Monitoring sources Monitoring strategies Monitoring types The golden signals

Alerting

Alerting strategy – key attributes Alerting strategy – potential approaches Handling service with low traffic Steps to establish an SLO alerting policy Alerting system – desirable characteristics

Time series

Time series structure Time series cardinality Time series data – metric types

Summary Points to remember Further reading Practice test Answers

Chapter 4: Building SRE Teams and Applying Cultural Practices

Building SRE teams

Staffing SRE engineers (SREs) SRE team implementations – procedure and strategy SRE engagement model

Incident management

Incident life cycle Elements of effective incident management

Being on call

Paging versus non-paging events Single-site versus multi-site production teams Recommended practices while being on call

Psychological safety

Factors to overcome in order to foster psychological safety

Sharing vision and knowledge and fostering collaboration

Unified vision Communication and collaboration

Summary Points to remember Further reading Practice test Answers

Section 2: Google Cloud Services to Implement DevOps via CI/CD Chapter 5: Managing Source Code Using Cloud Source Repositories

Technical requirements Introducing the key features

Creating a repository via Google Cloud Console Creating a repository via the CLI Adding files to a repository in CSR

One-way sync from GitHub/Bitbucket to CSR Common operations in CSR

Browsing repositories Performing a universal code search Detecting security keys Assigning access controls

Hands-on lab – integrating with Cloud Functions

Adding code to an existing repository through the Cloud Shell Editor Pushing code from the Cloud Shell Editor (local repository) into CSR Creating a cloud function and deploying code from the repository in CSR

Summary Further reading Practice test Answers

Chapter 6: Building Code Using Cloud Build, and Pushing to Container Registry

Technical requirements Key terminology (prerequisites) Understanding the need for automation Building and creating container images – Cloud Build

Cloud Build essentials Building code using Cloud Build Storing and viewing build logs Managing access controls Cloud Build best practices – optimizing builds

Managing build artifacts – Container Registry

Container Registry – key concepts

Hands-on lab – building, creating, pushing, and deploying a container to Cloud Run using Cloud Build triggers

Creating an empty repository in Source Repositories Creating a Cloud Build trigger Adding code and pushing it to the master branch Code walk-through Viewing the results

Summary Points to remember Further reading Practice test Answers

Chapter 7: Understanding Kubernetes Essentials to Deploy Containerized Applications

Technical requirements Kubernetes – a quick introduction

Container orchestration Kubernetes features

Kubernetes cluster anatomy

Master components – Kubernetes control plane Node components Using kubectl

Kubernetes objects

Pod Deployment StatefulSets DaemonSets Service

Scheduling and interacting with Pods

Summarizing master plane interactions on Pod creation Critical factors to consider while scheduling Pods

Kubernetes deployment strategies

Recreate strategy Rolling update strategy Blue/Green strategy Canary deployment

Summary Points to remember Further reading Practice test Answers

Chapter 8: Understanding GKE Essentials to Deploy Containerized Applications

Technical requirements Google Kubernetes Engine (GKE) – introduction

Creating a GKE cluster GKE cluster – deploying and exposing an application GKE Console

GKE – core features

GKE node pools GKE cluster configuration AutoScaling in GKE Networking in GKE Storage options for GKE Cloud Operations for GKE

GKE Autopilot – hands-on lab Summary Points to remember Further reading Practice test Answers

Chapter 9: Securing the Cluster Using GKE Security Constructs

Technical requirements Essential security patterns in Kubernetes

Authentication Authorization Control plane security Pod security

Hardening cluster security in GKE

GKE private clusters Container-optimized OS Shielded GKE nodes Network Policies – restricting traffic among pods Workload Identity

Points to remember Further reading Practice test Answers

Chapter 10: Exploring GCP Cloud Operations

Cloud Monitoring

Workspaces Dashboards Metrics explorer Uptime checks Alerting Monitoring agent Cloud Monitoring access controls

Cloud Logging

Audit Logs Logs ingestion, routing, and exporting Summarizing log characteristics across log buckets Logs Explorer UI Logs-based metrics Network-based log types Logging agent

Cloud Debugger

Setting up Cloud Debugger Using Cloud Debugger Access control for Cloud Debugger

Cloud Trace

Trace Overview Trace List Analysis Reports

Cloud Profiler

Access control for Cloud Profiler

Binding SRE and Cloud Operations

SLO monitoring Hands-on lab – tracking service reliability using SLO monitoring

Summary Points to remember Further reading Practice test Answers

Appendix: Getting Ready for Professional Cloud DevOps Engineer Certification

Cloud Deployment Manager Cloud Tasks Spinnaker

Mock Exam 1

Test Duration: 2 hours Total Number of Questions: 50 Answers

Mock Exam 2

Test Duration: 2 hours Total Number of Questions: 50 Answers Why subscribe?

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