Google Cloud for DevOps Engineers

Cover
Title Page
Copyright and credits
Contributors
Table of Contents
Preface
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
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