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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Cloud Infrastructure Automation24%- Configuration management
  • 1. Managing secrets with Secret Manager
  • 2. Implementing configuration drift detection
  • 3. Using Ansible for configuration management
- Infrastructure as Code (IaC)
  • 1. Implementing immutable infrastructure patterns
  • 2. Implementing with Terraform
  • 3. Managing infrastructure modules and state
- Deployment strategies
  • 1. Canary releases and progressive rollouts
  • 2. Blue-green deployments
  • 3. Rolling updates with Kubernetes
  • 4. Feature flags with Firebase Remote Config or LaunchDarkly
Microservices Architecture14%- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
- Service mesh and networking
  • 1. Implementing Anthos Service Mesh / Istio
  • 2. Implementing service-to-service authentication
  • 3. Configuring traffic management and load balancing
- Container orchestration with GKE
  • 1. Designing Kubernetes cluster architectures
  • 2. Managing pod lifecycle and resource quotas
  • 3. Implementing workload deployment and scaling
  • 4. Configuring node pools and auto-scaling
CI/CD Pipeline Development26%- Designing and implementing CI/CD pipelines
  • 1. Configuring build caching strategies
  • 2. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 3. Configuring build triggers and webhooks
  • 4. Implementing build automation scripts
  • 5. Setting up artifact management with Artifact Registry
- Containerization and Docker
  • 1. Managing container registries
  • 2. Creating optimized Docker images (multi-stage builds)
  • 3. Implementing container security best practices
- CI/CD best practices
  • 1. Managing secrets in CI/CD pipelines
  • 2. Configuring quality gates and code coverage
  • 3. Implementing shift-left testing
Reliability and Site Reliability Engineering (SRE)24%- SLOs, SLIs, and SLAs
  • 1. Error budget policies and management
  • 2. Setting appropriate Service Level Agreements
  • 3. Defining and implementing Service Level Objectives
  • 4. Creating and interpreting Service Level Indicators
- Monitoring and observability
  • 1. Creating dashboards for service health visibility
  • 2. Configuring Cloud Monitoring and Logging
  • 3. Setting up alerting policies and incident management
  • 4. Implementing distributed tracing with Cloud Trace
- Incident management
  • 1. Configuring automated incident response
  • 2. Post-incident reviews and blameless postmortems
  • 3. Implementing on-call procedures
Monitoring, Logging, and Debugging12%- Log management
  • 1. Configuring log retention policies
  • 2. Structuring logs for efficient querying
  • 3. Implementing log-based metrics
- Debugging and troubleshooting
  • 1. Debugging with Cloud Trace distributed tracing
  • 2. Using Cloud Debugger and Error Reporting
  • 3. Analyzing performance profiles with Cloud Profiler
- Cloud Operations Suite
  • 1. Implementing Cloud Logging with log sinks
  • 2. Creating uptime checks and alerts
  • 3. Configuring Cloud Monitoring metrics

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q43-Q48):

NEW QUESTION # 43
Some of your production services are running in Google Kubernetes Engine (GKE) in the eu-west-1 region.
Your build system runs in the us-west-1 region. You want to push the container images from your build system to a scalable registry to maximize the bandwidth for transferring the images to the cluster. What should you do?

Answer: C

Explanation:
Hostname Storage location gcr.io Stores images in data centers in the United States asia.gcr.io Stores images in data centers in Asia eu.gcr.io Stores images in data centers within member states of the European Union us.
gcr.io Stores images in data centers in the United States


NEW QUESTION # 44
You need to create a Cloud Monitoring SLO for a service that will be published soon. You want to verify that requests to the service will be addressed in fewer than 300 ms at least 90% Of the time per calendar month. You need to identify the metric and evaluation method to use. What should you do?

Answer: A


NEW QUESTION # 45
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

Answer: B

Explanation:
https://www.atlassian.com/incident-management/kpis/common-metrics
https://linkedin.github.io/school-of-sre/


NEW QUESTION # 46
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?

Answer: B

Explanation:
The correct answer is C.
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources.This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1.Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2.By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials.User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials.The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform.Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.


NEW QUESTION # 47
You are building the Cl/CD pipeline for an application deployed to Google Kubernetes Engine (GKE) The application is deployed by using a Kubernetes Deployment, Service, and Ingress The application team asked you to deploy the application by using the blue'green deployment methodology You need to implement the rollback actions What should you do?

Answer: D

Explanation:
Explanation
The best option for implementing the rollback actions is to update the Kubernetes Service to point to the previous Kubernetes Deployment. A Kubernetes Service is a resource that defines how to access a set of Pods.
A Kubernetes Deployment is a resource that manages the creation and update of Pods. By using the blue/green deployment methodology, you can create two Deployments, one for the current version (blue) and one for the new version (green), and use a Service to switch traffic between them. If you need to rollback, you can update the Service to point to the previous Deployment (blue) and stop sending traffic to the new Deployment (green).


NEW QUESTION # 48
......

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