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

Section	Weight	Objectives
Microservices Architecture	14%	- Container orchestration with GKE 1. Managing pod lifecycle and resource quotas 2. Implementing workload deployment and scaling 3. Designing Kubernetes cluster architectures 4. Configuring node pools and auto-scaling - 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. Configuring traffic management and load balancing 3. Implementing service-to-service authentication
CI/CD Pipeline Development	26%	- Containerization and Docker 1. Creating optimized Docker images (multi-stage builds) 2. Managing container registries 3. Implementing container security best practices - Designing and implementing CI/CD pipelines 1. Configuring build caching strategies 2. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.) 3. Implementing build automation scripts 4. Setting up artifact management with Artifact Registry 5. Configuring build triggers and webhooks - CI/CD best practices 1. Implementing shift-left testing 2. Managing secrets in CI/CD pipelines 3. Configuring quality gates and code coverage
Cloud Infrastructure Automation	24%	- Deployment strategies 1. Feature flags with Firebase Remote Config or LaunchDarkly 2. Canary releases and progressive rollouts 3. Rolling updates with Kubernetes 4. Blue-green deployments - Configuration management 1. Implementing configuration drift detection 2. Managing secrets with Secret Manager 3. Using Ansible for configuration management - Infrastructure as Code (IaC) 1. Implementing with Terraform 2. Managing infrastructure modules and state 3. Implementing immutable infrastructure patterns
Reliability and Site Reliability Engineering (SRE)	24%	- Incident management 1. Post-incident reviews and blameless postmortems 2. Configuring automated incident response 3. Implementing on-call procedures - SLOs, SLIs, and SLAs 1. Error budget policies and management 2. Setting appropriate Service Level Agreements 3. Creating and interpreting Service Level Indicators 4. Defining and implementing Service Level Objectives - Monitoring and observability 1. Setting up alerting policies and incident management 2. Configuring Cloud Monitoring and Logging 3. Creating dashboards for service health visibility 4. Implementing distributed tracing with Cloud Trace
Monitoring, Logging, and Debugging	12%	- Debugging and troubleshooting 1. Analyzing performance profiles with Cloud Profiler 2. Using Cloud Debugger and Error Reporting 3. Debugging with Cloud Trace distributed tracing - Log management 1. Implementing log-based metrics 2. Structuring logs for efficient querying 3. Configuring log retention policies - Cloud Operations Suite 1. Creating uptime checks and alerts 2. Configuring Cloud Monitoring metrics 3. Implementing Cloud Logging with log sinks

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q80-Q85):

NEW QUESTION # 80
You recently deployed your application in Google Kubernetes Engine (GKE) and now need to release a new version of the application You need the ability to instantly roll back to the previous version of the application in case there are issues with the new version Which deployment model should you use?

A. Perform a testing, and test your application periodically after the deployment is complete
B. Perform a canary deployment, and test your new application periodically after the new version is deployed
C. Perform a rolling deployment and test your new application after the deployment is complete
D. Perform a blue/green deployment and test your new application after the deployment is complete

Answer: D

Explanation:
The best deployment model for releasing a new version of your application in GKE with the ability to instantly roll back to the previous version is to perform a blue/green deployment and test your new application after the deployment is complete. A blue/green deployment is a deployment strategy that involves creating two identical environments, one running the current version of the application (blue) and one running the new version of the application (green). The traffic is switched from blue to green after testing the new version, and if any issues are discovered, the traffic can be switched back to blue instantly. This way, you can minimize downtime and risk during deployment.

NEW QUESTION # 81
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead. What should you do?

A. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.
B. Configure Cloud Profiler, and initialize the cloud.go@gle.com/go/profiler library in the application.
C. Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
D. Use Cloud Monitoring to assess the App Engine CPU utilization metric.

Answer: B

NEW QUESTION # 82
Your company is creating a new cloud-native Google Cloud organization. You expect this Google Cloud organization to first be used by a small number of departments and then expand to be used by a large number of departments. Each department has a large number of applications varying in size. You need to design the VPC network architecture. Your solution must minimize the amount of management required while remaining flexible enough for development teams to quickly adapt to their evolving needs. What should you do?

A. Create a separate VPC for each department and use Private Service Connect to connect the VPCs.
B. Create a separate VPC for each department and connect the VPCs with VPC Network Peering.
C. Create a separate VPC for each department and connect the VPCs with Cloud VPN.
D. Create a separate VPC for each application and use Private Service Connect to connect the VPCs.

Answer: B

NEW QUESTION # 83
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval. What should you do to enforce approvals?

A. Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.
B. Use an Admission Controller to verify that incoming requests originate from approved sources.
C. Configure the build system with protected branches that require pull request approval.
D. Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.

Answer: A

Explanation:
The keywords here is "developers or operators". Option A the operators could push images to production without approval (operators could touch the cluster directly and the cluster cannot do any action against them). Rest same as francisco_guerra.

NEW QUESTION # 84
You deploy a new release of an internal application during a weekend maintenance window when there is minimal user tragic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix. You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do? (Choose two.)

A. Configure a CI server. Add a suite of unit tests to your code and have your CI server run them on commit and verify any changes.
B. Adopt the blue/green deployment strategy when releasing new code via a CD server.
C. Before merging new code, require 2 different peers to review the code changes.
D. Integrate a code linting tool to validate coding standards before any code is accepted into the repository.
E. Require developers to run automated integration tests on their local development environments before release.

Answer: C,D

NEW QUESTION # 85
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