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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q68-Q73):

NEW QUESTION # 68
Your company operates in a highly regulated domain. Your security team requires that only trusted container images can be deployed to Google Kubernetes Engine (GKE). You need to implement a solution that meets the requirements of the security team, while minimizing management overhead. What should you do?

Answer: B


NEW QUESTION # 69
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 # 70
You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock You check the metrics for the microservice and compare them to typical levels.

You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers What should you do?

Answer: C

Explanation:
The best option for ensuring that the warehouse system accurately reflects product inventory at the time orders are placed and minimizing the impact on customers is to increase the number of Pod replicas.
Increasing the number of Pod replicas will increase the scalability and availability of your microservice, which will allow it to handle more Pub/Sub messages and update stock information faster. This way, you can reduce the backlog of undelivered messages and oldest unacknowledged message age, which are causing delays in updating product inventory. You can use Horizontal Pod Autoscaler or Cloud Monitoring metrics- based autoscaling to automatically adjust the number of Pod replicas based on load or custom metrics.


NEW QUESTION # 71
You need to reduce the cost of virtual machines (VM| for your organization. After reviewing different options, you decide to leverage preemptible VM instances. Which application is suitable for preemptible VMs?

Answer: D


NEW QUESTION # 72
You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below

The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?

Answer: D

Explanation:
Explanation
The best option for mitigating the incident impact on users and enabling the developers to troubleshoot the issue is to change the selector on the Service app-svc to app: my-app, version: blue. A Service is a resource that defines how to access a set of Pods. A selector is a field that specifies which Pods are selected by the Service. By changing the selector on the Service app-svc to app: my-app, version: blue, you can ensure that the Service only routes traffic to the Pods that have both labels app: my-app and version: blue. These Pods belong to the Deployment app-blue, which uses the previous version of the application. This way, you can mitigate the incident impact on users by switching back to the working version of the application. You can also enable the developers to troubleshoot the issue with the new version of the application in the Deployment app-green without affecting users.


NEW QUESTION # 73
......

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