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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q47-Q52):

NEW QUESTION # 47
You need to run a business-critical workload on a fixed set of Compute Engine instances for several months. The workload is stable with the exact amount of resources allocated to it. You want to lower the costs for this workload without any performance implications. What should you do?

Answer: C


NEW QUESTION # 48
You have a pool of application servers running on Compute Engine. You need to provide a secure solution that requires the least amount of configuration and allows developers to easily access application logs for troubleshooting. How would you implement the solution on GCP?

Answer: D

Explanation:
https://cloud.google.com/logging/docs/audit#access-control


NEW QUESTION # 49
You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects Log entries for development projects must be exported to dev_dataset. and log entries for production projects must be exported to prod_dataset You need to minimize the number of log sinks created and you want to ensure that the log sinks apply to future projects What should you do?

Answer: D

Explanation:
Explanation
The best option for minimizing the number of log sinks created and ensuring that the log sinks apply to future projects is to create an aggregated log sink in the Dev and Prod folders. An aggregated log sink is a log sink that collects logs from multiple sources, such as projects, folders, or organizations. By creating an aggregated log sink in each folder, you can export log entries for development projects to dev_dataset and log entries for production projects to prod_dataset. You can also use filters to specify which logs you want to export.
Additionally, by creating an aggregated log sink at the folder level, you can ensure that the log sink applies to future projects that are created under that folder.


NEW QUESTION # 50
You are configuring connectivity across Google Kubernetes Engine (GKE) clusters in different VPCs You notice that the nodes in Cluster A are unable to access the nodes in Cluster B You suspect that the workload access issue is due to the network configuration You need to troubleshoot the issue but do not have execute access to workloads and nodes You want to identify the layer at which the network connectivity is broken What should you do?

Answer: A


NEW QUESTION # 51
Your company runs services on Google Cloud. Each team runs their applications in a dedicated project. New teams and projects are created regularly. Your security team requires that all logs are processed by a security information and event management (SIEM) system. The SIEM ingests logs by using Pub/Sub. You must ensure that all existing and future logs are scanned by the SIEM. What should you do?

Answer: B

Explanation:
Comprehensive and Detailed Explanation:
To ensure all logs (existing and future) are automatically processed by the SIEM system, the best approach is:
Use an organization-level aggregated sink # Captures logs from all existing and future projects automatically.
Send logs to a Pub/Sub topic # Since the SIEM ingests logs via Pub/Sub, this ensures logs are streamed in real- time.
Set an inclusion filter # To capture all logs needed by the security team.
#Why not other options?
B (Project-level logging sink)## Requires manual setup per project, which doesn't scale for new projects.
C (Log bucket instead of Pub/Sub)## SIEM is expecting real-time log ingestion via Pub/Sub, not a storage- based approach.
D (Folder-level logging sink)## Only applies to specific folders, not the entire organization.
#Official Reference:
Aggregated Sinks for Cloud Logging
Exporting Logs to SIEM via Pub/Sub


NEW QUESTION # 52
......

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