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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q28-Q33):

NEW QUESTION # 28
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?

A. Use Cloud Pub/Sub to trigger a Spinnaker pipeline.
B. Use a custom builder in Cloud Build to trigger a Jenkins pipeline.
C. Use Cloud Pub/Sub to trigger a custom deployment service running in Google Kubernetes Engine (GKE).
D. Use Cloud Build to trigger a Spinnaker pipeline.

Answer: A

Explanation:
https://cloud.google.com/architecture/continuous-delivery-toolchain-spinnaker-cloud
https://spinnaker.io/guides/user/pipeline/triggers/pubsub/

NEW QUESTION # 29
Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics alerts: and generating dashboards This setup does not provide a method to view metrics globally across all clusters You need to implement a scalable solution to support global Prometheus querying and minimize management overhead What should you do?

A. Configure workload metrics within Cloud Operations for GKE
B. Configure Prometheus cross-service federation for centralized data access
C. Configure Google Cloud Managed Service for Prometheus
D. Configure Prometheus hierarchical federation for centralized data access

Answer: C

NEW QUESTION # 30
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
B. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.
C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
D. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.

Answer: A

Explanation:
https://medium.com/google-cloud/fluentd-filter-plugin-for-google-cloud-data-loss-prevention-api-42bbb1308e76

NEW QUESTION # 31
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to- share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?

A. 1. Export VM utilization logs from Stackdriver to BigOuery.2. Create a dashboard in Data Studio.3.
Share the dashboard with your stakeholders.
B. 1. Export VM utilization logs (rom Stackdriver to BigQuery.2. From BigQuery. export the logs to a CSV file.3. Import the CSV file into Google Sheets.4. Build a dashboard in Google Sheets and share it with your stakeholders.
C. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.2. Enable the Cloud Storage API to pull the logs programmatically.3. Build a custom data visualization application.4. Display the pulled logs in a custom dashboard.
D. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.3. Build the dashboards in the SIEM system and share with your stakeholders.

Answer: A

NEW QUESTION # 32
You use a multiple step Cloud Build pipeline to build and deploy your application to Google Kubernetes Engine (GKE). You want to integrate with a third-party monitoring platform by performing a HTTP POST of the build information to a webhook. You want to minimize the development effort. What should you do?

A. Add a new step at the end of the pipeline in Cloud Build to HTTP POST the build information to a webhook.
B. Use Stackdriver Logging to create a logs-based metric from the Cloud Buitd logs. Create an Alert with a Webhook notification type.
C. Add logic to each Cloud Build step to HTTP POST the build information to a webhook.
D. Create a Cloud Pub/Sub push subscription to the Cloud Build cloud-builds PubSub topic to HTTP POST the build information to a webhook.

Answer: A

NEW QUESTION # 33
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