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

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

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Google Professional-Cloud-DevOps-Engineer Associate Level Exam - Professional-Cloud-DevOps-Engineer Reliable Test Questions

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q115-Q120):

NEW QUESTION # 115
You are investigating issues in your production application that runs on Google Kubernetes Engine (GKE).
You determined that the source Of the issue is a recently updated container image, although the exact change in code was not identified. The deployment is currently pointing to the latest tag. You need to update your cluster to run a version of the container that functions as intended. What should you do?

A. Alter the deployment to point to the sha2 56 digest of the previously working container.
B. Build a new container from a previous Git tag, and do a rolling update on the deployment to the new container.
C. Apply the latest tag to the previous container image, and do a rolling update on the deployment.
D. Create a new tag called stable that points to the previously working container, and change the deployment to point to the new tag.

Answer: A

NEW QUESTION # 116
You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.
B. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.
C. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.
D. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.

Answer: D

NEW QUESTION # 117
You are ready to deploy a new feature of a web-based application to production. You want to use Google Kubernetes Engine (GKE) to perform a phased rollout to half of the web server pods.
What should you do?

A. Use Node taints with NoExecute.
B. Use a replica set in the deployment specification.
C. Use a partitioned rolling update.
D. Use a stateful set with parallel pod management policy.

Answer: C

NEW QUESTION # 118
You are deploying an application that needs to access sensitive information. You need to ensure that this information is encrypted and the risk of exposure is minimal if a breach occurs. What should you do?

A. Integrate the application with a Single sign-on (SSO) system and do not expose secrets to the application
B. Inject the secret at the time of instance creation via an encrypted configuration management system.
C. Leverage a continuous build pipeline that produces multiple versions of the secret for each instance of the application.
D. Store the encryption keys in Cloud Key Management Service (KMS) and rotate the keys frequently

Answer: D

Explanation:
Explanation
https://cloud.google.com/security-key-management

NEW QUESTION # 119
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?

A. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
B. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
C. Create a new service account with the Container Developer role and use it to run Cloud Build.
D. Assign the Container Developer role to the Cloud Build service account.

Answer: D

Explanation:
Explanation
https://cloud.google.com/build/docs/deploying-builds/deploy-gke
https://cloud.google.com/build/docs/securing-builds/configure-user-specified-service-accounts

NEW QUESTION # 120
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