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

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

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최신 Cloud DevOps Engineer Professional-Cloud-DevOps-Engineer 무료샘플문제 (Q193-Q198):

질문 # 193
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?

A. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.
B. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
C. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.
D. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.

정답：D

질문 # 194
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?

A. Escalate the situation and request additional error budget.
B. Notify the team about the lack of error budget and ensure that all their tests are successful so the launch will not further risk the error budget.
C. Look through other metrics related to the product and find SLOs with remaining error budget.
Reallocate the error budgets and allow the feature launch.
D. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.

정답：D

설명：
Explanation
The correct answer is A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1. An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users. In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices. Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.

질문 # 195
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?

A. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
B. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using a key stored in Cloud Key Management Service (Cloud KMS).
C. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using their personal private key.
D. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) with a service account JSON key stored as a Kubernetes Secret.

정답：A

설명：
The correct answer is B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
According to the Google Cloud documentation, Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or Cloud Run1.
Binary Authorization uses attestations to certify that a specific image has completed a previous stage in the CI
/CD pipeline, such as passing a load test2.Attestations are signed by private keys that are associated with attestors, which are entities that verify the attestations3.To follow Google-recommended practices, you should store your private keys in Cloud Key ManagementService (Cloud KMS), which is a secure and scalable service for managing cryptographic keys4.You should also use Workload Identity, which is a feature that allows Kubernetes service accounts to act as Google service accounts, to authenticate to Cloud KMS and sign attestations without having to manage or expose service account keys5.
The other options are incorrect because they do not follow Google-recommended practices. Option A and option D require human intervention to sign the attestations, which is not scalable or automated. Option C exposes the service account JSON key as a Kubernetes Secret, which is less secure than using Workload Identity.

질문 # 196
Your application images are built using Cloud Build and pushed to Google Container Registry (GCR). You want to be able to specify a particular version of your application for deployment based on the release version tagged in source control. What should you do when you push the image?

A. Reference the image digest in the source control tag.
B. Use Cloud Build to include the release version tag in the application image.
C. Use GCR digest versioning to match the image to the tag in source control.
D. Supply the source control tag as a parameter within the image name.

정답：B

질문 # 197
You support a high-traffic web application that runs on Google Cloud Platform (GCP). You need to measure application reliability from a user perspective without making any engineering changes to it. What should you do?
Choose 2 answers

A. Modify the code to capture additional information for user interaction.
B. Analyze the web proxy logs only and capture response time of each request.
C. Create new synthetic clients to simulate a user journey using the application.
D. Use current and historic Request Logs to trace customer interaction with the application.
E. Review current application metrics and add new ones as needed.

정답：C,D

설명：
Explanation
The most effective ways to measure application reliability from a user perspective without making any engineering changes are to create new synthetic clients to simulate a user journey using the application, and to use current and historic Request Logs to trace customer interaction with the application. These methods can help you monitor the availability, latency, and errors of your application from an end-user perspective .

질문 # 198
......

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