Professional-Cloud-DevOps-Engineer学習資料 & Professional-Cloud-DevOps-Engineer試験対策

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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q60-Q65):

質問 # 60
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to the production environment. A recent security audit alerted your team that the code pushed to production could contain vulnerabilities and that the existing tooling around virtual machine (VM) vulnerabilities no longer applies to the containerized environment. You need to ensure the security and patch level of all code running through the pipeline. What should you do?

A. Configure the containers in the build pipeline to always update themselves before release.
B. Reconfigure the existing operating system vulnerability software to exist inside the container.
C. Implement static code analysis tooling against the Docker files used to create the containers.
D. Set up Container Analysis to scan and report Common Vulnerabilities and Exposures.

正解：D

質問 # 61
You are creating a CI/CD pipeline in Cloud Build to build an application container image The application code is stored in GitHub Your company requires thai production image builds are only run against the main branch and that the change control team approves all pushes to the main branch You want the image build to be as automated as possible What should you do?
Choose 2 answers

A. Add the owners file to the Included files filter on the trigger
B. Configure a branch protection rule for the main branch on the repository
C. Create a trigger on the Cloud Build job Set the repository event setting to Push to a branch
D. Enable the Approval option on the trigger
E. Create a trigger on the Cloud Build job Set the repository event setting to Pull request'

正解：B、C

質問 # 62
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 a stateful set with parallel pod management policy.
B. Use a replica set in the deployment specification.
C. Use Node taints with NoExecute.
D. Use a partitioned rolling update.

正解：D

解説：
https://medium.com/velotio-perspectives/exploring-upgrade-strategies-for-stateful-sets-in-kubernetes-c02b8286f251

質問 # 63
You support a user-facing web application. When analyzing the application's error budget over the previous six months, you notice that the application has never consumed more than 5% of its error budget in any given time window. You hold a Service Level Objective (SLO) review with business stakeholders and confirm that the SLO is set appropriately. You want your application's SLO to more closely reflect its observed reliability. What steps can you take to further that goal while balancing velocity, reliability, and business needs? (Choose two.)

A. Tighten the SLO match the application's observed reliability.
B. Implement and measure additional Service Level Indicators (SLIs) fro the application.
C. Add more serving capacity to all of your application's zones.
D. Announce planned downtime to consume more error budget, and ensure that users are not depending on a tighter SLO.
E. Have more frequent or potentially risky application releases.

正解：B、C

質問 # 64
You use Cloud Build to build and deploy your application. You want to securely incorporate database credentials and other application secrets into the build pipeline. You also want to minimize the development effort. What should you do?

A. Use client-side encryption to encrypt the secrets and store them in a Cloud Storage bucket. Store a decryption key in the bucket and grant Cloud Build access to the bucket.
B. Create a Cloud Storage bucket and use the built-in encryption at rest. Store the secrets in the bucket and grant Cloud Build access to the bucket.
C. Use Cloud Key Management Service (Cloud KMS) to encrypt the secrets and include them in your Cloud Build deployment configuration. Grant Cloud Build access to the KeyRing.
D. Encrypt the secrets and store them in the application repository. Store a decryption key in a separate repository and grant Cloud Build access to the repository.

正解：C

解説：
https://cloud.google.com/build/docs/securing-builds/use-encrypted-credentials

質問 # 65
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