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

Section	Weight	Objectives
Monitoring, Logging, and Debugging	12%	- Debugging and troubleshooting 1. Debugging with Cloud Trace distributed tracing 2. Analyzing performance profiles with Cloud Profiler 3. Using Cloud Debugger and Error Reporting - Log management 1. Structuring logs for efficient querying 2. Configuring log retention policies 3. Implementing log-based metrics - Cloud Operations Suite 1. Implementing Cloud Logging with log sinks 2. Configuring Cloud Monitoring metrics 3. Creating uptime checks and alerts
CI/CD Pipeline Development	26%	- 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. Implementing build automation scripts 5. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.) - 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. Managing secrets in CI/CD pipelines 2. Configuring quality gates and code coverage 3. Implementing shift-left testing
Cloud Infrastructure Automation	24%	- Infrastructure as Code (IaC) 1. Implementing with Terraform 2. Managing infrastructure modules and state 3. Implementing immutable infrastructure patterns - Deployment strategies 1. Rolling updates with Kubernetes 2. Canary releases and progressive rollouts 3. Feature flags with Firebase Remote Config or LaunchDarkly 4. Blue-green deployments - Configuration management 1. Implementing configuration drift detection 2. Managing secrets with Secret Manager 3. Using Ansible for configuration management
Microservices Architecture	14%	- 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. Implementing API versioning strategies 2. Exposing APIs with Cloud Endpoints / Apigee - Service mesh and networking 1. Implementing Anthos Service Mesh / Istio 2. Configuring traffic management and load balancing 3. Implementing service-to-service authentication
Reliability and Site Reliability Engineering (SRE)	24%	- 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 - Incident management 1. Configuring automated incident response 2. Post-incident reviews and blameless postmortems 3. Implementing on-call procedures - Monitoring and observability 1. Implementing distributed tracing with Cloud Trace 2. Setting up alerting policies and incident management 3. Configuring Cloud Monitoring and Logging 4. Creating dashboards for service health visibility

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q158-Q163):

NEW QUESTION # 158
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub.
You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

A. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
B. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
C. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
D. Disable the CI pipeline and revert to manually building and pushing the artifacts.

Answer: B

Explanation:
Explanation
"After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline"- means something wrong on the recent change not with the image registry.

NEW QUESTION # 159
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. You want to prevent these fields from being written in new log entries as quickly as possible. What should you do?

A. Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.
B. Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.
C. Stage log entries to Cloud Storage, and then trigger a Cloud Function to remove the fields and write the entries to Stackdriver via the Stackdriver Logging API.
D. Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.

Answer: D

NEW QUESTION # 160
Your company experiences bugs, outages, and slowness in its production systems. Developers use the production environment for new feature development and bug fixes. Configuration and experiments are done in the production environment, causing outages for users. Testers use the production environment for load testing, which often slows the production systems. You need to redesign the environment to reduce the number of bugs and outages in production and to enable testers to load test new features. What should you do?

A. Create a development environment for writing code and a test environment for configurations, experiments, and load testing.
B. Create an automated testing script in production to detect failures as soon as they occur.
C. Create a development environment with smaller server capacity and give access only to developers and testers.
D. Secure the production environment to ensure that developers can't change it and set up one controlled update per year.

Answer: A

NEW QUESTION # 161
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?

A. Add the auth application-default command as a step in Jenkins before running the Terraform commands.
B. Create a dedicated service account for the Terraform instance. Download and copy the secret key value to the GOOGLE environment variable on the Jenkins server.
C. Confirm that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions.use the Terraform module so that Secret Manager can retrieve credentials.

Answer: C

Explanation:
The correct answer is C.
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1. Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2. By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials. User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials. The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform. Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.

NEW QUESTION # 162
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_datasetYou 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?

A. Create a single aggregated log sink at the organization level.
B. Create a log sink in each project
C. Create two aggregated log sinks at the organization level, and filter by project ID
D. Create an aggregated Iog sink in the Dev and Prod folders

Answer: A

NEW QUESTION # 163
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