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

Section	Objectives
Topic 1: Optimize performance and continuous delivery	- Monitoring and observability 1. Performance tuning and feedback loops 2. Cloud Monitoring and Logging - System performance optimization 1. Scaling strategies and load handling
Topic 2: Implement security and compliance	- Secure CI/CD pipelines 1. Secret and credential management 2. IAM and least privilege access - Compliance and governance 1. Audit logging and policy enforcement
Topic 3: Develop and implement CI/CD pipelines	- Automate build, test, and deployment processes 1. Deployment automation strategies 2. Release management practices - Build and manage CI/CD pipelines using Google Cloud tools 1. Cloud Build pipeline design 2. Artifact repository management
Topic 4: Implement site reliability engineering (SRE) practices	- Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies - Incident management and postmortems 1. Alerting and on-call practices

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q17-Q22):

NEW QUESTION # 17
You need to build a CI/CD pipeline for a containerized application in Google Cloud Your development team uses a central Git repository for trunk-based development You want to run all your tests in the pipeline for any new versions of the application to improve the quality What should you do?

A. 1. Trigger Cloud Build to build the application container and run unit tests with the container2. If unit tests are successful, deploy the application container to a testing environment, and run integration tests3. If the integration tests are successful the pipeline deploys the application container to the production environment After that, run acceptance tests
B. 1. Trigger Cloud Build to run unit tests when the code is pushed If all unit tests are successful, build and push the application container to a central registry.2. Trigger Cloud Build to deploy the container to a testing environment, and run integration tests and acceptance tests3. If all tests are successful the pipeline deploys the application to the production environment and runs smoke tests
C. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repositoryIf all tests are successful build a container2. Trigger Cloud Build to deploy the application container to a testing environment, and run integrationtests and acceptance tests3. If all tests are successful tag the code as production ready Trigger Cloud Build to build and deploy the application container to the production environment
D. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repository2. Trigger Cloud Build to build the application container Deploy the application container to a testing environment, and run integration tests3. If the integration tests are successful deploy the application container to your production environment. and run acceptance tests

Answer: B

Explanation:
The best option for building a CI/CD pipeline for a containerized application in Google Cloud is to trigger Cloud Build to run unit tests when the code is pushed, if all unit tests are successful, build and push the application container to a central registry, trigger Cloud Build to deploy the container to a testing environment, and run integration tests and acceptance tests, and if all tests are successful, the pipeline deploys the application to the production environment and runs smoke tests. This option follows the best practices for CI/CD pipelines, such as running tests at different stages of the pipeline, using a central registry for storing and managing containers, deploying to different environments, and using Cloud Build as a unified tool for building, testing, and deploying.

NEW QUESTION # 18
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. Use Cloud Build to include the release version tag in the application image.
B. Supply the source control tag as a parameter within the image name.
C. Reference the image digest in the source control tag.
D. Use GCR digest versioning to match the image to the tag in source control.

Answer: B

Explanation:
Explanation
https://cloud.google.com/container-registry/docs/pushing-and-pulling

NEW QUESTION # 19
You support a popular mobile game application deployed on Google Kubernetes Engine (GKE) across several Google Cloud regions. Each region has multiple Kubernetes clusters. You receive a report that none of the users in a specific region can connect to the application. You want to resolve the incident while following Site Reliability Engineering practices. What should you do first?

A. Add an extra node pool that consists of high memory and high CPU machine type instances to the cluster.
B. Use Stackdriver Monitoring to check for a spike in CPU or memory usage for the affected region.
C. Use Stackdriver Logging to filter on the clusters in the affected region, and inspect error messages in the logs.
D. Reroute the user traffic from the affected region to other regions that don't report issues.

Answer: C

NEW QUESTION # 20
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

A. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.
B. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
C. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.
D. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.

Answer: A

Explanation:
https://sre.google/workbook/implementing-slos/
In the SRE principles book, it's recommended treating the SLI as the ratio of two numbers: the number of good events divided by the total number of events. For example: Number of successful HTTP requests / total HTTP requests (success rate)

NEW QUESTION # 21
You are running an experiment to see whether your users like a new feature of a web application. Shortly after deploying the feature as a canary release, you receive a spike in the number of 500 errors sent to users, and your monitoring reports show increased latency. You want to quickly minimize the negative impact on users.
What should you do first?

A. Trace the origin of 500 errors and the root cause of increased latency.
B. Start monitoring latency, traffic, errors, and saturation.
C. Record data for the postmortem document of the incident.
D. Roll back the experimental canary release.

Answer: D

NEW QUESTION # 22
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