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

Topic	Details
Topic 1	Implementing service monitoring strategies: This topic covers structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging. Its sub-topics include coverage of metrics with Cloud Monitoring, dashboards and alerts in Cloud Monitoring, Cloud Logging platform, and logging and monitoring access controls.
Topic 2	Bootstrapping a Google Cloud organization for DevOps: It discusses the overall resource hierarchy for an organization, infrastructure as code, CI CD architecture stack in Google Cloud, hybrid, and multi-cloud environments. Moreover, the topic focuses on multiple environments including staging and production.
Topic 3	Building and implementing CI CD pipelines for a service: Management and designing of CI CD pipelines, implementation of CI CD pipelines, management of CI CD configuration, and secrets are discussed in this paper. Moreover, it focuses on storage methods and key rotation services, and finally securing the CI CD deployment pipeline.
Topic 4	Optimizing the service performance: It delves into the identification of service performance issues, implementation of debugging tools in Google Cloud, and optimization of resource utilization and costs.
Topic 5	Applying site reliability engineering practices to a service: It deals with velocity, and reliability of the service, service lifecycle, healthy communication, and collaboration for operations. The topic also discusses mitigation of incident impact on users and conducting a postmortem.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q138-Q143):

NEW QUESTION # 138
You recently migrated an ecommerce application to Google Cloud. You now need to prepare the application for the upcoming peak traffic season. You want to follow Google-recommended practices. What should you do first to prepare for the busy season?

A. Migrate the application to Cloud Run, and use autoscaling.
B. Pre-provision the additional compute power that was used last season, and expect growth.
C. Create a Terraform configuration for the application's underlying infrastructure to quickly deploy to additional regions.
D. Load test the application to profile its performance for scaling.

Answer: D

Explanation:
The first thing you should do to prepare your ecommerce application for the upcoming peak traffic season is to load test the application to profile its performance for scaling. Load testing is a process of simulating high traffic or user demand on your application and measuring how it responds.Load testing can help you identify any bottlenecks, errors, or performance issues that might affect your application during the busy season1.Load testing can also help you determine the optimal scaling strategy for your application, such as horizontal scaling (adding more instances) or vertical scaling (adding more resources to each instance)2.
There are different tools and methods for load testing your ecommerce application on Google Cloud, depending on the type and complexity of your application.For example, you can use Cloud Load Balancing to distribute traffic across multiple instances of your application, and use Cloud Monitoring to measure the latency, throughput, and error rate of your application3.You can also use Cloud Functions or Cloud Run to create serverless load generators that can simulate user requests and send them to your application4.
Alternatively, you can use third-party tools such as Apache JMeter or Locust to create and run load tests on your application.
By load testing your ecommerce application before the peak traffic season, you can ensure that your application is ready to handle the expected load and provide a good user experience. You can also use the results of your load tests to plan and implement other steps to prepare your application for the busy season, such as migrating to a more scalable platform, creating a Terraform configuration for deploying to additional regions, or pre-provisioning additional compute power.
References:
1:Load Testing 101: How To Test Website Performance | BlazeMeter
2: Scaling applications | Google Cloud
3:Load testing using Google Cloud | Solutions | Google Cloud
4: Serverless load testing using Cloud Functions | Solutions | Google Cloud

NEW QUESTION # 139
You are using Jenkins to orchestrate your CI/CD pipelines deploying your applications to GKE and on-premises VMs. After expanding your on-premises infrastructure, all resource utilization is normal, but you notice that initiating on-premises deployments is taking longer than expected. You need to accelerate the initiation of on-premises deployments. What should you do?

A. Configure Jenkins to use an artifact repository in your on-premises environment.
B. Increase the number of Jenkins executor threads.
C. Implement a blue-green deployment strategy for your on-premises VMs.
D. Upgrade your on-premises VMs to have faster CPUs and more memory.

Answer: A

NEW QUESTION # 140
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.
What should you do?

A. Publish various metrics from the application directly to the Stackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
B. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
C. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
D. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.

Answer: C

NEW QUESTION # 141
You are reviewing your deployment pipeline in Google Cloud Deploy You must reduce toil in the pipeline and you want to minimize the amount of time it takes to complete an end-to-end deployment What should you do?
Choose 2 answers

A. Automate promotion approvals from the development environment to the test environment
B. Use a script to automate the creation of the deployment pipeline in Google Cloud Deploy
C. Divide the automation steps into smaller tasks
D. Add more engineers to finish the manual steps.
E. Create a trigger to notify the required team to complete the next step when manual intervention is required

Answer: A,E

Explanation:
Explanation
The best options for reducing toil in the pipeline and minimizing the amount of time it takes to complete an end-to-end deployment are to create a trigger to notify the required team to complete the next step when manual intervention is required and to automate promotion approvals from the development environment to the test environment. A trigger is a resource that initiates a deployment when an event occurs, such as a code change, a schedule, or a manual request. You can create a trigger to notify the required team to complete the next step when manual intervention is required by using Cloud Build or Cloud Functions. This way, you can reduce the waiting time and human errors in the pipeline. A promotion approval is a process that allows you to approve or reject a deployment from one environment to another, such as from development to test. You can automate promotion approvals from the development environment to the test environment by using Google Cloud Deploy or Cloud Build. This way, you can speed up the deployment process and avoid manual steps.

NEW QUESTION # 142
You are the Site Reliability Engineer responsible for managing your company's data services and products.
You regularly navigate operational challenges, such as unpredictable data volume and high cost, with your company's data ingestion processes. You recently learned that a new data ingestion product will be developed in Google Cloud. You need to collaborate with the product development team to provide operational input on the new product. What should you do?

A. Deploy the prototype product in a test environment, run a load test, and share the results with the product development team.
B. When the new product is used by at least one internal customer in production, share error logs and monitoring metrics with the product development team.
C. Review the design of the product with the product development team to provide feedback early in the design phase.
D. When the initial product version passes the quality assurance phase and compliance assessments, deploy the product to a staging environment. Share error logs and performance metrics with the product development team.

Answer: C

Explanation:
Explanation
The correct answer is D. Review the design of the product with the product development team to provide feedback early in the design phase.
According to the Google Cloud DevOps best practices, a Site Reliability Engineer (SRE) should collaborate with the product development team from the beginning of the product lifecycle, not just after the product is deployed or tested. This way, the SRE can provide operational input on the product design, such as scalability, reliability, security, and cost efficiency. The SRE can also help define service level objectives (SLOs) and service level indicators (SLIs) for the product, as well as monitoring and alerting strategies. By collaborating early and often, the SRE and the product development team can ensure that the product meets the operational requirements and expectations of the customers.

NEW QUESTION # 143
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