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

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

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                          Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q152-Q157):

                          NEW QUESTION # 152
                          You are investigating issues in your production application that runs on Google Kubernetes Engine (GKE).
                          You determined that the source Of the issue is a recently updated container image, although the exact change in code was not identified. The deployment is currently pointing to the latest tag. You need to update your cluster to run a version of the container that functions as intended. What should you do?

                          Answer: A


                          NEW QUESTION # 153
                          You have an application that runs in Google Kubernetes Engine (GKE). The application consists of several microservices that are deployed to GKE by using Deployments and Services One of the microservices is experiencing an issue where a Pod returns 403 errors after the Pod has been running for more than five hours Your development team is working on a solution but the issue will not be resolved for a month You need to ensure continued operations until the microservice is fixed You want to follow Google-recommended practices and use the fewest number of steps What should you do?

                          Answer: D


                          NEW QUESTION # 154
                          You are investigating issues in your production application that runs on Google Kubernetes Engine (GKE). You determined that the source Of the issue is a recently updated container image, although the exact change in code was not identified. The deployment is currently pointing to the latest tag. You need to update your cluster to run a version of the container that functions as intended. What should you do?

                          Answer: A


                          NEW QUESTION # 155
                          Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
                          * Mean Time to Detect (MUD} in minutes
                          * Mean Time to Repair (MTTR) in minutes
                          * Mean Time Between Failure (MTBF) in days
                          * User Impact Percentage
                          The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

                          Answer: B

                          Explanation:
                          Explanation
                          https://www.atlassian.com/incident-management/kpis/common-metrics
                          https://linkedin.github.io/school-of-sre/


                          NEW QUESTION # 156
                          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?

                          Answer: B

                          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 # 157
                          ......

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