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

SectionObjectives
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
          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
              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
                    Optimize performance and continuous delivery- Monitoring and observability
                    • 1. Cloud Monitoring and Logging
                      • 2. Performance tuning and feedback loops
                        - System performance optimization
                        • 1. Scaling strategies and load handling

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                          Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q204-Q209):

                          NEW QUESTION # 204
                          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?

                          Answer: B


                          NEW QUESTION # 205
                          You need to deploy a new service to production. The service needs to automatically scale using a Managed Instance Group (MIG) and should be deployed over multiple regions. The service needs a large number of resources for each instance and you need to plan for capacity. What should you do?

                          Answer: B

                          Explanation:
                          https://cloud.google.com/compute/quotas#understanding_quotas
                          https://cloud.google.com/compute/quotas


                          NEW QUESTION # 206
                          You need to define Service Level Objectives (SLOs) for a high-traffic multi-region web application. Customers expect the application to always be available and have fast response times. Customers are currently happy with the application performance and availability. Based on current measurement, you observe that the 90th percentile of latency is 120ms and the 95th percentile of latency is 275ms over a 28-day window. What latency SLO would you recommend to the team to publish?

                          Answer: D


                          NEW QUESTION # 207
                          Your CTO has asked you to implement a postmortem policy on every incident for internal use. You want to define what a good postmortem is to ensure that the policy is successful at your company. What should you do?
                          Choose 2 answers

                          Answer: A,C

                          Explanation:
                          The correct answers are B and E.
                          A good postmortem should include what caused the incident, how the incident could have been worse, and how to prevent a future occurrence of the incident1. This helps to identify the root cause of the problem, the impact of the incident, and the actions to take to mitigate or eliminate the risk of recurrence.
                          A good postmortem should also include all incident participants in postmortem authoring and share postmortems as widely as possible2. This helps to foster a culture of learning and collaboration, as well as to increase the visibility and accountability of the incident response process.
                          Answer A is incorrect because it assigns blame to a person or team, which goes against the principle of blameless postmortems2. Blameless postmortems focus on finding solutions rather than pointing fingers, and encourage honest and constructive feedback without fear of punishment.
                          Answer C is incorrect because it omits how the incident could have been worse, which is an important factor to consider when evaluating the severity and impact of the incident1. It also avoids naming internal system components, which makes it harder to understand the technical details and root cause of the problem.
                          Answer D is incorrect because it omits how to prevent a future occurrence of the incident, which is the main goal of a postmortem1. It also avoids naming customer information, which may be relevant for understanding the impact and scope of the incident.


                          NEW QUESTION # 208
                          Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes. What should you do?

                          Answer: D

                          Explanation:
                          Explanation
                          The correct answer is A. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
                          The node/ephemeral_storage/used_bytes metric reports the total amount of ephemeral storage used by Pods on each node1. You can use Metrics Explorer to query and visualize this metric and filter it by node name, namespace, or Pod name2. This way, you can identify which Pods are consuming the most ephemeral storage and causing disk pressure on the nodes. You do not need to have execute access to the workloads or nodes to use Metrics Explorer.
                          The other options are incorrect because they require execute access to the workloads or nodes, which you do not have. The df -h and du -sh * commands are Linux commands that can measure disk usage, but you need to run them inside the Pods or on the nodes, which is not possible in your scenario34.


                          NEW QUESTION # 209
                          ......

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