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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: 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 3: Develop and implement CI/CD pipelines- Build and manage CI/CD pipelines using Google Cloud tools
              • 1. Cloud Build pipeline design
                • 2. Artifact repository management
                  - Automate build, test, and deployment processes
                  • 1. Release management practices
                    • 2. Deployment automation strategies
                      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 (Q88-Q93):

                          NEW QUESTION # 88
                          You support an application that stores product information in cached memory. For every cache miss, an entry is logged in Stackdriver Logging. You want to visualize how often a cache miss happens over time. What should you do?

                          Answer: C

                          Explanation:
                          Explanation
                          https://cloud.google.com/logging/docs/logs-based-metrics#counter-metric


                          NEW QUESTION # 89
                          You are implementing a CI'CD pipeline for your application in your company s multi-cloud environment Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes Which solution stack should you use'?

                          Answer: B

                          Explanation:
                          Explanation
                          Cloud Build is a fully managed continuous integration and continuous delivery (CI/CD) service that helps you automate your builds, tests, and deployments. Google Cloud Deploy is a service that automates the deployment of your applications to Google Kubernetes Engine (GKE).
                          Together, Cloud Build and Google Cloud Deploy can be used to build and deploy your application's custom Compute Engine images to your current environment and to other cloud providers in the future.
                          Here are the steps involved in using Cloud Build and Google Cloud Deploy to implement a CI/CD pipeline for your application:
                          Create a Cloud Build trigger that fires whenever a change is made to your application's code.
                          In the Cloud Build trigger, configure Cloud Build to build your application's Docker image.
                          Create a Google Cloud Deploy configuration file that specifies how to deploy your application's Docker image to GKE.
                          In Google Cloud Deploy, create a deployment that uses your configuration file.
                          Once you have created the Cloud Build trigger and Google Cloud Deploy configuration file, any changes made to your application's code will trigger Cloud Build to build a new Docker image. Google Cloud Deploy will then deploy the new Docker image to GKE.
                          This solution stack is adaptable to future changes because it uses a cloud-agnostic approach. Cloud Build can be used to build Docker images for any cloud provider, and Google Cloud Deploy can be used to deploy Docker images to any Kubernetes cluster.
                          The other solution stacks are not as adaptable to future changes. For example, solution stack A (Cloud Build with Packer) is limited to building Docker images for Compute Engine. Solution stack C (Google Kubernetes Engine with Google Cloud Deploy) is limited to deploying Docker images to GKE. Solution stack D (Cloud Build with kpt) is a newer solution that is not yet as mature as Cloud Build and Google Cloud Deploy.
                          Overall, the best solution stack for implementing a CI/CD pipeline for your application in a multi-cloud environment is Cloud Build with Google Cloud Deploy. This solution stack is fully managed, cloud-agnostic, and adaptable to future changes.


                          NEW QUESTION # 90
                          Your application artifacts are being built and deployed via a CI/CD pipeline. You want the CI/CD pipeline to securely access application secrets. You also want to more easily rotate secrets in case of a security breach. What should you do?

                          Answer: D


                          NEW QUESTION # 91
                          You support a large service with a well-defined Service Level Objective (SLO). The development team deploys new releases of the service multiple times a week. If a major incident causes the service to miss its SLO, you want the development team to shift its focus from working on features to improving service reliability. What should you do before a major incident occurs?

                          Answer: C

                          Explanation:
                          Reason : Incident has not occurred yet, even when development team is already pushing new features multiple times a week. The option A says, to define an error budget "policy", not to define error budget(It is already present). Just simple means to bring in all stakeholders, and decide how to consume the error budget effectively that could bring balance between feature deployment and reliability.
                          The goals of this policy are to: -- Protect customers from repeated SLO misses -- Provide an incentive to balance reliability with other features https://sre.google/workbook/error-budget-policy/


                          NEW QUESTION # 92
                          You are managing an application that runs in Compute Engine The application uses a custom HTTP server to expose an API that is accessed by other applications through an internal TCP/UDP load balancer A firewall rule allows access to the API port from 0.0.0-0/0. You need to configure Cloud Logging to log each IP address that accesses the API by using the fewest number of steps What should you do Bret?

                          Answer: C

                          Explanation:
                          The best option for configuring Cloud Logging to log each IP address that accesses the API by using the fewest number of steps is to enable logging on the firewall rule. A firewall rule is a rule that controls the traffic to and from your Compute Engine instances. You can enable logging on a firewall rule to capture information about the traffic that matches the rule, such as source and destination IP addresses, protocols, ports, and actions. You can use Cloud Logging to view and export the firewall logs to other destinations, such as BigQuery, for further analysis.


                          NEW QUESTION # 93
                          ......

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