Professional-Cloud-DevOps-Engineerテキスト、Professional-Cloud-DevOps-Engineer模擬練習

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

SectionObjectives
Topic 1: Optimize performance and continuous delivery- System performance optimization
  • 1. Scaling strategies and load handling
    - Monitoring and observability
    • 1. Performance tuning and feedback loops
      • 2. Cloud Monitoring and Logging
        Topic 2: Develop and implement CI/CD pipelines- Automate build, test, and deployment processes
        • 1. Release management practices
          • 2. Deployment automation strategies
            - Build and manage CI/CD pipelines using Google Cloud tools
            • 1. Artifact repository management
              • 2. Cloud Build pipeline design
                Topic 3: Implement security and compliance- Secure CI/CD pipelines
                • 1. IAM and least privilege access
                  • 2. Secret and credential management
                    - Compliance and governance
                    • 1. Audit logging and policy enforcement
                      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 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q162-Q167):

                          質問 # 162
                          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?

                          正解：C


                          質問 # 163
                          Your company operates in a highly regulated domain that requires you to store all organization logs for seven years You want to minimize logging infrastructure complexity by using managed services You need to avoid any future loss of log capture or stored logs due to misconfiguration or human error What should you do?

                          正解：A

                          解説：
                          The best option for storing all organization logs for seven years and avoiding any future loss of log capture or stored logs due to misconfiguration or human error is to use Cloud Logging to configure an aggregated sink at the organization level to export all logs into Cloud Storage with a seven-year retention policy and Bucket Lock. Cloud Logging is a service that allows you to collect and manage logs from your Google Cloud resources and applications. An aggregated sink is a sink that collects logs from multiple sources, such as projects, folders, or organizations. You can use Cloud Logging to configure an aggregated sink at the organization level to export all logs into Cloud Storage, which is a service that allows you to store and access data in Google Cloud. A retention policy is a policy that specifies how long objects in a bucket are retained before they are deleted. Bucket Lock is a feature that allows you to lock a retention policy on a bucket and prevent it from being reduced or removed. You can use Cloud Storage with a seven-year retention policy and Bucket Lock to ensure that your logs are stored for seven years and protected from accidental or malicious deletion.


                          質問 # 164
                          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?

                          正解：D


                          質問 # 165
                          Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?

                          正解：D

                          解説：
                          Explanation
                          https://cloud.google.com/kubernetes-engine/docs/tutorials/autoscaling-metrics The Google Cloud HTTP Load Balancer (GCLB) provides metrics on the number of requests and the response latency for each backend service. These metrics can be used as custom metrics for the horizontal pod autoscaler (HPA) to scale the deployment based on the load. This is the correct solution to use an appropriate SLI for scaling.


                          質問 # 166
                          You are configuring connectivity across Google Kubernetes Engine (GKE) clusters in different VPCs You notice that the nodes in Cluster A are unable to access the nodes in Cluster B You suspect that the workload access issue is due to the network configuration You need to troubleshoot the issue but do not have execute access to workloads and nodes You want to identify the layer at which the network connectivity is broken What should you do?

                          正解：B

                          解説：
                          Explanation
                          The best option for troubleshooting the issue without having execute access to workloads and nodes is to use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B. Network Connectivity Center is a service that allows you to create, manage, and monitor network connectivity across Google Cloud, hybrid, and multi-cloud environments. You can use Network Connectivity Center to perform a Connectivity Test, which is a feature that allows you to test the reachability and latency between two endpoints, such as GKE clusters, VM instances, or IP addresses. By using Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B, you can identify the layer at which the network connectivity is broken, such as the firewall, routing, or load balancing.


                          質問 # 167
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