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Professional-Cloud-Devops-Engineer認定試験は、Google Cloud Cloud Technologiesにおける個人のスキルと専門知識を検証するように設計されたGoogle Cloud Certified Examsの1つです。この試験では、継続的な統合と配信、監視と伐採、サイトの信頼性エンジニアリング、セキュリティとコンプライアンスなど、さまざまなトピックをカバーしています。

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Google Professional-Cloud-Devops-Engineer認定試験の資格を得るには、候補者は、DevOpsエンジニアリングの役割で少なくとも3年間の経験があり、Google Cloudを使用して最低1年の経験が必要です。候補者は、PythonやBashなどのスクリプト言語の経験と同様に、ソフトウェア開発の原則と実践を確実に理解することも期待されています。

Google Cloud Certified - Professional Cloud DevOps Engineer Exam 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q21-Q26):

質問 # 21
You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.
B. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.
C. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.
D. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.

正解：C

質問 # 22
You are monitoring a service that uses n2-standard-2 Compute Engine instances that serve large files. Users have reported that downloads are slow. Your Cloud Monitoring dashboard shows that your VMS are running at peak network throughput. You want to improve the network throughput performance. What should you do?

A. Add additional network interface controllers (NICs) to your VMS.
B. Change the machine type for your VMS to n2-standard-8.
C. Deploy a Cloud NAT gateway and attach the gateway to the subnet of the VMS.
D. Deploy the Ops Agent to export additional monitoring metrics.

正解：B

解説：
Explanation
The correct answer is C. Change the machine type for your VMs to n2-standard-8.
According to the Google Cloud documentation, the network throughput performance of a Compute Engine VM depends on its machine type1. The n2-standard-2 machine type has a maximum egress bandwidth of 4 Gbps, which can be a bottleneck for serving large files. By changing the machine type to n2-standard-8, you can increase the maximum egress bandwidth to 16 Gbps, which can improve the network throughput performance and reduce the download time for users. You also need to enable per VM Tier_1 networking performance, which is a feature that allows VMs to achieve higher network performance than the default settings2.
The other options are incorrect because they do not improve the network throughput performance of your VMs. Option A is incorrect because Cloud NAT is a service that allows private IP addresses to access the internet, but it does not increase the network bandwidth or speed3. Option B is incorrect because adding additional network interfaces (NICs) or IP addresses per NIC does not increase ingress or egress bandwidth for a VM1. Option D is incorrect because deploying the Ops Agent can help you monitor and troubleshoot your VMs, but it does not affect the network throughput performance4.

質問 # 23
You are running a web application that connects to an AlloyDB cluster by using a private IP address in your default VPC. You need to run a database schema migration in your CI/CD pipeline by using Cloud Build before deploying a new version of your application. You want to follow Google-recommended security practices. What should you do?

A. Create a service account that has permission to access the database. Configure Cloud Build to use this service account and execute the schema migration script in a private pool.
B. Add the database username and password to Secret Manager. When running the schema migration script, retrieve the username and password from Secret Manager.
C. Set up a Cloud Build private pool to access the database through a static external IP address. Configure the database to only allow connections from this IP address. Execute the schema migration script in the private pool.
D. Add the database username and encrypted password to the application configuration file. Use these credentials in Cloud Build to execute the schema migration script.

正解：A

質問 # 24
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead. What should you do?

A. Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
B. Configure Cloud Profiler, and initialize the cloud.go@gle.com/go/profiler library in the application.
C. Use Cloud Monitoring to assess the App Engine CPU utilization metric.
D. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.

正解：B

解説：
The correct answer is C. Configure Cloud Profiler, and initialize the cloud.google.com/go/profiler library in the application.
According to the Google Cloud documentation, Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications1. Cloud Profiler can help you identify slow paths in your code and optimize the performance of your applications. Cloud Profiler supports applications written in Go that run on App Engine standard environment2. To use Cloud Profiler, you need to configure it in your Google Cloud project and initialize the cloud.google.com/go/profiler library in your application code3. You can then use the Cloud Profiler interface to analyze the profiling data and visualize the results by using flame graphs4. Cloud Profiler has minimal performance impact and management overhead, as it only samples a small fraction of the application activity and does not require any additional infrastructure or agents.
The other options are incorrect because they do not meet the requirements of minimizing performance impact and management overhead. Option A is incorrect because it requires installing a continuous profiling tool into Compute Engine, which is an additional infrastructure that needs to be managed and maintained. Option B is incorrect because it requires periodically running the go tool pprof command against the application instance, which is a manual and disruptive process that can affect the application performance. Option D is incorrect because it only uses Cloud Monitoring to assess the App Engine CPU utilization metric, which is not enough to identify slow paths in the code or optimize the application performance.
Reference:
Cloud Profiler documentation, Overview. Profiling Go applications, Supported environments. Profiling Go applications, Using Cloud Profiler. Analyzing data, Analyzing data.

質問 # 25
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to the production environment. A recent security audit alerted your team that the code pushed to production could contain vulnerabilities and that the existing tooling around virtual machine (VM) vulnerabilities no longer applies to the containerized environment. You need to ensure the security and patch level of all code running through the pipeline. What should you do?

A. Reconfigure the existing operating system vulnerability software to exist inside the container.
B. Implement static code analysis tooling against the Docker files used to create the containers.
C. Configure the containers in the build pipeline to always update themselves before release.
D. Set up Container Analysis to scan and report Common Vulnerabilities and Exposures.

正解：B

解説：
https://cloud.google.com/binary-authorization
Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or Cloud Run. With Binary Authorization, you can require images to be signed by trusted authorities during the development process and then enforce signature validation when deploying. By enforcing validation, you can gain tighter control over your container environment by ensuring only verified images are integrated into the build-and-release process.

質問 # 26
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