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Google Professional-Cloud-DevOps-Engineer certification exam is a rigorous and comprehensive assessment of the candidate's skills and knowledge in cloud DevOps engineering. It covers a wide range of topics, including cloud infrastructure automation, containerization, CI/CD pipelines, monitoring and logging, security and compliance, and more. Professional-Cloud-DevOps-Engineer Exam is designed to test the candidate's ability to design, implement, and manage cloud-based DevOps solutions that meet the needs of modern organizations.
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How to book Google Professional Cloud DevOps Engineer Exams
The registration for the Google Professional Cloud DevOps Engineer exam follows the steps given below.
- Step 1: Visit the Google Cloud Webassessor Website
- Step 2: Sign-in or sign up to your Google Cloud Webassessor account
- Step 3: Search for the exam name Google Professional Cloud DevOps Engineer
- Step 4: Take the date of the exam, choose the exam center, and make further payment using payment methods like credit/debit, etc.
After registering for the exam, prepare from the Professional Cloud DevOps Engineer exam dumps and make sure to take Professional Cloud DevOps Engineer practice exam so you know the exam format in advance. This will give you an advantage over other candidates.
Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q64-Q69):
NEW QUESTION # 64
You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below
The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?
- A. Update the Deployment ape-green to use the previous version of the application
- B. Update the Deployment app-blue to use the new version of the application
- C. Change the selector on the Service app-2vc to app: my-app.
- D. Change the selector on the Service app-svc to app: my-app, version: blue
Answer: D
Explanation:
Explanation
The best option for mitigating the incident impact on users and enabling the developers to troubleshoot the issue is to change the selector on the Service app-svc to app: my-app, version: blue. A Service is a resource that defines how to access a set of Pods. A selector is a field that specifies which Pods are selected by the Service. By changing the selector on the Service app-svc to app: my-app, version: blue, you can ensure that the Service only routes traffic to the Pods that have both labels app: my-app and version: blue. These Pods belong to the Deployment app-blue, which uses the previous version of the application. This way, you can mitigate the incident impact on users by switching back to the working version of the application. You can also enable the developers to troubleshoot the issue with the new version of the application in the Deployment app-green without affecting users.
NEW QUESTION # 65
You are the Operations Lead for an ongoing incident with one of your services. The service usually runs at around 70% capacity. You notice that one node is returning 5xx errors for all requests. There has also been a noticeable increase in support cases from customers. You need to remove the offending node from the load balancer pool so that you can isolate and investigate the node. You want to follow Google-recommended practices to manage the incident and reduce the impact on users. What should you do?
- A. 1. Communicate your intent to the incident team.2. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately.3. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
- B. 1 . Drain traffic from the unhealthy node and remove the old node from service.2. Add a new node to the pool, wait for the new node to report as healthy, and then serve traffic to the new node.3. Monitor traffic to ensure that the pool is healthy and is handling traffic appropriately.4. Communicate your actions to the incident team.
- C. 1 . Drain traffic from the unhealthy node and remove the node from service.2. Monitor traffic to ensure that the error is resolved and that the other nodes in the pool are handling the traffic appropriately.3. Scale the pool as necessary to handle the new load.4. Communicate your actions to the incident team.
- D. 1. Communicate your intent to the incident team.2. Add a new node to the pool, and wait for the new node to report as healthy.3. When traffic is being served on the new node, drain traffic from the unhealthy node, and remove the old node from service.
Answer: A
NEW QUESTION # 66
You are designing a system with three different environments: development, quality assurance (QA), and production.
Each environment will be deployed with Terraform and has a Google Kubemetes Engine (GKE) cluster created so that application teams can deploy their applications. Anthos Config Management will be used and templated to deploy infrastructure level resources in each GKE cluster. All users (for example, infrastructure operators and application owners) will use GitOps. How should you structure your source control repositories for both Infrastructure as Code (laC) and application code?
- A. Cloud Infrastructure (Terraform) repository is shared: different directories are different environments GKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated:
different branches are different environments Application (app source code) repositories are separated:
different branches are different features - B. Cloud Infrastructure (Terraform) repositories are separated: different branches are different environments GKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated: different overlay directories are different environments Application (app source code) repositories are separated: different branches are different features
- C. Cloud Infrastructure (Terraform) repository is shared: different directories are different environments GKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: different overlay directories are different environments Application (app source code) repositories are separated:
different branches are different features - D. Cloud Infrastructure (Terraform) repository is shared: different branches are different environments GKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: different overlay directories are different environments Application (app source code) repository is shared:
different directories are different features
Answer: A
Explanation:
Explanation
The correct answer is B. Cloud Infrastructure (Terraform) repository is shared: different directories are different environments. GKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated: different branches are different environments. Application (app source code) repositories are separated: different branches are different features.
This answer follows the best practices for using Terraform and Anthos Config Management with GitOps, as described in the following sources:
For Terraform, it is recommended to use a single repository for all environments, and use directories to separate them. This way, you can reuse the same Terraform modules and configurations across environments, and avoid code duplication and drift. You can also use Terraform workspaces to isolate the state files for each environment12.
For Anthos Config Management, it is recommended to use separate repositories for each environment, and use branches to separate the clusters within each environment. This way, you can enforce different policies and configurations for each environment, and use pull requests to promote changes across environments. You can also use Kustomize to create overlays for each cluster that apply specific patches or customizations34.
For application code, it is recommended to use separate repositories for each application, and use branches to separate the features or bug fixes for each application. This way, you can isolate the development and testing of each application, and use pull requests to merge changes into the main branch. You can also use tags or labels to trigger deployments to different environments5 .
References:
1: Best practices for using Terraform | Google Cloud
2: Terraform Recommended Practices - Part 1 | Terraform - HashiCorp Learn
3: Deploy Anthos on GKE with Terraform part 1: GitOps with Config Sync | Google Cloud Blog
4: Using Kustomize with Anthos Config Management | Anthos Config Management Documentation | Google Cloud
5: Deploy Anthos on GKE with Terraform part 3: Continuous Delivery with Cloud Build | Google Cloud Blog GitOps-style continuous delivery with Cloud Build | Cloud Build Documentation | Google Cloud
NEW QUESTION # 67
You are building and running client applications in Cloud Run and Cloud Functions Your client requires that all logs must be available for one year so that the client can import the logs into their logging service You must minimize required code changes What should you do?
- A. Update all images in Cloud Run and all functions in Cloud Functions to send logs to both Cloud Logging and the client's logging service Ensure that all the ports required to send logs are open in the VPC firewall
- B. Create a Pub/Sub topic subscription and logging sink Configure the logging sink to send all logs into the topic Give your client access to the topic to retrieve the logs
- C. Create a storage bucket and appropriate VPC firewall rules Update all images in Cloud Run and all functions in Cloud Functions to send logs to a file within the storage bucket
- D. Create a logs bucket and logging sink. Set the retention on the logs bucket to 365 days Configure the logging sink to send logs to the bucket Give your client access to the bucket to retrieve the logs
Answer: D
Explanation:
The best option for storing all logs for one year and minimizing required code changes is to create a logs bucket and logging sink, set the retention on the logs bucket to 365 days, configure the logging sink to send logs to the bucket, and give your client access to the bucket to retrieve the logs. A logs bucket is a Cloud Storage bucket that is used to store logs from Cloud Logging. A logging sink is a resource that defines where log entries are sent, such as a logs bucket, BigQuery dataset, or Pub/Sub topic. You can create a logs bucket and logging sink in Cloud Logging and set the retention on the logs bucket to 365 days. This way, you can ensure that all logs are stored for one year and protected from deletion. You can also configure the logging sink to send logs from Cloud Run and Cloud Functions to the logs bucket without any code changes. You can then give your client access to the logs bucket by using IAM policies or signed URLs.
NEW QUESTION # 68
You support a high-traffic web application that runs on Google Cloud Platform (GCP). You need to measure application reliability from a user perspective without making any engineering changes to it. What should you do?
Choose 2 answers
- A. Use current and historic Request Logs to trace customer interaction with the application.
- B. Create new synthetic clients to simulate a user journey using the application.
- C. Analyze the web proxy logs only and capture response time of each request.
- D. Modify the code to capture additional information for user interaction.
- E. Review current application metrics and add new ones as needed.
Answer: A,C
Explanation:
https://cloud.google.com/architecture/adopting-slos?hl=en
NEW QUESTION # 69
......
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