Pass Your Google Professional-Cloud-DevOps-Engineer Exam with Correct 208 Questions and Answers
Latest [May 27, 2026] 2026 Realistic Verified Professional-Cloud-DevOps-Engineer Dumps
NEW QUESTION # 74
Your application runs on Google Cloud Platform (GCP). You need to implement Jenkins for deploying application releases to GCP. You want to streamline the release process, lower operational toil, and keep user data secure. What should you do?
- A. Implement Jenkins on Google Cloud Functions.
- B. Implement Jenkins on Compute Engine virtual machines.
- C. Implement Jenkins on Kubernetes on-premises
- D. Implement Jenkins on local workstations.
Answer: B
Explanation:
Explanation
Your application runs on Google Cloud Platform (GCP). You need to implement Jenkins for deploying application releases to GCP. You want to streamline the release process, lower operational toil, and keep user data secure. What should you do?
https://plugins.jenkins.io/google-compute-engine/
NEW QUESTION # 75
Your company uses a CI/CD pipeline with Cloud Build and Artifact Registry to deploy container images to Google Kubernetes Engine (GKE). Images are tagged with the latest commit hash and promoted to production after successful testing in the development and pre-production environments. A recent production deployment caused the application to fail due to untested integration functionality, requiring a disruptive manual rollback. During the rollback, you noticed many old and unused container images accumulating in Artifact Registry. You need to improve rollout and rollback management and clean up the old container images. What should you do?
- A. Set up a rollback pipeline in Cloud Build, and implement an Artifact Registry cleanup policy.
- B. Deploy Cloud Service Mesh across the GKE clusters, and manually clean up Artifact Registry images.
- C. Adopt Cloud Deploy for managing deployments, and implement an Artifact Registry cleanup policy.
- D. Adopt Cloud Deploy for managing deployments, and schedule a Cloud Build job for container image cleanup.
Answer: C
NEW QUESTION # 76
Your company follows Site Reliability Engineering practices. You are the Incident Commander for a new. customer-impacting incident. You need to immediately assign two incident management roles to assist you in an effective incident response. What roles should you assign?
Choose 2 answers
- A. Operations Lead
- B. Communications Lead
- C. Engineering Lead
- D. Customer Impact Assessor
- E. External Customer Communications Lead
Answer: A,D
NEW QUESTION # 77
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?
- A. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using their personal private key.
- B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
- C. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) with a service account JSON key stored as a Kubernetes Secret.
- D. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using a key stored in Cloud Key Management Service (Cloud KMS).
Answer: B
Explanation:
The correct answer is B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
According to the Google Cloud documentation, Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or Cloud Run1.
Binary Authorization uses attestations to certify that a specific image has completed a previous stage in the CI
/CD pipeline, such as passing a load test2.Attestations are signed by private keys that are associated with attestors, which are entities that verify the attestations3.To follow Google-recommended practices, you should store your private keys in Cloud Key ManagementService (Cloud KMS), which is a secure and scalable service for managing cryptographic keys4.You should also use Workload Identity, which is a feature that allows Kubernetes service accounts to act as Google service accounts, to authenticate to Cloud KMS and sign attestations without having to manage or expose service account keys5.
The other options are incorrect because they do not follow Google-recommended practices. Option A and option D require human intervention to sign the attestations, which is not scalable or automated. Option C exposes the service account JSON key as a Kubernetes Secret, which is less secure than using Workload Identity.
NEW QUESTION # 78
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. Analyze the web proxy logs only and capture response time of each request.
- B. Modify the code to capture additional information for user interaction.
- C. Create new synthetic clients to simulate a user journey using the application.
- D. Review current application metrics and add new ones as needed.
- E. Use current and historic Request Logs to trace customer interaction with the application.
Answer: B,C
NEW QUESTION # 79
You are performing a semi-annual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP), using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?
- A. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough.
- B. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
- C. Because you are deployed on GKE and are using a cluster autoscaler, your GKE cluster will scale automatically regardless of growth rate.
- D. Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify your expected resource needs.
Answer: C
NEW QUESTION # 80
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'?
- A. Cloud Build with Google Cloud Deploy
- B. Cloud Build with kpt
- C. Cloud Build with Packer
- D. Google Kubernetes Engine with Google Cloud Deploy
Answer: A
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 # 81
Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs and you must ensure that the Ops Agent remains up to date. What should you do?
- A. Use the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory
- B. Use the gcloud CLI to create an Agent Policy.
- C. Install the Ops Agent on the Compute Engine image by using a startup script
- D. Select all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard Then select Install agents
Answer: B
Explanation:
Explanation
The best option for configuring all current and future Compute Engine instances to collect system logs and ensure that the Ops Agent remains up to date is to use the gcloud CLI to create an Agent Policy. An Agent Policy is a resource that defines how Ops Agents are installed and configured on VM instances that match certain criteria, such as labels or zones. Ops Agents are software agents that collect metrics and logs from VM instances and send them to Cloud Operations products, such as Cloud Monitoring and Cloud Logging. By creating an Agent Policy, you can ensure that all current and future VM instances that match the policy criteria will have the Ops Agent installed and updated automatically. This way, you can collect system logs from all VM instances and use them to generate dashboards in Cloud Operations.
NEW QUESTION # 82
Your company recently migrated to Google Cloud. You need to design a fast, reliable, and repeatable solution for your company to provision new projects and basic resources in Google Cloud. What should you do?
- A. Write a script by using the gcloud CLI that passes the appropriate parameters from the request. Save the script in a Git repository.
- B. Use the Google Cloud console to create projects.
- C. Use the Terraform repositories from the Cloud Foundation Toolkit. Apply the code with appropriate parameters to create the Google Cloud project and related resources.
- D. Write a Terraform module and save it in your source control repository. Copy and run the apply command to create the new project.
Answer: C
Explanation:
Explanation
Terraform is an open-source tool that allows you to define and provision infrastructure as code1. Terraform can be used to create and manage Google Cloud resources, such as projects, networks, and services2. The Cloud Foundation Toolkit is a set of open-source Terraform modules and tools that provide best practices and guidance for deploying Google Cloud infrastructure3. The Cloud Foundation Toolkit includes Terraform repositories for creating Google Cloud projects and related resources, such as IAM policies, APIs, service accounts, and billing4. By using the Terraform repositories from the Cloud Foundation Toolkit, you can design a fast, reliable, and repeatable solution for your company to provision new projects and basic resources in Google Cloud. You can also customize the Terraform code to suit your specific needs and preferences.
NEW QUESTION # 83
You work for a global organization and are running a monolithic application on Compute Engine You need to select the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps You want to use historical system metncs to identify the machine type for the application to use You want to follow Google-recommended practices What should you do?
- A. Use the Recommender API and apply the suggested recommendations
- B. Install the Ops Agent in a fleet of VMs by using the gcloud CLI
- C. Create an Agent Policy to automatically install Ops Agent in all VMs
- D. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
Answer: A
Explanation:
The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations.
The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.
NEW QUESTION # 84
Your company uses a CI/CD pipeline with Cloud Build and Artifact Registry to deploy container images to Google Kubernetes Engine (GKE). Images are tagged with the latest commit hash and promoted to production after successful testing in the development and pre-production environments. A recent production deployment caused the application to fail due to untested integration functionality, requiring a disruptive manual rollback.
During the rollback, you noticed many old and unused container images accumulating in Artifact Registry.
You need to improve rollout and rollback management and clean up the old container images. What should you do?
- A. Set up a rollback pipeline in Cloud Build, and implement an Artifact Registry cleanup policy.
- B. Deploy Cloud Service Mesh across the GKE clusters, and manually clean up Artifact Registry images.
- C. Adopt Cloud Deploy for managing deployments, and implement an Artifact Registry cleanup policy.
- D. Adopt Cloud Deploy for managing deployments, and schedule a Cloud Build job for container image cleanup.
Answer: C
Explanation:
Comprehensive and Detailed Explanation:
Cloud Deploy is a GCP-native managed CI/CD tool for reliable and automated releases across environments.
Artifact Registry Cleanup Policy automates image retention and deletion of old images, reducing storage costs and avoiding clutter.
Rollback and rollback policies should be handled by Cloud Deploy, not manual interventions.
#Why not other options?
A## Cloud Build jobs for cleanup are not scalable or automated compared to Artifact Registry policies.
B## Cloud Service Mesh is not related to deployment rollbacks or image cleanup.
D## Cloud Deploy provides better rollback management than a custom rollback pipeline.
#Official Reference:
Google Cloud Deploy Overview
Artifact Registry Cleanup Policy
NEW QUESTION # 85
You recently deployed your application in Google Kubernetes Engine (GKE) and now need to release a new version of the application You need the ability to instantly roll back to the previous version of the application in case there are issues with the new version Which deployment model should you use?
- A. Perform A. B testing, and test your application periodically after the deployment is complete
- B. Perform a blue/green deployment and test your new application after the deployment is complete
- C. Perform a rolling deployment and test your new application after the deployment is complete
- D. Perform a canary deployment, and test your new application periodically after the new version is deployed
Answer: B
Explanation:
The best deployment model for releasing a new version of your application in GKE with the ability to instantly roll back to the previous version is to perform a blue/green deployment and test your new application after the deployment is complete. A blue/green deployment is a deployment strategy that involves creating two identical environments, one running the current version of the application (blue) and one running the new version of the application (green). The traffic is switched from blue to green after testing the new version, and if any issues are discovered, the traffic can be switched back to blue instantly. This way, you can minimize downtime and risk during deployment.
NEW QUESTION # 86
You are responsible for creating development environments for your company's development team. You want to create environments with identical IDEs for all developers while ensuring that these environments are not exposed to public networks. You need to choose the most cost-effective solution without impacting developer productivity. What should you do?
- A. Create a Cloud Workstations private cluster. Create a workstation configuration with a runningTimeout parameter.
- B. Create multiple Compute Engine VM instances without an external IP address. Configure an instance schedule to shut down the VMs.
- C. Create multiple Compute Engine VM instances with an external IP address and use a Public NAT gateway. Configure an instance schedule to shut down the VMs.
- D. Create a Cloud Workstations private cluster. Create a workstation configuration with an idleTimeout parameter.
Answer: A
Explanation:
Comprehensive and Detailed 150 to 200 words of Explanation From Google Cloud DevOps guides documents:
According to Google Cloud's documentation on Cloud Workstations, this service is specifically designed to provide managed, secure, and highly customizable development environments. By selecting a private cluster, you ensure that the workstations are not assigned public IP addresses, keeping them entirely off the public internet and satisfying the security requirement. This managed approach is superior to manual Compute Engine setups because it uses container-based configurations to provide identical IDEs and toolsets to every developer, which eliminates environment drift and boosts productivity.
Regarding cost-effectiveness, the runningTimeout parameter is a vital mechanism. While idleTimeout is excellent for short-term inactivity, runningTimeout provides a definitive "hard stop" to ensure that workstations do not run indefinitely if a developer forgets to shut down their session at the end of a shift, thereby preventing runaway costs. This aligns with Google's SRE and DevOps best practices for cost optimization and resource management. Choosing Cloud Workstations over manual VM management (Options C and D) reduces the operational overhead of patching and maintaining individual machine images, allowing the team to focus on delivery rather than infrastructure maintenance.
NEW QUESTION # 87
Your company allows teams to self-manage Google Cloud projects, including project-level Identity and Access Management (IAM). You are concerned that the team responsible for the Shared VPC project might accidentally delete the project, so a lien has been placed on the project. You need to design a solution to restrict Shared VPC project deletion to those with the resourcemanager.projects.updateLiens permission at the organization level. What should you do?
- A. Enable VPC Service Controls for the container.googleapis.com API service.
- B. Enable the compute.restrictXpnProjectLienRemoval organization policy constraint.
- C. Instruct teams to only perform IAM permission management as code with Terraform.
- D. Revoke the resourcemanager.projects.updateLiens permission from all users associated with the project.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From General Google Cloud IAM and Organization Policy Knowledge:
The core requirement is to prevent accidental deletion of a Shared VPC host project, even by project owners, by ensuring that only users with a specific permission at the organization level can remove the lien that protects the project.
A lien (resourcemanager.projects.delete) has already been placed on the project. This prevents its deletion.
The challenge is to prevent the removal of this lien by project-level administrators.
The permission to remove a lien is resourcemanager.projectLiens.update (or resourcemanager.projects.
updateLiens as stated in the question, which implies a broader update capability including liens).
Option A (Enable VPC Service Controls for the container.googleapis.com API service): VPC Service Controls are for data exfiltration prevention by creating service perimeters. They do not directly control IAM permissions for lien management or project deletion.
Option B (Revoke the resourcemanager.projects.updateLiens permission from all users associated with the project): While this would prevent project-level users from removing the lien, it doesn't enforce therequirement that only users with this permission at the organization level can remove it. A project owner could potentially re-grant themselves this permission at the project level if not otherwise restricted. The goal is a stronger, centrally enforced restriction.
Option C (Enable the compute.restrictXpnProjectLienRemoval organization policy constraint): This is specifically designed for the scenario described.Organization Policies allow centralized control over resource configurations across the organization.
The compute.restrictXpnProjectLienRemoval constraint, when enforced (set to True), restricts the removal of liens on Shared VPC host projects. Only users who have the resourcemanager.projectLiens.update permission (or resourcemanager.projects.updateLiens) granted at the organization level can then remove such liens. This prevents project owners or other project-level principals from removing the lien unless they also have this specific permission at the org level.
Option D (Instruct teams to only perform IAM permission management as code with Terraform): While Infrastructure as Code (IaC) is a good practice for managing IAM, it's an operational guideline and doesn't technically enforce the restriction on lien removal. A user with sufficient project-level IAM permissions could still manually remove the lien via the console or gcloud if not prevented by an organization policy.
Therefore, enabling the compute.restrictXpnProjectLienRemoval organization policy is the direct and most effective way to meet the requirement.
Reference (Based on Google Cloud Organization Policy and Shared VPC documentation):
Google Cloud documentation on Resource Manager Liens: https://cloud.google.com/resource-manager/docs
/project-liens
Google Cloud documentation on Organization Policy Constraints: https://cloud.google.com/resource-manager
/docs/organization-policy/org-policy-constraints
Specifically, the compute.restrictXpnProjectLienRemoval constraint: "When set to true, liens on Shared VPC host projects can only be removed by users that have resourcemanager.projectLiens.update permission on the organization." (or similar wording indicating org-level permission is required). This constraint ensures that the protection afforded by the lien on a critical Shared VPC host project cannot be easily circumvented at the project level.
NEW QUESTION # 88
You support an application deployed on Compute Engine. The application connects to a Cloud SQL instance to store and retrieve dat a. After an update to the application, users report errors showing database timeout messages. The number of concurrent active users remained stable. You need to find the most probable cause of the database timeout. What should you do?
- A. Check the serial port logs of the Compute Engine instance.
- B. Use Stackdriver Profiler to visualize the resources utilization throughout the application.
- C. Use Cloud Security Scanner to see whether your Cloud SQL is under a Distributed Denial of Service (DDoS) attack.
- D. Determine whether there is an increased number of connections to the Cloud SQL instance.
Answer: B
NEW QUESTION # 89
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using aCI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message
You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?
- A. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
- B. Delete the managed instance group and recreate it after updating the instance template
- C. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
- D. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
Answer: C
Explanation:
The best option for updating the instance template and minimizing disruption to the application and the number of pipeline runs is to set the create_before_destroy meta-argument to true in the lifecycle block on the instance template. The create_before_destroy meta-argument is a Terraform feature that specifies that a new resource should be created before destroying an existing one during an update. This way, you can avoid downtime and errors when updating a resource that is in use by another resource, such as an instance template that is used by a managed instance group. By setting the create_before_destroy meta-argument to true in the lifecycle block on the instance template, you can ensure that Terraform creates a new instance template with the updated machine type, updates the managed instance group to use the new instance template, and then deletes the old instance template.
NEW QUESTION # 90
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?
- A. Use Cloud Logging to configure an export sink at each project level to export all logs into a BigQuery dataset
- B. 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
- C. Use Cloud Logging to configure an aggregated sink at the organization level to export all logs into a BigQuery dataset
- D. Use Cloud Logging to configure an export sink at each project level to export all logs into Cloud Storage with a seven-year retention policy and Bucket Lock
Answer: B
NEW QUESTION # 91
You encounter a large number of outages in the production systems you support. You receive alerts for all the outages that wake you up at night. The alerts are due to unhealthy systems that are automatically restarted within a minute. You want to set up a process that would prevent staff burnout while following Site Reliability Engineering practices. What should you do?
- A. Redefine the related Service Level Objective so that the error budget is not exhausted.
- B. Create an incident report for each of the alerts.
- C. Eliminate unactionable alerts.
- D. Distribute the alerts to engineers in different time zones.
Answer: C
NEW QUESTION # 92
Your company runs services on Google Cloud. Each team runs their applications in a dedicated project. New teams and projects are created regularly. Your security team requires that all logs are processed by a security information and event management (SIEM) system. The SIEM ingests logs by using Pub/Sub. You must ensure that all existing and future logs are scanned by the SIEM. What should you do?
- A. Create an organization-level aggregated sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs.
- B. Create an organization-level aggregated sink with a SIEM log bucket as the destination. Set an inclusion filter to include all logs.
- C. Create a project-level logging sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs. Repeat for each project.
- D. Create a folder-level aggregated sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs. Repeat for each folder.
Answer: A
Explanation:
Comprehensive and Detailed Explanation:
To ensure all logs (existing and future) are automatically processed by the SIEM system, the best approach is:
Use an organization-level aggregated sink # Captures logs from all existing and future projects automatically.
Send logs to a Pub/Sub topic # Since the SIEM ingests logs via Pub/Sub, this ensures logs are streamed in real- time.
Set an inclusion filter # To capture all logs needed by the security team.
#Why not other options?
B (Project-level logging sink)## Requires manual setup per project, which doesn't scale for new projects.
C (Log bucket instead of Pub/Sub)## SIEM is expecting real-time log ingestion via Pub/Sub, not a storage- based approach.
D (Folder-level logging sink)## Only applies to specific folders, not the entire organization.
#Official Reference:
Aggregated Sinks for Cloud Logging
Exporting Logs to SIEM via Pub/Sub
NEW QUESTION # 93
You are on-call for an infrastructure service that has a large number of dependent systems. You receive an alert indicating that the service is failing to serve most of its requests and all of its dependent systems with hundreds of thousands of users are affected. As part of your Site Reliability Engineering (SRE) incident management protocol, you declare yourself Incident Commander (IC) and pull in two experienced people from your team as Operations Lead (OLJ and Communications Lead (CL). What should you do next?
- A. Start a postmortem, add incident information, circulate the draft internally, and ask internal stakeholders for input.
- B. Look for ways to mitigate user impact and deploy the mitigations to production.
- C. Establish a communication channel where incident responders and leads can communicate with each other.
- D. Contact the affected service owners and update them on the status of the incident.
Answer: C
NEW QUESTION # 94
You support a web application that runs on App Engine and uses CloudSQL and Cloud Storage for data storage. After a short spike in website traffic, you notice a big increase in latency for all user requests, increase in CPU use, and the number of processes running the application. Initial troubleshooting reveals:
After the initial spike in traffic, load levels returned to normal but users still experience high latency.
Requests for content from the CloudSQL database and images from Cloud Storage show the same high latency.
No changes were made to the website around the time the latency increased.
There is no increase in the number of errors to the users.
You expect another spike in website traffic in the coming days and want to make sure users don't experience latency. What should you do?
- A. Modify the App Engine configuration to have additional idle instances.
- B. Upgrade the GCS buckets to Multi-Regional.
- C. Enable high availability on the CloudSQL instances.
- D. Move the application from App Engine to Compute Engine.
Answer: A
NEW QUESTION # 95
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