Google Professional-Cloud-DevOps-Engineer Dumps – 100% Cover Real Exam Questions (Updated 200 Questions) [Q24-Q46]

Google Professional-Cloud-DevOps-Engineer Dumps – 100% Cover Real Exam Questions (Updated 200 Questions) [Q24-Q46]

January 24, 2026 latestexam 0 Comments

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Google Professional-Cloud-DevOps-Engineer Dumps – 100% Cover Real Exam Questions (Updated 200 Questions)

Real Professional-Cloud-DevOps-Engineer dumps – Real Google dumps PDF

Google Professional-Cloud-DevOps-Engineer certification is a valuable asset for professionals who want to advance their careers in the cloud computing industry. It demonstrates their expertise in designing and managing cloud-based solutions using Google Cloud technologies. Google Cloud Certified – Professional Cloud DevOps Engineer Exam certification also provides a competitive advantage in the job market, as it validates the candidate’s skills and knowledge in a rapidly growing field. Overall, the Professional-Cloud-DevOps-Engineer certification is an excellent choice for professionals who want to enhance their career prospects and stay up-to-date with the latest trends in cloud-based DevOps engineering.

QUESTION 24
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?

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).

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.

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.

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.

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.
Reference:
Creating an attestor, Creating an attestor.Cloud Key Management Service Documentation, Overview.
Attestations overview, Attestations overview.Using Workload Identity with Binary Authorization, Using Workload Identity with Binary Authorization.Binary Authorization, Binary Authorization.

QUESTION 25
You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently. How should you assign owners and collaborators to action items?

Assign one owner for each action item and any necessary collaborators.

Assign multiple owners for each item to guarantee that the team addresses items quickly

Assign collaborators but no individual owners to the items to keep the postmortem blameless.

Assign the team lead as the owner for all action items because they are in charge of the SRE team.

https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/

QUESTION 26
Your application images are built wing Cloud Build and pushed to Google Container Registry (GCR). You want to be able to specify a particular version of your application for deployment based on the release version tagged in source control. What would you do when you push the image?

Reference the image digest in the source control tag.

Supply the source control tag as a parameter within the image name.

Use Cloud Build to include the release version tag in the application image.

Use GCR digest versioning to match the image to the tag in source control.

QUESTION 27
You are responsible for creating and modifying the Terraform templates that define your Infrastructure. Because two new engineers will also be working on the same code, you need to define a process and adopt a tool that will prevent you from overwriting each other’s code. You also want to ensure that you capture all updates in the latest version. What should you do?

Store your code in a Git-based version control system.
* Establish a process that allows developers to merge their own changes at the end of each day.
* Package and upload code lo a versioned Cloud Storage bucket as the latest master version.

Store your code in a Git-based version control system.
* Establish a process that includes code reviews by peers and unit testing to ensure integrity and functionality before integration of code.
* Establish a process where the fully integrated code in the repository becomes the latest master version.

Store your code as text files in Google Drive in a defined folder structure that organizes the files.
* At the end of each day. confirm that all changes have been captured in the files within the folder structure.
* Rename the folder structure with a predefined naming convention that increments the version.

Store your code as text files in Google Drive in a defined folder structure that organizes the files.
* At the end of each day, confirm that all changes have been captured in the files within the folder structure and create a new .zip archive with a predefined naming convention.
* Upload the .zip archive to a versioned Cloud Storage bucket and accept it as the latest version.

QUESTION 28
Your team is designing a new application for deployment both inside and outside Google Cloud Platform (GCP). You need to collect detailed metrics such as system resource utilization. You want to use centralized GCP services while minimizing the amount of work required to set up this collection system. What should you do?

Import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis.

Install an Application Performance Monitoring (APM) tool in both locations, and configure an export to a central data storage location for analysis.

Instrument the code using a timing library, and publish the metrics via a health check endpoint that is scraped by Stackdriver.

Import the Stackdriver Debugger package, and configure the application to emit debug messages with timing information.

QUESTION 29
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.

Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.

Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.

Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.

QUESTION 30
You are running a web application deployed to a Compute Engine managed instance group Ops Agent is installed on all instances You recently noticed suspicious activity from a specific IP address You need to configure Cloud Monitoring to view the number of requests from that specific IP address with minimal operational overhead. What should you do?

Configure the Ops Agent with a logging receiver Create a logs-based metric

Create a script to scrape the web server log Export the IP address request metrics to the Cloud Monitoring API

Update the application to export the IP address request metrics to the Cloud Monitoring API

Configure the Ops Agent with a metrics receiver

The best option for configuring Cloud Monitoring to view the number of requests from a specific IP address with minimal operational overhead is to configure the Ops Agent with a logging receiver and create a logs-based metric. The Ops Agent is an agent that collects system metrics and logs from your VM instances and sends them to Cloud Monitoring and Cloud Logging. A logging receiver is a configuration that specifies which logs are collected by the Ops Agent and how they are processed. You can use a logging receiver to collect web server logs from your VM instances and send them to Cloud Logging. A logs-based metric is a metric that is extracted from log entries in Cloud Logging. You can use a logs-based metric to count the number of requests from a specific IP address by using a filter expression. You can then use Cloud Monitoring to view and analyze the logs-based metric.

QUESTION 31
Your team is designing a new application for deployment both inside and outside Google Cloud Platform (GCP). You need to collect detailed metrics such as system resource utilization. You want to use centralized GCP services while minimizing the amount of work required to set up this collection system. What should you do?

Import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis.

Import the Stackdriver Debugger package, and configure the application to emit debug messages with timing information.

Instrument the code using a timing library, and publish the metrics via a health check endpoint that is scraped by Stackdriver.

Install an Application Performance Monitoring (APM) tool in both locations, and configure an export to a central data storage location for analysis.

Explanation/Reference:

QUESTION 32
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 Kubernetes Engine Enterprise (GKE Enterprise) cluster created so that application teams can deploy their applications. Config Sync will be used and templated to deploy infrastructure-level resources in each GKE Enterprise 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 (IaC) and application code?

Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Enterprise Infrastructure (Config Sync Kustomize manifests) repository is shared: different overlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features

Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Enterprise Infrastructure (Config Sync Kustomize manifests) repositories are separated: different branches are different environmentsApplication (app source code) repositories are separated: different branches are different features

Cloud Infrastructure (Terraform) repository is shared: different branches are different environmentsGKE Enterprise Infrastructure (Config Sync Kustomize manifests) repository is shared: different overlay directories are different environmentsApplication (app source code) repository is shared: different directories are different features

Cloud Infrastructure (Terraform) repositories are separated: different branches are different environmentsGKE Enterprise Infrastructure (Config Sync Kustomize manifests) repositories are separated: different overlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features

QUESTION 33
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?

Update the Deployment app-blue to use the new version of the application

Update the Deployment ape-green to use the previous version of the application

Change the selector on the Service app-2vc to app: my-app.

Change the selector on the Service app-svc to app: my-app, version: blue

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.

QUESTION 34
You need to run a business-critical workload on a fixed set of Compute Engine instances for several months.
The workload is stable with the exact amount of resources allocated to it. You want to lower the costs for this workload without any performance implications. What should you do?

Purchase Committed Use Discounts.

Migrate the instances to a Managed Instance Group.

Convert the instances to preemptible virtual machines.

Create an Unmanaged Instance Group for the instances used to run the workload.

Explanation/Reference: https://cloud.google.com/compute/docs/faq

QUESTION 35
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?

Eliminate unactionable alerts.

Create an incident report for each of the alerts.

Distribute the alerts to engineers in different time zones.

Redefine the related Service Level Objective so that the error budget is not exhausted.

QUESTION 36
You need to define Service Level Objectives (SLOs) for a high-traffic multi-region web application. Customers expect the application to always be available and have fast response times. Customers are currently happy with the application performance and availability. Based on current measurement, you observe that the 90th percentile of latency is 120ms and the 95th percentile of latency is 275ms over a 28-day window. What latency SLO would you recommend to the team to publish?

90th percentile – 100ms
95th percentile – 250ms

90th percentile – 120ms
95th percentile – 275ms

90th percentile – 150ms
95th percentile – 300ms

90th percentile – 250ms
95th percentile – 400ms

QUESTION 37
You are writing a postmortem for an incident that severely affected users. You want to prevent similar incidents in the future. Which two of the following sections should you include in the postmortem? (Choose two.)

An explanation of the root cause of the incident

A list of employees responsible for causing the incident

A list of action items to prevent a recurrence of the incident

Your opinion of the incident’s severity compared to past incidents

Copies of the design documents for all the services impacted by the incident

QUESTION 38
You are running a real-time gaming application on Compute Engine that has a production and testing environment. Each environment has their own Virtual Private Cloud (VPC) network. The application frontend and backend servers are located on different subnets in the environment’s VPC. You suspect there is a malicious process communicating intermittently in your production frontend servers. You want to ensure that network traffic is captured for analysis. What should you do?

Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 0.5.

Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 1.0.

Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 0.5. Apply changes in testing before production.

Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 1.0. Apply changes in testing before production.

QUESTION 39
You are developing the deployment and testing strategies for your CI/CD pipeline in Google Cloud You must be able to
* Reduce the complexity of release deployments and minimize the duration of deployment rollbacks
* Test real production traffic with a gradual increase in the number of affected users You want to select a deployment and testing strategy that meets your requirements What should you do?

Recreate deployment and canary testing

Blue/green deployment and canary testing

Rolling update deployment and A/B testing

Rolling update deployment and shadow testing

The best option for selecting a deployment and testing strategy that meets your requirements is to use blue
/green deployment and canary testing. 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 reduce the complexity of release deployments and minimize the duration of deployment rollbacks. A canary testing is a testing strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test real production traffic with a gradual increase in the number of affected users.

QUESTION 40
You are using Terraform to manage infrastructure as code within a Cl/CD pipeline You notice that multiple copies of the entire infrastructure stack exist in your Google Cloud project, and a new copy is created each time a change to the existing infrastructure is made You need to optimize your cloud spend by ensuring that only a single instance of your infrastructure stack exists at a time. You want to follow Google-recommended practices What should you do?

Create a new pipeline to delete old infrastructure stacks when they are no longer needed

Confirm that the pipeline is storing and retrieving the terraform. if state file from Cloud Storage with the Terraform gcs backend

Verify that the pipeline is storing and retrieving the terrafom.tfstat* file from a source control

Update the pipeline to remove any existing infrastructure before you apply the latest configuration

Explanation
The best option for optimizing your cloud spend by ensuring that only a single instance of your infrastructure stack exists at a time is to confirm that the pipeline is storing and retrieving the terraform.tfstate file from Cloud Storage with the Terraform gcs backend. The terraform.tfstate file is a file that Terraform uses to store the current state of your infrastructure. The Terraform gcs backend is a backend type that allows you to store the terraform.tfstate file in a Cloud Storage bucket. By using the Terraform gcs backend, you can ensure that your pipeline has access to the latest state of your infrastructure and avoid creating multiple copies of the entire infrastructure stack.

QUESTION 41
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?

Deploy a Cloud NAT gateway and attach the gateway to the subnet of the VMS.

Add additional network interface controllers (NICs) to your VMS.

Change the machine type for your VMS to n2-standard-8.

Deploy the Ops Agent to export additional monitoring metrics.

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.

QUESTION 42
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

MTTD: 5MTTR: 10MTBF: 90Impact: 33%

MTTD:5MTTR: 20MTBF: 90Impact: 33%

MTTD:5MTTR: 10MTBF: 90Impact 50%

MTTD:5MTTR: 20MTBF: 90Impact: 50%

QUESTION 43
You are developing the deployment and testing strategies for your CI/CD pipeline in Google Cloud You must be able to
* Reduce the complexity of release deployments and minimize the duration of deployment rollbacks
* Test real production traffic with a gradual increase in the number of affected users You want to select a deployment and testing strategy that meets your requirements What should you do?

Recreate deployment and canary testing

Blue/green deployment and canary testing

Rolling update deployment and A/B testing

Rolling update deployment and shadow testing

Explanation
The best option for selecting a deployment and testing strategy that meets your requirements is to use blue/green deployment and canary testing. 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 reduce the complexity of release deployments and minimize the duration of deployment rollbacks. A canary testing is a testing strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test real production traffic with a gradual increase in the number of affected users.

QUESTION 44
Your team is writing a postmortem after an incident on your external facing application Your team wants to improve the postmortem policy to include triggers that indicate whether an incident requires a postmortem Based on Site Reliability Engineenng (SRE) practices, what triggers should be defined in the postmortem policy?
Choose 2 answers

An external stakeholder asks for a postmortem

Data is lost due to an incident

An internal stakeholder requests a postmortem

The monitoring system detects that one of the instances for your application has failed

The CD pipeline detects an issue and rolls back a problematic release.

QUESTION 45
You are the Site Reliability Engineer responsible for managing your company’s data services and products.
You regularly navigate operational challenges, such as unpredictable data volume and high cost, with your company’s data ingestion processes. You recently learned that a new data ingestion product will be developed in Google Cloud. You need to collaborate with the product development team to provide operational input on the new product. What should you do?

Deploy the prototype product in a test environment, run a load test, and share the results with the product development team.

When the initial product version passes the quality assurance phase and compliance assessments, deploy the product to a staging environment. Share error logs and performancemetrics with the product development team.

When the new product is used by at least one internal customer in production, share error logs and monitoring metrics with the product development team.

Review the design of the product with the product development team to provide feedback early in the design phase.

The correct answer is D. Review the design of the product with the product development team to provide feedback early in the design phase.
According to the Google Cloud DevOps best practices, a Site Reliability Engineer (SRE) should collaborate with the product development team from the beginning of the product lifecycle, not just after the product is deployed or tested. This way, the SRE can provide operational input on the product design, such as scalability, reliability, security, and cost efficiency. The SRE can also help define service level objectives (SLOs) and service level indicators (SLIs) for the product, as well as monitoring and alerting strategies. By collaborating early and often, the SRE and the product development team can ensure that the product meets the operational requirements and expectations of the customers.
Reference:
Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate, Course 1: Site Reliability Engineering and DevOps, Week 1: Introduction to SRE and DevOps.

QUESTION 46
You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently.
How should you assign owners and collaborators to action items?

Assign one owner for each action item and any necessary collaborators.

Assign multiple owners for each item to guarantee that the team addresses items quickly

Assign collaborators but no individual owners to the items to keep the postmortem blameless.

Assign the team lead as the owner for all action items because they are in charge of the SRE team.

Explanation
https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/

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What is the duration, language, and format of Google Professional Cloud DevOps Engineer Exam

Length of Examination: 120 minutes
Language: English
Format: Multiple choices, multiple select
Passing score: 80%
Number of Questions: 50-60

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Google Professional-Cloud-DevOps-Engineer Dumps – 100% Cover Real Exam Questions (Updated 200 Questions) [Q24-Q46]

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