Google Professional Cloud DevOps Engineer Practice Exam

Jonnie Karnath2023-10-25T07:53:37+00:00

In order to ensure your success in the Google Cloud Certified – Professional Cloud DevOps Engineer Exam, you may consider utilizing the Google Professional Cloud DevOps Engineer Practice Exam from Certspots. This comprehensive Professional Cloud DevOps Engineer practice exam will not only enhance your confidence but also provide you with valuable insights and knowledge to effectively prepare for your test. By dedicating time and effort to this Professional Cloud DevOps Engineer practice exam, you will be equipped with the necessary skills and understanding to approach your actual exam with ease and achieve a favorable outcome.

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1. Your company runs an ecommerce website built with JVM-based applications and microservice architecture in Google Kubernetes Engine (GKE) The application load increases during the day and decreases during the night Your operations team has configured the application to run enough Pods to handle the evening peak load. You want to automate scaling by only running enough Pods and nodes for the load.

What should you do?

Configure the Vertical Pod Autoscaler but keep the node pool size static

Configure the Vertical Pod Autoscaler and enable the cluster autoscaler

Configure the Horizontal Pod Autoscaler but keep the node pool size static

Configure the Horizontal Pod Autoscaler and enable the cluster autoscaler

2. You created a Stackdriver chart for CPU utilization in a dashboard within your workspace project. You want to share the chart with your Site Reliability Engineering (SRE) team only. You want to ensure you follow the principle of least privilege.

What should you do?

Share the workspace Project ID with the SRE team. Assign the SRE team the Monitoring Viewer IAM role in the workspace project.

Share the workspace Project ID with the SRE team. Assign the SRE team the Dashboard Viewer IAM role in the workspace project.

Click "Share chart by URL" and provide the URL to the SRE team. Assign the SRE team the Monitoring Viewer IAM role in the workspace project.

Click "Share chart by URL" and provide the URL to the SRE team. Assign the SRE team the Dashboard Viewer IAM role in the workspace project.

3. You use Spinnaker to deploy your application and have created a canary deployment stage in the pipeline. Your application has an in-memory cache that loads objects at start time. You want to automate the comparison of the canary version against the production version.

How should you configure the canary analysis?

Compare the canary with a new deployment of the current production version.

Compare the canary with a new deployment of the previous production version.

Compare the canary with the existing deployment of the current production version.

Compare the canary with the average performance of a sliding window of previous production versions.

4. You are creating a CI/CD pipeline in Cloud Build to build an application container image The application code is stored in GitHub Your company requires that production image builds are only run against the main branch and that the change control team approves all pushes to the main branch

You want the image build to be as automated as possible.

What should you do? Choose 2 answers

Create a trigger on the Cloud Build job Set the repository event setting to Pull request'

Add the owners file to the Included files filter on the trigger

Create a trigger on the Cloud Build job Set the repository event setting to Push to a branch

Configure a branch protection rule for the main branch on the repository

Enable the Approval option on the trigger

5. You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects Log entries for development projects must be exported to dev_dataset. and log entries for production projects must be exported to prod_dataset. You need to minimize the number of log sinks created and you want to ensure that the log sinks apply to future projects.

What should you do?

Create a single aggregated log sink at the organization level.

Create a log sink in each project

Create two aggregated log sinks at the organization level, and filter by project ID

Create an aggregated Iog sink in the Dev and Prod folders

6. You are developing a strategy for monitoring your Google Cloud Platform (GCP) projects in production using Stackdriver Workspaces. One of the requirements is to be able to quickly identify and react to production environment issues without false alerts from development and staging projects. You want to ensure that you adhere to the principle of least privilege when providing relevant team members with access to Stackdriver Workspaces.

What should you do?

Grant relevant team members read access to all GCP production projects. Create Stackdriver workspaces inside each project.

Grant relevant team members the Project Viewer IAM role on all GCP production projects. Create Slackdriver workspaces inside each project.

Choose an existing GCP production project to host the monitoring workspace. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.

Create a new GCP monitoring project, and create a Stackdriver Workspace inside it. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.

7. 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.

8. Your company is using HTTPS requests to trigger a public Cloud Run-hosted service accessible at the https://booking-engine-abcdef .a.run.app URL You need to give developers the ability to test the latest revisions of the service before the service is exposed to customers.

What should you do?

Runthegcioud run deploy booking-engine ―no-traffic ―-ag dev command Use the https://dev---- booking-engine-abcdef. a. run. app URL for testing

Runthegcioud run services update-traffic booking-engine ―to-revisions LATEST*! command Use the https: //booking-engine-abcdef. a. run. ape URL for testing

Pass the curl -K "Authorization: Hearer S(gclcud auth print-identity-token)" auth token Use the https: / /booking-engine-abcdef. a. run. app URL to test privately

Grant the roles/run. invoker role to the developers testing the booking-engine service Use the https: //booking-engine-abcdef. private. run. app URL for testing

9. You have an application that runs in Google Kubernetes Engine (GKE). The application consists of several microservices that are deployed to GKE by using Deployments and Services One of the microservices is experiencing an issue where a Pod returns 403 errors after the Pod has been running for more than five hours Your development team is working on a solution but the issue will not be resolved for a month You need to ensure continued operations until the microservice is fixed You want to follow Google-recommended practices and use the fewest number of steps.

What should you do?

Create a cron job to terminate any Pods that have been running for more than five hours

Add a HTTP liveness probe to the microservice s deployment

Monitor the Pods and terminate any Pods that have been running for more than five hours

Configure an alert to notify you whenever a Pod returns 403 errors

10. You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting.

What should you do?

Install the Stackdriver Error Reporting library for Python, and then run your code on a Compute Engine V

Install the Stackdriver Error Reporting library for Python, and then run your code on Google Kubernetes Engine.

Install the Stackdriver Error Reporting library for Python, and then run your code on App Engine flexible environment.

Use the Stackdriver Error Reporting API to write errors from your application to ReportedErrorEvent, and then generate log entries with properly formatted error messages in Stackdriver Logging.

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11. You have an application running in Google Kubernetes Engine. The application invokes multiple services per request but responds too slowly. You need to identify which downstream service or services are causing the delay.

What should you do?

Analyze VPC flow logs along the path of the request.

Investigate the Liveness and Readiness probes for each service.

Create a Dataflow pipeline to analyze service metrics in real time.

Use a distributed tracing framework such as OpenTelemetry or Stackdriver Trace.

12. 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 a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval.

What should you do to enforce approvals?

Configure the build system with protected branches that require pull request approval.

Use an Admission Controller to verify that incoming requests originate from approved sources.

Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.

Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.

13. You are managing the production deployment to a set of Google Kubernetes Engine (GKE) clusters. You want to make sure only images which are successfully built by your trusted CI/CD pipeline are deployed to production.

What should you do?

Enable Cloud Security Scanner on the clusters.

Enable Vulnerability Analysis on the Container Registry.

Set up the Kubernetes Engine clusters as private clusters.

Set up the Kubernetes Engine clusters with Binary Authorization.

14. Your company's security team needs to have read-only access to Data Access audit logs in the _Required bucket. You want to provide your security team with the necessary permissions following the principle of least privilege and Google-recommended practices.

What should you do?

Assign the roles/logging, viewer role to each member of the security team

Assign the roles/logging. viewer role to a group with all the security team members

Assign the roles/logging.privateLogViewer role to each member of the security team

Assign the roles/logging.privateLogviewer role to a group with all the security team members

15. 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

Operations Lead

Engineering Lead

Communications Lead

Customer Impact Assessor

External Customer Communications Lead

16. Your organization uses a change advisory board (CAB) to approve all changes to an existing service You want to revise this process to eliminate any negative impact on the software delivery performance

What should you do? Choose 2 answers

Replace the CAB with a senior manager to ensure continuous oversight from development to deployment

Let developers merge their own changes but ensure that the team's deployment platform can roll back changes if any issues are discovered

Move to a peer-review based process for individual changes that is enforced at code check-in time and supported by automated tests

Batch changes into larger but less frequent software releases

Ensure that the team's development platform enables developers to get fast feedback on the impact of their changes

17. You are using Stackdriver to monitor applications hosted on Google Cloud Platform (GCP). You recently deployed a new application, but its logs are not appearing on the Stackdriver dashboard. You need to troubleshoot the issue.

What should you do?

Confirm that the Stackdriver agent has been installed in the hosting virtual machine.

Confirm that your account has the proper permissions to use the Stackdriver dashboard.

Confirm that port 25 has been opened in the firewall to allow messages through to Stackdriver.

Confirm that the application is using the required client library and the service account key has proper permissions.

18. You support a web application that is hosted on Compute Engine. The application provides a booking service for thousands of users. Shortly after the release of a new feature, your monitoring dashboard shows that all users are experiencing latency at login. You want to mitigate the impact of the incident on the users of your service.

What should you do first?

Roll back the recent release.

Review the Stackdriver monitoring.

Upsize the virtual machines running the login services.

Deploy a new release to see whether it fixes the problem.

19. 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.

20. 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

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21. Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members.

What should you do?

Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.

Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.

Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.

Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member’s computer. Organize files with a naming convention that identifies each new version.

22. Your organization wants to increase the availability target of an application from 99 9% to 99 99% for an investment of $2 000 The application's current revenue is S1,000,000 You need to determine whether the increase in availability is worth the investment for a single year of usage.

What should you do?

Calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment

Calculate the value of improved availability to be $1 000 and determine that the increase in availability is not worth the investment

Calculate the value of improved availability to be $1 000 and determine that the increase in availability is worth the investment

Calculate the value of improved availability to be $9,000. and determine that the increase in availability is worth the investment

23. Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics alerts: and generating dashboards This setup does not provide a method to view metrics globally across all clusters You need to implement a scalable solution to support global Prometheus querying and minimize management overhead.

What should you do?

Configure Prometheus cross-service federation for centralized data access

Configure workload metrics within Cloud Operations for GKE

Configure Prometheus hierarchical federation for centralized data access

Configure Google Cloud Managed Service for Prometheus

24. 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?

Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.

Deploy a Fluentd daemonset to GK

Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.

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.

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.

25. 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 a CI/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?

Delete the managed instance group and recreate it after updating the instance template

Add a new instance template update the managed instance group to use the new instance template and delete the old instance template

Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.

Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template

26. 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.

27. The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated.

What should you do?

Deploy the application through a continuous delivery pipeline by using canary deployments Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics

Deploy the application through a continuous delivery pipeline by using blue/green deployments Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues

Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues

Deploy the application by using kubectl and set the spec. updatestrategy. type field to RollingUpdate Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.

28. You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices.

What should you do?

Disable the CI pipeline and revert to manually building and pushing the artifacts.

Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.

Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.

Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.

29. You need to reduce the cost of virtual machines (VM| for your organization. After reviewing different options, you decide to leverage preemptible VM instances.

Which application is suitable for preemptible VMs?

A scalable in-memory caching system

The organization's public-facing website

A distributed, eventually consistent NoSQL database cluster with sufficient quorum

A GPU-accelerated video rendering platform that retrieves and stores videos in a storage bucket

30. You support the backend of a mobile phone game that runs on a Google Kubernetes Engine (GKE) cluster. The application is serving HTTP requests from users. You need to implement a solution that will reduce the network cost.

What should you do?

Configure the VPC as a Shared VPC Host project.

Configure your network services on the Standard Tier.

Configure your Kubernetes duster as a Private Cluster.

Configure a Google Cloud HTTP Load Balancer as Ingress.

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31. 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?

Install a toolbox container on the node in Cluster A Confirm that the routes to Cluster B are configured appropriately

Use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster

Use a debug container to run the traceroute command from Cluster A to Cluster B and from Cluster B to Cluster A Identify the common failure point

Enable VPC Flow Logs in both VPCs and monitor packet drops

32. Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third parties are able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible.

What should you do?

• Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that third parties can upload batches of data and provide appropriate credentials to the server • Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group • Use an image pre-loaded with the data processing software that terminates the instances when processing completes

• Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket • Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data • Stop the processing service when there are no batches of data to process

• Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket • Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group • Use an image pre-loaded with the data processing software that terminates the instances when processing completes

• Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket • Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data • Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing

33. You support an e-commerce application that runs on a large Google Kubernetes Engine (GKE) cluster deployed on-premises and on Google Cloud Platform. The application consists of microservices that run in containers. You want to identify containers that are using the most CPU and memory.

What should you do?

Use Stackdriver Kubernetes Engine Monitoring.

Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.

Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.

Use Stackdriver Logging to export application logs to BigOuery. aggregate logs per container, and then analyze CPU and memory consumption.

34. You built a serverless application by using Cloud Run and deployed the application to your production environment You want to identify the resource utilization of the application for cost optimization.

What should you do?

Use Cloud Trace with distributed tracing to monitor the resource utilization of the application

Use Cloud Profiler with Ops Agent to monitor the CPU and memory utilization of the application

Use Cloud Monitoring to monitor the container CPU and memory utilization of the application

Use Cloud Ops to create logs-based metrics to monitor the resource utilization of the application

35. 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.

36. 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

37. Your company is developing applications that are deployed on Google Kubernetes Engine (GKE). Each team manages a different application. You need to create the development and production environments for each team, while minimizing costs. Different teams should not be able to access other teams’ environments.

What should you do?

Create one GCP Project per team. In each project, create a cluster for Development and one for Production. Grant the teams IAM access to their respective clusters.

Create one GCP Project per team. In each project, create a cluster with a Kubernetes namespace for Development and one for Production. Grant the teams IAM access to their respective clusters.

Create a Development and a Production GKE cluster in separate projects. In each cluster, create a Kubernetes namespace per team, and then configure Identity Aware Proxy so that each team can only access its own namespace.

Create a Development and a Production GKE cluster in separate projects. In each cluster, create a Kubernetes namespace per team, and then configure Kubernetes Role-based access control (RBAC) so that each team can only access its own namespace.

38. Your application services run in Google Kubernetes Engine (GKE). You want to make sure that only images from your centrally-managed Google Container Registry (GCR) image registry in the altostrat-images project can be deployed to the cluster while minimizing development time.

What should you do?

Create a custom builder for Cloud Build that will only push images to gcr.io/altostrat-images.

Use a Binary Authorization policy that includes the whitelist name pattern gcr.io/attostrat-images/.

Add logic to the deployment pipeline to check that all manifests contain only images from gcr.io/altostrat-images.

Add a tag to each image in gcr.io/altostrat-images and check that this tag is present when the image is deployed.

39. You want to share a Cloud Monitoring custom dashboard with a partner team.

What should you do?

Provide the partner team with the dashboard URL to enable the partner team to create a copy of the dashboard

Export the metrics to BigQuery Use Looker Studio to create a dashboard, and share the dashboard with the partner team

Copy the Monitoring Query Language (MQL) query from the dashboard; and send the MQL query to the partner team

Download the JSON definition of the dashboard, and send the JSON file to the partner team

40. Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.

What should you do?

Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.

Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.

Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.

Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.

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Google Professional Cloud DevOps Engineer Practice Exam

Google Professional Cloud DevOps Engineer Practice Exam

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