You want to re-architect a monolithic application so that it follows a microservices model.

You want to

accomplish this efficiently while minimizing the impact of this change to the business.

Which approach should you take?

A. Deploy the application to Compute Engine and turn on autoscaling.

B. Replace the application's features with appropriate microservices in phases.

C. Refactor the monolithic application with appropriate microservices in a single effort and deploy it.

D. Build a new application with the appropriate microservices separate from the monolith and replace it when it is complete.

You are supporting a business-critical application in production deployed on Cloud Run. The application is reporting HTTP 500 errors that are affecting the usability of the application. You want to be alerted when the number of errors exceeds 15% of the requests within a specific time window. What should you do?

A. Navigate to the Cloud Run page in the Google Cloud console, and select the service from the services list. Use the Metrics tab to visualize the number of errors for that revision and refresh the page daily.

B. Create a Cloud Function that consumes the Cloud Monitoring API Use Cloud Composer to trigger the Cloud Function daily and alert you if the number of errors is above the defined threshold.

C. Create an alerting policy in Cloud Monitoring that alerts you if the number of errors is above the defined threshold.

D. Create a Cloud Function that consumes the Cloud Monitoring API Use Cloud Scheduler to trigger the Cloud Function daily and alert you if the number of errors is above the defined threshold

Your team develops services that run on Google Cloud. You want to process messages sent to a Pub/Sub topic, and then store them. Each message must be processed exactly once to avoid duplication of data and any data conflicts. You need to use the cheapest and most simple solution. What should you do?

A. Process the messages with a Dataproc job, and write the output to storage.

B. Process the messages with a Dataflow streaming pipeline using Apache Beam's PubSubIO package, and write the output to storage.

C. Process the messages with a Cloud Function, and write the results to a BigQuery location where you can run a job to deduplicate the data.

D. Retrieve the messages with a Dataflow streaming pipeline, store them in Cloud Bigtable, and use another Dataflow streaming pipeline to deduplicate messages.

Your team develops services that run on Google Kubernetes Engine. Your team's code is stored in Cloud Source Repositories. You need to quickly identify bugs in the code before it is deployed to production. You want to invest in automation to improve developer feedback and make the process as efficient as possible. What should you do?

A. Use Spinnaker to automate building container images from code based on Git tags.

B. Use Cloud Build to automate building container images from code based on Git tags.

C. Use Spinnaker to automate deploying container images to the production environment.

D. Use Cloud Build to automate building container images from code based on forked versions.

You are deploying your application to a Compute Engine virtual machine instance with the Stackdriver

Monitoring Agent installed. Your application is a unix process on the instance. You want to be alerted if the unix process has not run for at least 5 minutes. You are not able to change the application to generate metrics or logs.

Which alert condition should you configure?

A. Uptime check

B. Process health

C. Metric absence

D. Metric threshold

You are designing an application that uses a microservices architecture. You are planning to deploy the application in the cloud and on-premises. You want to make sure the application can scale up on demand and also use managed

services as much as possible.

What should you do?

A. Deploy open source Istio in a multi-cluster deployment on multiple Google Kubernetes Engine (GKE) clusters managed by Anthos.

B. Create a GKE cluster in each environment with Anthos, and use Cloud Run for Anthos to deploy your application to each cluster.

C. Install a GKE cluster in each environment with Anthos, and use Cloud Build to create a Deployment for your application in each cluster.

D. Create a GKE cluster in the cloud and install open-source Kubernetes on-premises. Use an external load balancer service to distribute traffic across the two environments.

You recently developed a new service on Cloud Run. The new service authenticates using a custom service and then writes transactional information to a Cloud Spanner database. You need to verify that your application can support up to 5,000 read and 1,000 write transactions per second while identifying any bottlenecks that occur. Your test infrastructure must be able to autoscale. What should you do?

A. Build a test harness to generate requests and deploy it to Cloud Run. Analyze the VPC Flow Logs using Cloud Logging.

B. Create a Google Kubernetes Engine cluster running the Locust or JMeter images to dynamically generate load tests. Analyze the results using Cloud Trace.

C. Create a Cloud Task to generate a test load. Use Cloud Scheduler to run 60,000 Cloud Task transactions per minute for 10 minutes. Analyze the results using Cloud Monitoring.

D. Create a Compute Engine instance that uses a LAMP stack image from the Marketplace, and use Apache Bench to generate load tests against the service. Analyze the results using Cloud Trace.

You are trying to connect to your Google Kubernetes Engine (GKE) cluster using kubectl from Cloud Shell. You have deployed your GKE cluster with a public endpoint. From Cloud Shell, you run the following command:

You notice that the kubectl commands time out without returning an error message. What is the most likely cause of this issue?

A. Your user account does not have privileges to interact with the cluster using kubectl.

B. Your Cloud Shell external IP address is not part of the authorized networks of the cluster.

C. The Cloud Shell is not part of the same VPC as the GKE cluster.

D. A VPC firewall is blocking access to the cluster's endpoint.

You have an application written in Python running in production on Cloud Run. Your application needs to read/write data stored in a Cloud Storage bucket in the same project. You want to grant access to your application following the principle of least privilege. What should you do?

A. Create a user-managed service account with a custom Identity and Access Management (IAM) role.

B. Create a user-managed service account with the Storage Admin Identity and Access Management (IAM) role.

C. Create a user-managed service account with the Project Editor Identity and Access Management (IAM) role.

D. Use the default service account linked to the Cloud Run revision in production.

You are planning to migrate a MySQL database to the managed Cloud SQL database for Google Cloud. You have Compute Engine virtual machine instances that will connect with this Cloud SQL instance. You do not want to whitelist IPs for the Compute Engine instances to be able to access Cloud SQL.

What should you do?

A. Enable private IP for the Cloud SQL instance.

B. Whitelist a project to access Cloud SQL, and add Compute Engine instances in the whitelisted project.

C. Create a role in Cloud SQL that allows access to the database from external instances, and assign the Compute Engine instances to that role.

D. Create a CloudSQL instance on one project. Create Compute engine instances in a different project. Create a VPN between these two projects to allow internal access to CloudSQL.