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  • Exam Name: Google Certified Professional - Cloud Developer
  • Last Update: 02-Mar-2024
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Professional-Cloud-Developer Questions and Answers

Question # 1

You have an application deployed in production. When a new version is deployed, some issues don't arise until the application receives traffic from users in production. You want to reduce both the impact and the number of users affected.

Which deployment strategy should you use?


Blue/green deployment


Canary deployment


Rolling deployment


Recreate deployment

Question # 2

Before promoting your new application code to production, you want to conduct testing across a variety of different users. Although this plan is risky, you want to test the new version of the application with production users and you want to control which users are forwarded to the new version of the application based on their operating system. If bugs are discovered in the new version, you want to roll back the newly deployed version of the application as quickly as possible.

What should you do?


Deploy your application on Cloud Run. Use traffic splitting to direct a subset of user traffic to the new version based on the revision tag.


Deploy your application on Google Kubernetes Engine with Anthos Service Mesh. Use traffic splitting to direct a subset of user traffic to the new version based on the user-agent header.


Deploy your application on App Engine. Use traffic splitting to direct a subset of user traffic to the new version based on the IP address.


Deploy your application on Compute Engine. Use Traffic Director to direct a subset of user traffic to the new version based on predefined weights.

Question # 3

You are deploying a microservices application to Google Kubernetes Engine (GKE) that will broadcast livestreams. You expect unpredictable traffic patterns and large variations in the number of concurrent users. Your application must meet the following requirements:

• Scales automatically during popular events and maintains high availability

• Is resilient in the event of hardware failures

How should you configure the deployment parameters? (Choose two.)


Distribute your workload evenly using a multi-zonal node pool.


Distribute your workload evenly using multiple zonal node pools.


Use cluster autoscaler to resize the number of nodes in the node pool, and use a Horizontal Pod Autoscaler to scale the workload.


Create a managed instance group for Compute Engine with the cluster nodes. Configure autoscaling rules for the managed instance group.


Create alerting policies in Cloud Monitoring based on GKE CPU and memory utilization. Ask an on-duty engineer to scale the workload by executing a script when CPU and memory usage exceed predefined thresholds.

Question # 4

You plan to deploy a new application revision with a Deployment resource to Google Kubernetes Engine (GKE) in production. The container might not work correctly. You want to minimize risk in case there are issues after deploying the revision. You want to follow Google-recommended best practices. What should you do?


Perform a rolling update with a PodDisruptionBudget of 80%.


Perform a rolling update with a HorizontalPodAutoscaler scale-down policy value of 0.


Convert the Deployment to a StatefulSet, and perform a rolling update with a PodDisruptionBudget of 80%.


Convert the Deployment to a StatefulSet, and perform a rolling update with a HorizontalPodAutoscaler scale-down policy value of 0.

Question # 5

You have an analytics application that runs hundreds of queries on BigQuery every few minutes using BigQuery API. You want to find out how much time these queries take to execute. What should you do?


Use Stackdriver Monitoring to plot slot usage.


Use Stackdriver Trace to plot API execution time.


Use Stackdriver Trace to plot query execution time.


Use Stackdriver Monitoring to plot query execution times.

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