Google Professional-Cloud-Developer Exam Dumps

Google Certified Professional - Cloud Developer

Google Professional-Cloud-Developer Sample Questions

Question # 1

Your company has deployed a new API to App Engine Standard environment. During testing, the API is not behaving as expected. You want to monitor the application over time to diagnose the problem within the application code without redeploying the application. Which tool should you use? 

A. Stackdriver Trace 
B. Stackdriver Monitoring 
C. Stackdriver Debug Snapshots 
D. Stackdriver Debug Logpoints 

Answer: B

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Question # 2

You have been tasked with planning the migration of your company’s application from onpremises to Google Cloud. Your company’s monolithic application is an ecommerce website. The application will be migrated to microservices deployed on Google Cloud in stages. The majority of your company’s revenue is generated through online sales, so it is important to minimize risk during the migration. You need to prioritize features and select the first functionality to migrate. What should you do?

A. Migrate the Product catalog, which has integrations to the frontend and product database. 
B. Migrate Payment processing, which has integrations to the frontend, order database, and third-party payment vendor. 
C. Migrate Order fulfillment, which has integrations to the order database, inventory system, and third-party shipping vendor.
 D. Migrate the Shopping cart, which has integrations to the frontend, cart database, inventory system, and payment processing system.

Answer: A

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Question # 3

Your team develops services that run on Google Cloud. You need to build a data processing service and will use Cloud Functions. The data to be processed by the function is sensitive. You need to ensure that invocations can only happen from authorized services and follow Google-recommended best practices for securing functions. What should you do?

A. Enable Identity-Aware Proxy in your project. Secure function access using its permissions. 
B. Create a service account with the Cloud Functions Viewer role. Use that service account to invoke the function. 
C. Create a service account with the Cloud Functions Invoker role. Use that service account to invoke the function. 
D. Create an OAuth 2.0 client ID for your calling service in the same project as the function you want to secure. Use those credentials to invoke the function. 

Answer: C

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Question # 4

You have an HTTP Cloud Function that is called via POST. Each submission’s request body has a flat, unnested JSON structure containing numeric and text data. After the Cloud Function completes, the collected data should be immediately available for ongoing and complex analytics by many users in parallel. How should you persist the submissions?

A. Directly persist each POST request’s JSON data into Datastore. 
B. Transform the POST request’s JSON data, and stream it into BigQuery. 
C. Transform the POST request’s JSON data, and store it in a regional Cloud SQL cluster. 
D. Persist each POST request’s JSON data as an individual file within Cloud Storage, with the file name containing the request identifier. 

Answer: D

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Question # 5

Your application is running on Compute Engine and is showing sustained failures for a small number of requests. You have narrowed the cause down to a single Compute Engine instance, but the instance is unresponsive to SSH. What should you do next?

 A. Reboot the machine. 
B. Enable and check the serial port output. 
C. Delete the machine and create a new one. 
D. Take a snapshot of the disk and attach it to a new machine. 

Answer: A

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Question # 6

Your application is built as a custom machine image. You have multiple unique deployments of the machine image. Each deployment is a separate managed instance group with its own template. Each deployment requires a unique set of configuration values. You want to provide these unique values to each deployment but use the same custom machine image in all deployments. You want to use out-of-the-box features of Compute Engine. What should you do? 

A. Place the unique configuration values in the persistent disk.
B. Place the unique configuration values in a Cloud Bigtable table. 
C. Place the unique configuration values in the instance template startup script. 
D. Place the unique configuration values in the instance template instance metadata. 

Answer: A

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Question # 7

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. 

Answer: B

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Question # 8

Your company is planning to migrate their on-premises Hadoop environment to the cloud. Increasing storage cost and maintenance of data stored in HDFS is a major concern for your company. You also want to make minimal changes to existing data analytics jobs and existing architecture. How should you proceed with the migration?

A. Migrate your data stored in Hadoop to BigQuery. Change your jobs to source their information from BigQuery instead of the on-premises Hadoop environment.
 B. Create Compute Engine instances with HDD instead of SSD to save costs. Then perform a full migration of your existing environment into the new one in Compute Engine instances. 
C. Create a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop environment to the new Cloud Dataproc cluster. Move your HDFS data into larger HDD disks to save on storage costs. 
D. Create a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop code objects to the new cluster. Move your data to Cloud Storage and leverage the Cloud Dataproc connector to run jobs on that data.

Answer: D

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Question # 9

Your data is stored in Cloud Storage buckets. Fellow developers have reported that data downloaded from Cloud Storage is resulting in slow API performance. You want to research the issue to provide details to the GCP support team. Which command should you run?

A. gsutil test –o output.json gs://my-bucket 
B. gsutil perfdiag –o output.json gs://my-bucket 
C. gcloud compute scp example-instance:~/test-data –o output.json gs://my-bucket 
D. gcloud services test –o output.json gs://my-bucket 

Answer: B

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Question # 10

You have two tables in an ANSI-SQL compliant database with identical columns that you need to quickly combine into a single table, removing duplicate rows from the result set. What should you do?

A. Use the JOIN operator in SQL to combine the tables. 
B. Use nested WITH statements to combine the tables. 
C. Use the UNION operator in SQL to combine the tables. 
D. Use the UNION ALL operator in SQL to combine the tables.

Answer: C

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Question # 11

You are parsing a log file that contains three columns: a timestamp, an account number (a string), and a transaction amount (a number). You want to calculate the sum of all transaction amounts for each unique account number efficiently. Which data structure should you use?

A. A linked list 
B. A hash table 
C. A two-dimensional array 
D. A comma-delimited string

Answer: B

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Question # 12

You are developing an HTTP API hosted on a Compute Engine virtual machine instance that needs to be invoked by multiple clients within the same Virtual Private Cloud (VPC). You want clients to be able to get the IP address of the service. What should you do?

A. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule. Clients should use this IP address to connect to the service.
 B. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule. Then, define an A record in Cloud DNS. Clients should use the name of the A record to connect to the service.
 C. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url https://[INSTANCE_NAME].[ZONE].c.[PROJECT_ID].internal/. 
D. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url https://[API_NAME]/[API_VERSION]/. 

Answer: D

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Question # 13

You are developing a new application that has the following design requirements: Creation and changes to the application infrastructure are versioned and auditable. The application and deployment infrastructure uses Google-managed services as much as possible. The application runs on a serverless compute platform. How should you design the application’s architecture?

A. 1. Store the application and infrastructure source code in a Git repository. 2. Use Cloud Build to deploy the application infrastructure with Terraform. 3. Deploy the application to a Cloud Function as a pipeline step. 
B. 1. Deploy Jenkins from the Google Cloud Marketplace, and define a continuous integration pipeline in Jenkins. 2. Configure a pipeline step to pull the application source code from a Git repository. 3. Deploy the application source code to App Engine as a pipeline step. 
C. 1. Create a continuous integration pipeline on Cloud Build, and configure the pipeline to deploy the application infrastructure using Deployment Manager templates. 2. Configure a pipeline step to create a container with the latest application source code. 3. Deploy the container to a Compute Engine instance as a pipeline step.
D. 1. Deploy the application infrastructure using gcloud commands. 2. Use Cloud Build to define a continuous integration pipeline for changes to the application source code. 3. Configure a pipeline step to pull the application source code from a Git repository, and create a containerized application. 4. Deploy the new container on Cloud Run as a pipeline step. 

Answer: D

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