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 Professional-Cloud-Developer Dumps with Practice Exam Questions Answers

Questions: 254 questions

Last Update: May 13, 2024

Professional-Cloud-Developer Question Includes: Single Choice Questions: 237, Multiple Choice Questions: 17,

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Professional-Cloud-Developer Questions and Answers

Question # 1

For this question, refer to the HipLocal case study.

A recent security audit discovers that HipLocal’s database credentials for their Compute Engine-hosted MySQL databases are stored in plain text on persistent disks. HipLocal needs to reduce the risk of these credentials being stolen. What should they do?


Create a service account and download its key. Use the key to authenticate to Cloud Key Management Service (KMS) to obtain the database credentials.


Create a service account and download its key. Use the key to authenticate to Cloud Key Management Service (KMS) to obtain a key used to decrypt the database credentials.


Create a service account and grant it the roles/iam.serviceAccountUser role. Impersonate as this account and authenticate using the Cloud SQL Proxy.


Grant the roles/secretmanager.secretAccessor role to the Compute Engine service account. Store and access the database credentials with the Secret Manager API.

Question # 2

HipLocal has connected their Hadoop infrastructure to GCP using Cloud Interconnect in order to query data stored on persistent disks.

Which IP strategy should they use?


Create manual subnets.


Create an auto mode subnet.


Create multiple peered VPCs.


Provision a single instance for NAT.

Question # 3

HipLocal’s data science team wants to analyze user reviews.

How should they prepare the data?


Use the Cloud Data Loss Prevention API for redaction of the review dataset.


Use the Cloud Data Loss Prevention API for de-identification of the review dataset.


Use the Cloud Natural Language Processing API for redaction of the review dataset.


Use the Cloud Natural Language Processing API for de-identification of the review dataset.

Question # 4

For this question refer to the HipLocal case study.

HipLocal wants to reduce the latency of their services for users in global locations. They have created read replicas of their database in locations where their users reside and configured their service to read traffic using those replicas. How should they further reduce latency for all database interactions with the least amount of effort?


Migrate the database to Bigtable and use it to serve all global user traffic.


Migrate the database to Cloud Spanner and use it to serve all global user traffic.


Migrate the database to Firestore in Datastore mode and use it to serve all global user traffic.


Migrate the services to Google Kubernetes Engine and use a load balancer service to better scale the application.

Question # 5

HipLocal's APIs are showing occasional failures, but they cannot find a pattern. They want to collect some

metrics to help them troubleshoot.

What should they do?


Take frequent snapshots of all of the VMs.


Install the Stackdriver Logging agent on the VMs.


Install the Stackdriver Monitoring agent on the VMs.


Use Stackdriver Trace to look for performance bottlenecks.