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?

Place the unique configuration values in the persistent disk.

Place the unique configuration values in a Cloud Bigtable table.

Place the unique configuration values in the instance template startup script.

Place the unique configuration values in the instance template instance metadata.

Your application performs well when tested locally, but it runs significantly slower when you deploy it to App Engine standard environment. You want to diagnose the problem. What should you do?

Add logging commands to the application and use Stackdriver Logging to check where the latency problem occurs.

File a ticket with Cloud Support indicating that the application performs faster locally.

Use Stackdriver Debugger Snapshots to look at a point-in-time execution of the application.

Use Stackdriver Trace to determine which functions within the application have higher latency.

Add logging commands to the application and use Stackdriver Logging to check where the latency problem occurs.

You have an application running in App Engine. Your application is instrumented with Stackdriver Trace. The /product-details request reports details about four known unique products at /sku-details as shown below. You want to reduce the time it takes for the request to complete. What should you do?

Change /product-details to perform the requests in parallel.

Increase the size of the instance class.

Change the Persistent Disk type to SSD.

Change /product-details to perform the requests in parallel.

Store the /sku-details information in a database, and replace the webservice call with a database query.

Your company has a data warehouse that keeps your application information in BigQuery. The BigQuery data warehouse keeps 2 PBs of user data. Recently, your company expanded your user base to include EU users and needs to comply with these requirements:Your company must be able to delete all user account information upon user request.All EU user data must be stored in a single region specifically for EU users.Which two actions should you take? (Choose two.)

Create a Cloud Storage bucket in the EU region to store information for EU users only.

Use DML statements in BigQuery to update/delete user records based on their requests.

Use BigQuery federated queries to query data from Cloud Storage.

Create a dataset in the EU region that will keep information about EU users only.

Create a Cloud Storage bucket in the EU region to store information for EU users only.

Re-upload your data using to a Cloud Dataflow pipeline by filtering your user records out.

Use DML statements in BigQuery to update/delete user records based on their requests.

Your App Engine standard configuration is as follows:service: productioninstance_class: B1You want to limit the application to 5 instances. Which code snippet should you include in your configuration?

basic_scaling:instances: 5min_pending_latency: 30ms

manual_scaling:instances: 5min_pending_latency: 30ms

manual_scaling:max_instances: 5idle_timeout: 10m

basic_scaling:instances: 5min_pending_latency: 30ms

basic_scaling:max_instances: 5idle_timeout: 10m

Your analytics system executes queries against a BigQuery dataset. The SQL query is executed in batch and passes the contents of a SQL file to the BigQuery CLI. Then it redirects the BigQuery CLI output to another process. However, you are getting a permission error from the BigQuery CLI when the queries are executed. You want to resolve the issue. What should you do?

Grant the service account BigQuery Data Editor and BigQuery Data Viewer roles.

Grant the service account BigQuery Data Viewer and BigQuery Job User roles.

Grant the service account BigQuery Data Editor and BigQuery Data Viewer roles.

Create a view in BigQuery from the SQL query and SELECT* from the view in the CLI.

Create a new dataset in BigQuery, and copy the source table to the new dataset Query the new dataset and table from the CLI.

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?

Enable and check the serial port output.

Delete the machine and create a new one.

Take a snapshot of the disk and attach it to a new machine.

You configured your Compute Engine instance group to scale automatically according to overall CPU usage. However, your application's response latency increases sharply before the cluster has finished adding up instances. You want to provide a more consistent latency experience for your end users by changing the configuration ot the instance group autoscaler. Which two configuration changes should you make? (Choose two.)

Add the label ''AUTOSCALE'' to the instance group template.

Increase the target CPU usage for the instance group autoscaler.

Add the label ''AUTOSCALE'' to the instance group template.

Decrease the cool-down period for instances added to the group.

Increase the target CPU usage for the instance group autoscaler.

Decrease the target CPU usage for the instance group autoscaler.

Remove the health-check for individual VMs in the instance group.

You have an application controlled by a managed instance group. When you deploy a new version of the application, costs should be minimized and the number of instances should not increase. You want to ensure that, when each new instance is created, the deployment only continues if the new instance is healthy. What should you do?

Perform a rolling-action with maxSurge set to 1, maxUnavailable set to 0.

Perform a rolling-action with maxSurge set to 0, maxUnavailable set to 1

Perform a rolling-action with maxHealthy set to 1, maxUnhealthy set to 0.

Perform a rolling-action with maxHealthy set to 0, maxUnhealthy set to 1.

Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible. What should you do?

Use the instance's service account Application Default Credentials to authenticate to the required resources.

Use HTTP signed URLs to securely provide access to the required resources.

Use the instance's service account Application Default Credentials to authenticate to the required resources.

Generate a P12 file from the GCP Console after the instance is deployed, and copy the credentials to the host instance before starting the application.

Commit the credential JSON file into your application's source repository, and have your CI/CD process package it with the software that is deployed to the instance.

Your application is deployed in a Google Kubernetes Engine (GKE) cluster. You want to expose this application publicly behind a Cloud Load Balancing HTTP(S) load balancer. What should you do?

Configure a GKE Ingress resource.

Configure a GKE Service resource.

Configure a GKE Ingress resource with type: LoadBalancer.

Configure a GKE Service resource with type: LoadBalancer.

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?

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.

Migrate your data stored in Hadoop to BigQuery. Change your jobs to source their information from BigQuery instead of the on-premises Hadoop environment.

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.

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.

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.

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?

gsutil perfdiag --o output.json gs://my-bucket

gsutil test --o output.json gs://my-bucket

gsutil perfdiag --o output.json gs://my-bucket

gcloud compute scp example-instance:~/test-data --o output.json gs://my-bucket

gcloud services test --o output.json gs://my-bucket

You are using Cloud Build build to promote a Docker image to Development, Test, and Production environments. You need to ensure that the same Docker image is deployed to each of these environments. How should you identify the Docker image in your build?

Use a semantic version Docker image tag.

Use the latest Docker image tag.

Use a unique Docker image name.

Use the digest of the Docker image.

Use a semantic version Docker image tag.

Your company has created an application that uploads a report to a Cloud Storage bucket. When the report is uploaded to the bucket, you want to publish a message to a Cloud Pub/Sub topic. You want to implement a solution that will take a small amount to effort to implement. What should you do?

Create a Cloud Function that is triggered by the Cloud Storage bucket. In the Cloud Function, publish a message to the Cloud Pub/Sub topic.

Configure the Cloud Storage bucket to trigger Cloud Pub/Sub notifications when objects are modified.

Create an App Engine application to receive the file; when it is received, publish a message to the Cloud Pub/Sub topic.

Create a Cloud Function that is triggered by the Cloud Storage bucket. In the Cloud Function, publish a message to the Cloud Pub/Sub topic.

Create an application deployed in a Google Kubernetes Engine cluster to receive the file; when it is received, publish a message to the Cloud Pub/Sub topic.

Your teammate has asked you to review the code below, which is adding a credit to an account balance in Cloud Datastore. Which improvement should you suggest your teammate make?

Get the entity with an ancestor query.

Get and put the entity in a transaction.

Use a strongly consistent transactional database.

Don't return the account entity from the function.

Your company stores their source code in a Cloud Source Repositories repository. Your company wants to build and test their code on each source code commit to the repository and requires a solution that is managed and has minimal operations overhead.Which method should they use?

Use Cloud Build with a trigger configured for each source code commit.

Use Jenkins deployed via the Google Cloud Platform Marketplace, configured to watch for source code commits.

Use a Compute Engine virtual machine instance with an open source continuous integration tool, configured to watch for source code commits.

Use a source code commit trigger to push a message to a Cloud Pub/Sub topic that triggers an App Engine service to build the source code.

You are writing a Compute Engine hosted application in project A that needs to securely authenticate to a Cloud Pub/Sub topic in project B.What should you do?

Configure the instances with a service account owned by project A. Add the service account as a publisher on the topic.

Configure the instances with a service account owned by project B. Add the service account as a Cloud Pub/Sub publisher to project A.

Configure the instances with a service account owned by project A. Add the service account as a publisher on the topic.

Configure Application Default Credentials to use the private key of a service account owned by project B. Add the service account as a Cloud Pub/Sub publisher to project A.

Configure Application Default Credentials to use the private key of a service account owned by project A. Add the service account as a publisher on the topic

You are developing a corporate tool on Compute Engine for the finance department, which needs to authenticate users and verify that they are in the finance department. All company employees use G Suite.What should you do?

Enable Cloud Identity-Aware Proxy on the HTTP(s) load balancer and restrict access to a Google Group containing users in the finance department. Verify the provided JSON Web Token within the application.

Enable Cloud Identity-Aware Proxy on the HTTP(s) load balancer and restrict access to a Google Group containing users in the finance department. Issue client-side certificates to everybody in the finance team and verify the certificates in the application.

Configure Cloud Armor Security Policies to restrict access to only corporate IP address ranges. Verify the provided JSON Web Token within the application.

Configure Cloud Armor Security Policies to restrict access to only corporate IP address ranges. Issue client side certificates to everybody in the finance team and verify the certificates in the application.

Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API.Which two steps should you take? (Choose two.)

Use Zipkin collector to gather data.

Use Stackdriver Trace to generate reports.

Use Zipkin collector to gather data.

Use Fluentd agent to gather data.

Use Stackdriver Trace to generate reports.

Use Stackdriver Debugger to generate report.

Use Stackdriver Profiler to generate report.

You are porting an existing Apache/MySQL/PHP application stack from a single machine to Google Kubernetes Engine. You need to determine how to containerize the application. Your approach should follow Google-recommended best practices for availability. What should you do?

Package each component in a separate container. Implement readiness and liveness probes.

Package the application in a single container. Use a process management tool to manage each component.

Package each component in a separate container. Use a script to orchestrate the launch of the components.

Package the application in a single container. Use a bash script as an entrypoint to the container, and then spawn each component as a background job.

You are developing an application that will be launched on Compute Engine instances into multiple distinct projects, each corresponding to the environments in your software development process (development, QA, staging, and production). The instances in each project have the same application code but a different configuration. During deployment, each instance should receive the application's configuration based on the environment it serves. You want to minimize the number of steps to configure this flow.What should you do?

In each project, configure a metadata key ''environment'' whose value is the environment it serves. Use your deployment tool to query the instance metadata and configure the application based on the ''environment'' value.

When creating your instances, configure a startup script using the gcloud command to determine the project name that indicates the correct environment.

In each project, configure a metadata key ''environment'' whose value is the environment it serves. Use your deployment tool to query the instance metadata and configure the application based on the ''environment'' value.

Deploy your chosen deployment tool on an instance in each project. Use a deployment job to retrieve the appropriate configuration file from your version control system, and apply the configuration when deploying the application on each instance.

During each instance launch, configure an instance custom-metadata key named ''environment'' whose value is the environment the instance serves. Use your deployment tool to query the instance metadata, and configure the application based on the ''environment'' value.

You are developing an ecommerce application that stores customer, order, and inventory data as relational tables inside Cloud Spanner. During a recent load test, you discover that Spanner performance is not scaling linearly as expected. Which of the following is the cause?

The use of Version 1 UUIDs as primary keys that increase monotonically.

The use of 64-bit numeric types for 32-bit numbers.

The use of the STRING data type for arbitrary-precision values.

The use of Version 1 UUIDs as primary keys that increase monotonically.

The use of LIKE instead of STARTS_WITH keyword for parameterized SQL queries.

You are developing an application that reads credit card data from a Pub/Sub subscription. You have written code and completed unit testing. You need to test the Pub/Sub integration before deploying to Google Cloud. What should you do?

Create a service to publish messages, and deploy the Pub/Sub emulator. Publish a standard set of testing messages from the publishing service to the emulator.

Create a service to publish messages, and deploy the Pub/Sub emulator. Generate random content in the publishing service, and publish to the emulator.

Create a service to publish messages to your application. Collect the messages from Pub/Sub in production, and replay them through the publishing service.

Create a service to publish messages, and deploy the Pub/Sub emulator. Collect the messages from Pub/Sub in production, and publish them to the emulator.

Create a service to publish messages, and deploy the Pub/Sub emulator. Publish a standard set of testing messages from the publishing service to the emulator.

You are designing an application that will subscribe to and receive messages from a single Pub/Sub topic and insert corresponding rows into a database. Your application runs on Linux and leverages preemptible virtual machines to reduce costs. You need to create a shutdown script that will initiate a graceful shutdown. What should you do?

Write a shutdown script that publishes a message to the Pub/Sub topic announcing that a shutdown is in progress. After the application reads the message, it disconnects from the database.

Write a shutdown script that uses inter-process signals to notify the application process to disconnect from the database.

Write a shutdown script that broadcasts a message to all signed-in users that the Compute Engine instance is going down and instructs them to save current work and sign out.

Write a shutdown script that writes a file in a location that is being polled by the application once every five minutes. After the file is read, the application disconnects from the database.

Write a shutdown script that publishes a message to the Pub/Sub topic announcing that a shutdown is in progress. After the application reads the message, it disconnects from the database.

You work for a web development team at a small startup. Your team is developing a Node.js application using Google Cloud services, including Cloud Storage and Cloud Build. The team uses a Git repository for version control. Your manager calls you over the weekend and instructs you to make an emergency update to one of the company's websites, and you're the only developer available. You need to access Google Cloud to make the update, but you don't have your work laptop. You are not allowed to store source code locally on a non-corporate computer. How should you set up your developer environment?

Use Cloud Shell and the built-in code editor for development. Send your source code updates as pull requests.

Use a text editor and the Git command line to send your source code updates as pull requests from a public computer.

Use a text editor and the Git command line to send your source code updates as pull requests from a virtual machine running on a public computer.

Use Cloud Shell and the built-in code editor for development. Send your source code updates as pull requests.

Use a Cloud Storage bucket to store the source code that you need to edit. Mount the bucket to a public computer as a drive, and use a code editor to update the code. Turn on versioning for the bucket, and point it to the team's Git repository.

Your team develops services that run on Google Kubernetes Engine. You need to standardize their log data using Google-recommended practices and make the data more useful in the fewest number of steps. What should you do? (Choose two.)

Create aggregated exports on application logs to BigQuery to facilitate log analytics.

Write log output to standard output (stdout) as single-line JSON to be ingested into Cloud Logging as structured logs.

Create aggregated exports on application logs to BigQuery to facilitate log analytics.

Create aggregated exports on application logs to Cloud Storage to facilitate log analytics.

Write log output to standard output (stdout) as single-line JSON to be ingested into Cloud Logging as structured logs.

Mandate the use of the Logging API in the application code to write structured logs to Cloud Logging.

Mandate the use of the Pub/Sub API to write structured data to Pub/Sub and create a Dataflow streaming pipeline to normalize logs and write them to BigQuery for analytics.

You are designing a deployment technique for your new applications on Google Cloud. As part of your deployment planning, you want to use live traffic to gather performance metrics for both new and existing applications. You need to test against the full production load prior to launch. What should you do?

Use A/B testing with traffic mirroring during deployment

You support an application that uses the Cloud Storage API. You review the logs and discover multiple HTTP 503 Service Unavailable error responses from the API. Your application logs the error and does not take any further action. You want to implement Google-recommended retry logic to improve success rates. Which approach should you take?

Retry each failure at increasing time intervals up to a maximum number of tries.

Retry the failures in batch after a set number of failures is logged.

Retry each failure at a set time interval up to a maximum number of times.

Retry each failure at increasing time intervals up to a maximum number of tries.

Retry each failure at decreasing time intervals up to a maximum number of tries.

You need to redesign the ingestion of audit events from your authentication service to allow it to handle a large increase in traffic. Currently, the audit service and the authentication system run in the same Compute Engine virtual machine. You plan to use the following Google Cloud tools in the new architecture:Multiple Compute Engine machines, each running an instance of the authentication serviceMultiple Compute Engine machines, each running an instance of the audit servicePub/Sub to send the events from the authentication services.How should you set up the topics and subscriptions to ensure that the system can handle a large volume of messages and can scale efficiently?

Create one Pub/Sub topic. Create one pull subscription to allow the audit services to share the messages.

Create one Pub/Sub topic. Create one pull subscription per audit service instance to allow the services to share the messages.

Create one Pub/Sub topic. Create one push subscription with the endpoint pointing to a load balancer in front of the audit services.

Create one Pub/Sub topic per authentication service. Create one pull subscription per topic to be used by one audit service.

Create one Pub/Sub topic per authentication service. Create one push subscription per topic, with the endpoint pointing to one audit service.

You are developing a marquee stateless web application that will run on Google Cloud. The rate of the incoming user traffic is expected to be unpredictable, with no traffic on some days and large spikes on other days. You need the application to automatically scale up and down, and you need to minimize the cost associated with running the application. What should you do?

Build the application in Python with Firestore as the database. Deploy the application to Cloud Run.

Build the application in C# with Firestore as the database. Deploy the application to App Engine flexible environment.

Build the application in Python with CloudSQL as the database. Deploy the application to App Engine standard environment.

Build the application in Python with Firestore as the database. Deploy the application to a Compute Engine managed instance group with autoscaling.

You have written a Cloud Function that accesses other Google Cloud resources. You want to secure the environment using the principle of least privilege. What should you do?

Create a new service account that has a custom IAM role to access the resources. The deployer is given permission to act as the new service account.

Create a new service account that has Editor authority to access the resources. The deployer is given permission to get the access token.

Create a new service account that has a custom IAM role to access the resources. The deployer is given permission to get the access token.

Create a new service account that has Editor authority to access the resources. The deployer is given permission to act as the new service account.

Create a new service account that has a custom IAM role to access the resources. The deployer is given permission to act as the new service account.

You are a SaaS provider deploying dedicated blogging software to customers in your Google Kubernetes Engine (GKE) cluster. You want to configure a secure multi-tenant platform to ensure that each customer has access to only their own blog and can't affect the workloads of other customers. What should you do?

Deploy a namespace per tenant and use Network Policies in each blog deployment.

Enable Application-layer Secrets on the GKE cluster to protect the cluster.

Deploy a namespace per tenant and use Network Policies in each blog deployment.

Use GKE Audit Logging to identify malicious containers and delete them on discovery.

Build a custom image of the blogging software and use Binary Authorization to prevent untrusted image deployments.

You are developing an internal application that will allow employees to organize community events within your company. You deployed your application on a single Compute Engine instance. Your company uses Google Workspace (formerly G Suite), and you need to ensure that the company employees can authenticate to the application from anywhere. What should you do?

Add an HTTP(S) load balancer in front of the instance, and set up Identity-Aware Proxy (IAP). Configure the IAP settings to allow your company domain to access the website.

Add a public IP address to your instance, and restrict access to the instance using firewall rules. Allow your company's proxy as the only source IP address.

Add an HTTP(S) load balancer in front of the instance, and set up Identity-Aware Proxy (IAP). Configure the IAP settings to allow your company domain to access the website.

Set up a VPN tunnel between your company network and your instance's VPC location on Google Cloud. Configure the required firewall rules and routing information to both the on-premises and Google Cloud networks.

Add a public IP address to your instance, and allow traffic from the internet. Generate a random hash, and create a subdomain that includes this hash and points to your instance. Distribute this DNS address to your company's employees.

You are developing a web application that will be accessible over both HTTP and HTTPS and will run on Compute Engine instances. On occasion, you will need to SSH from your remote laptop into one of the Compute Engine instances to conduct maintenance on the app. How should you configure the instances while following Google-recommended best practices?

Configure Cloud Identity-Aware Proxy API for SSH access. Then configure the Compute Engine servers with private IP addresses behind an HTTP(s) load balancer for the application web traffic.

Set up a backend with Compute Engine web server instances with a private IP address behind a TCP proxy load balancer.

Configure the firewall rules to allow all ingress traffic to connect to the Compute Engine web servers, with each server having a unique external IP address.

Configure Cloud Identity-Aware Proxy API for SSH access. Then configure the Compute Engine servers with private IP addresses behind an HTTP(s) load balancer for the application web traffic.

Set up a backend with Compute Engine web server instances with a private IP address behind an HTTP(S) load balancer. Set up a bastion host with a public IP address and open firewall ports. Connect to the web instances using the bastion host.

You have a mixture of packaged and internally developed applications hosted on a Compute Engine instance that is running Linux. These applications write log records as text in local files. You want the logs to be written to Cloud Logging. What should you do?

Install a Google version of fluentd on the Compute Engine instance.

Pipe the content of the files to the Linux Syslog daemon.

Install a Google version of fluentd on the Compute Engine instance.

Install a Google version of collectd on the Compute Engine instance.

Using cron, schedule a job to copy the log files to Cloud Storage once a day.

Google Professional Cloud Developer Practice Test 3 - Free Online Exam Prep & Questions

You are working on a social media application. You plan to add a feature that allows users to upload images. These images will be 2 MB -- 1 GB in size. You want to minimize their infrastructure operations overhead for this feature. What should you do?

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Google Professional Cloud Developer Practice Test 3

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