[Jun 11, 2023] Professional-Cloud-Developer Test Engine files, Professional-Cloud-Developer Dumps PDF
Latest Google Professional-Cloud-Developer PDF and Dumps (2023) Free Exam Questions Answers
The Google Professional-Cloud-Developer Certification Exam is designed for professionals who want to demonstrate their skills in developing cloud-based applications using the Google Cloud Platform. This certification validates the skills and knowledge required to develop and deploy applications using Google Cloud technologies, such as App Engine, Cloud Storage, Cloud SQL, and Compute Engine.
The Professional-Cloud-Developer exam is intended for developers who have experience in building applications on Google Cloud, and who are looking to demonstrate their expertise to potential employers and clients. The exam covers a wide range of topics, including cloud computing concepts, Google Cloud services, application development, and deployment.
To prepare for the Professional-Cloud-Developer exam, candidates should have a solid understanding of cloud computing concepts and be familiar with the Google Cloud platform. They should also have experience in one or more programming languages, such as Java, Python, or JavaScript, as well as experience in developing and deploying applications on Google Cloud.
NEW QUESTION # 21
Your team is developing an application in Google Cloud that executes with user identities maintained by Cloud Identity. Each of your application's users will have an associated Pub/Sub topic to which messages are published, and a Pub/Sub subscription where the same user will retrieve published messages. You need to ensure that only authorized users can publish and subscribe to their own specific Pub/Sub topic and subscription. What should you do?
- A. Grant the user identity the pubsub.publisher and pubsub.subscriber roles at the project level.
- B. Bind the user identity to the pubsub.publisher and pubsub.subscriber roles at the resource level.
- C. Configure the application to run as a service account that has the pubsub.publisher and pubsub.subscriber roles.
- D. Grant the user identity a custom role that contains the pubsub.topics.create and pubsub.subscriptions.create permissions.
Answer: D
NEW QUESTION # 22
You are evaluating developer tools to help drive Google Kubernetes Engine adoption and integration with your development environment, which includes VS Code and IntelliJ. What should you do?
- A. Use a Cloud Notebook instance to ingest and process data and deploy models.
- B. Use the Cloud Shell integrated Code Editor to edit code and configuration files.
- C. Use Cloud Shell to manage your infrastructure and applications from the command line.
- D. Use Cloud Code to develop applications.
Answer: D
Explanation:
Reference: https://cloud.google.com/code
NEW QUESTION # 23
You are developing an application using different microservices that should remain internal to the cluster. You want to be able to configure each microservice with a specific number of replicas. You also want to be able to address a specific microservice from any other microservice in a uniform way, regardless of the number of replicas the microservice scales to. You need to implement this solution on Google Kubernetes Engine. What should you do?
- A. Deploy each microservice as a Pod. Expose the Pod in the cluster using a Service, and use the Service DNS name to address the microservice from other microservices within the cluster.
- B. Deploy each microservice as a Pod. Expose the Pod in the cluster using an Ingress, and use the Ingress IP address name to address the Pod from other microservices within the cluster.
- C. Deploy each microservice as a Deployment. Expose the Deployment in the cluster using an Ingress, and use the Ingress IP address to address the Deployment from other microservices within the cluster.
- D. Deploy each microservice as a Deployment. Expose the Deployment in the cluster using a Service, and use the Service DNS name to address it from other microservices within the cluster.
Answer: D
NEW QUESTION # 24
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?
- A. Create manual subnets.
- B. Create an auto mode subnet.
- C. Create multiple peered VPCs.
- D. Provision a single instance for NAT.
Answer: A
NEW QUESTION # 25
The new version of your containerized application has been tested and is ready to deploy to production on Google Kubernetes Engine. You were not able to fully load-test the new version in pre-production environments, and you need to make sure that it does not have performance problems once deployed. Your deployment must be automated. What should you do?
- A. Use Cloud Load Balancing to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues.
- B. Deploy the application using kubectl and set the spec.updateStrategv.type to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.
- C. Deploy the application via a continuous delivery pipeline using blue/green deployments. Use Cloud Monitoring to look for performance issues, and launch fully when the metrics support it.
- D. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues. and ramp up traffic as the metrics support it.
Answer: C
Explanation:
Explanation
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_blueg
NEW QUESTION # 26
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?
- A. Use Cloud Build with a trigger configured for each source code commit.
- B. Use Jenkins deployed via the Google Cloud Platform Marketplace, configured to watch for source code commits.
- C. 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.
- D. Use a Compute Engine virtual machine instance with an open source continuous integration tool, configured to watch for source code commits.
Answer: A
Explanation:
https://cloud.google.com/build/docs/automating-builds/create-manage-triggers#:~:text=A%20Cloud%20Build%20trigger%20automatically,changes%20that%20match%20certain%20criteria.
NEW QUESTION # 27
Technician Tommy is replacing a logic board on a Mac mini. Which of the following should he hold when handling the logic board?
- A. The heat sinks
- B. The connectors
- C. The edges of the logic board
- D. Any components
Answer: C
Explanation:
Explanation/Reference: https://www.ifixit.com/Guide/Mac+mini+Late+2014+Logic+Board+Replacement/33077
NEW QUESTION # 28
You are load testing your server application. During the first 30 seconds, you observe that a previously inactive Cloud Storage bucket is now servicing 2000 write requests per second and 7500 read requests per second.
Your application is now receiving intermittent 5xx and 429 HTTP responses from the Cloud Storage JSON API as the demand escalates. You want to decrease the failed responses from the Cloud Storage API.
What should you do?
- A. Limit the upload rate from your application clients so that the dormant bucket's peak request rate is reached more gradually.
- B. Use the XML API instead of the JSON API for interfacing with Cloud Storage.
- C. Pass the HTTP response codes back to clients that are invoking the uploads from your application.
- D. Distribute the uploads across a large number of individual storage buckets.
Answer: D
Explanation:
Reference:
https://cloud.google.com/storage/docs/request-rate
NEW QUESTION # 29
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. 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. - B. 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. - C. 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. - 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.
Answer: D
Explanation:
4. Deploy the new container on Cloud Run as a pipeline step.
NEW QUESTION # 30
You want to create "fully baked" or "golden" Compute Engine images for your application. You need to bootstrap your application to connect to the appropriate database according to the environment the application is running on (test, staging, production). What should you do?
- A. When creating the Compute Engine instance, add a tag with the name of the database to be connected. In your application, query the Compute Engine API to pull the tags for the current instance, and use the tag to construct the appropriate database connection string.
- B. Embed the appropriate database connection string in the image. Create a different image for each environment.
- C. When creating the Compute Engine instance, create a metadata item with a key of "DATABASE" and a value for the appropriate database connection string. In your application, read the "DATABASE" environment variable, and use the value to connect to the appropriate database.
- D. When creating the Compute Engine instance, create a metadata item with a key of "DATABASE" and a value for the appropriate database connection string. In your application, query the metadata server for the "DATABASE" value, and use the value to connect to the appropriate database.
Answer: C
NEW QUESTION # 31
You work for an organization that manages an ecommerce site. Your application is deployed behind a global HTTP(S) load balancer. You need to test a new product recommendation algorithm. You plan to use A/B testing to determine the new algorithm's effect on sales in a randomized way. How should you test this feature?
- A. Use HTTP header-based routing.
- B. Enable the new recommendation feature flag on a single instance.
- C. Mirror traffic to the new version of your application.
- D. Split traffic between versions using weights.
Answer: D
Explanation:
Explanation
https://cloud.google.com/load-balancing/docs/https/traffic-management-global#traffic_actions_weight-based_tra Deploying a new version of an existing production service generally incurs some risk. Even if your tests pass in staging, you probably don't want to subject 100% of your users to the new version immediately. With traffic management, you can define percentage-based traffic splits across multiple backend services.
For example, you can send 95% of the traffic to the previous version of your service and 5% to the new version of your service. After you've validated that the new production version works as expected, you can gradually shift the percentages until 100% of the traffic reaches the new version of your service. Traffic splitting is typically used for deploying new versions, A/B testing, service migration, and similar processes.
https://cloud.google.com/traffic-director/docs/advanced-traffic-management#weight-based_traffic_splitting_for_
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#split_the_traffic_
https://cloud.google.com/load-balancing/docs/https/traffic-management-global#traffic_actions_weight-based_tra
NEW QUESTION # 32
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 service Multiple Compute Engine machines, each running an instance of the audit service Pub/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?
- A. Create one Pub/Sub topic. Create one pull subscription to allow the audit services to share the messages.
- B. Create one Pub/Sub topic. Create one pull subscription per audit service instance to allow the services to share the messages.
- C. Create one Pub/Sub topic. Create one push subscription with the endpoint pointing to a load balancer in front of the audit services.
- D. Create one Pub/Sub topic per authentication service. Create one pull subscription per topic to be used by one audit service.
- E. Create one Pub/Sub topic per authentication service. Create one push subscription per topic, with the endpoint pointing to one audit service.
Answer: D
NEW QUESTION # 33
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?
- A. Build the application in C# with Firestore as the database. Deploy the application to App Engine flexible environment.
- B. Build the application in Python with Firestore as the database. Deploy the application to a Compute Engine managed instance group with autoscaling.
- C. Build the application in Python with Firestore as the database. Deploy the application to Cloud Run.
- D. Build the application in Python with CloudSQL as the database. Deploy the application to App Engine standard environment.
Answer: D
NEW QUESTION # 34
Your company wants to expand their users outside the United States for their popular application. The company wants to ensure 99.999% availability of the database for their application and also wants to minimize the read latency for their users across the globe.
Which two actions should they take? (Choose two.)
- A. Create a minimum of two Cloud Spanner instances in separate regions with at least one node.
- B. Create a cluster with at least 3 Spanner nodes.
- C. Create a Cloud Dataflow pipeline to replicate data across different databases.
- D. Create a multi-regional Cloud Spanner instance with "nam3" configuration.
- E. Create a cluster with at least 1 Spanner node.
- F. Create a multi-regional Cloud Spanner instance with "nam-asia-eur1" configuration.
Answer: C,D
NEW QUESTION # 35
Your website is deployed on Compute Engine. Your marketing team wants to test conversion rates between 3 different website designs.
Which approach should you use?
- A. Deploy the website on Cloud Functions and use traffic splitting.
- B. Deploy the website on Cloud Functions as three separate functions.
- C. Deploy the website on App Engine as three separate services.
- D. Deploy the website on App Engine and use traffic splitting.
Answer: D
NEW QUESTION # 36
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?
- A. Use Cloud Shell and the built-in code editor for development. Send your source code updates as pull requests.
- B. Use a text editor and the Git command line to send your source code updates as pull requests from a public computer.
- C. 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.
- D. 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.
Answer: A
Explanation:
Explanation
https://cloud.google.com/shell/docs
NEW QUESTION # 37
This architectural diagram depicts a system that streams data from thousands of devices. You want to ingest data into a pipeline, store the data, and analyze the data using SQL statements. Which Google Cloud services should you use for steps 1, 2, 3, and 4?
- A. 1) Dataflow
2) Pub/Sub
3) Firestore
4) BigQuery - B. 1) Pub/Sub
2) Dataflow
3) BigQuery
4) Firestore - C. 1) Pub/Sub
2) Dataflow
3) Firestore
4) BigQuery - D. 1) App Engine
2) Pub/Sub
3) BigQuery
4) Firestore
Answer: C
NEW QUESTION # 38
You recently migrated a monolithic application to Google Cloud by breaking it down into microservices. One of the microservices is deployed using Cloud Functions. As you modernize the application, you make a change to the API of the service that is backward-incompatible. You need to support both existing callers who use the original API and new callers who use the new API. What should you do?
- A. Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API. Use Cloud Endpoints to provide an API gateway that exposes a versioned API.
- B. Leave the original Cloud Function as-is and deploy a second Cloud Function that includes only the changed API. Calls are automatically routed to the correct function.
- C. Re-deploy the Cloud Function after making code changes to support the new API. Requests for both versions of the API are fulfilled based on a version identifier included in the call.
- D. Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API. Use a load balancer to distribute calls between the versions.
Answer: C
Explanation:
Reference: https://cloud.google.com/endpoints/docs/openapi/versioning-an-api
NEW QUESTION # 39
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?
- A. Set up a backend with Compute Engine web server instances with a private IP address behind a TCP proxy load balancer.
- B. 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.
- C. 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.
- D. 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.
Answer: C
Explanation:
Reference: https://cloud.google.com/compute/docs/instances/connecting-advanced#cloud_iap
https://cloud.google.com/solutions/connecting-securely#storing_host_keys_by_enabling_guest_attributes
NEW QUESTION # 40
You manage a microservices application on Google Kubernetes Engine (GKE) using Istio. You secure the communication channels between your microservices by implementing an Istio AuthorizationPolicy, a Kubernetes NetworkPolicy, and mTLS on your GKE cluster. You discover that HTTP requests between two Pods to specific URLs fail, while other requests to other URLs succeed. What is the cause of the connection issue?
- A. The Authorization Policy of your cluster is blocking HTTP requests for specific paths within your application.
- B. The Pod initiating the HTTP requests is attempting to connect to the target Pod via an incorrect TCP port.
- C. The cluster has mTLS configured in permissive mode, but the Pod's sidecar proxy is sending unencrypted traffic in plain text.
- D. A Kubernetes NetworkPolicy resource is blocking HTTP traffic between the Pods.
Answer: A
NEW QUESTION # 41
You are configuring a continuous integration pipeline using Cloud Build to automate the deployment of new container images to Google Kubernetes Engine (GKE). The pipeline builds the application from its source code, runs unit and integration tests in separate steps, and pushes the container to Container Registry. The application runs on a Python web server.
The Dockerfile is as follows:
FROM python:3.7-alpine -
COPY . /app -
WORKDIR /app -
RUN pip install -r requirements.txt
CMD [ "gunicorn", "-w 4", "main:app" ]
You notice that Cloud Build runs are taking longer than expected to complete. You want to decrease the build time. What should you do? (Choose two.)
- A. Cache the Docker image for subsequent builds using the -- cache-from argument in your build config file.
- B. Change the base image in the Dockerfile to ubuntu:latest, and install Python 3.7 using a package manager utility.
- C. Store application source code on Cloud Storage, and configure the pipeline to use gsutil to download the source code.
- D. Deploy a Container Registry on a Compute Engine VM in a VPC, and use it to store the final images.
- E. Select a virtual machine (VM) size with higher CPU for Cloud Build runs.
Answer: A,E
Explanation:
Explanation
https://cloud.google.com/build/docs/optimize-builds/increase-vcpu-for-builds By default, Cloud Build runs your builds on a standard virtual machine (VM). In addition to the standard VM, Cloud Build provides several high-CPU VM types to run builds. To increase the speed of your build, select a machine with a higher vCPU to run builds. Keep in mind that although selecting a high vCPU machine increases your build speed, it may also increase the startup time of your build as Cloud Build only starts non-standard machines on demand.
https://cloud.google.com/build/docs/optimize-builds/speeding-up-builds#using_a_cached_docker_image The easiest way to increase the speed of your Docker image build is by specifying a cached image that can be used for subsequent builds. You can specify the cached image by adding the --cache-from argument in your build config file, which will instruct Docker to build using that image as a cache source.
NEW QUESTION # 42
You are creating a Google Kubernetes Engine (GKE) cluster and run this command:
The command fails with the error:
You want to resolve the issue. What should you do?
- A. Request additional GKE quota in the GCP Console.
- B. Open a support case to request additional GKE quota.
- C. Request additional Compute Engine quota in the GCP Console.
- D. Decouple services in the cluster, and rewrite new clusters to function with fewer cores.
Answer: A
NEW QUESTION # 43
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