Google Professional-Cloud-Developer Q&A - in .pdf

  • Professional-Cloud-Developer pdf
  • Exam Code: Professional-Cloud-Developer
  • Exam Name: Google Certified Professional - Cloud Developer
  • Updated: Sep 03, 2025
  • Q & A: 265 Questions and Answers
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  • Exam Code: Professional-Cloud-Developer
  • Exam Name: Google Certified Professional - Cloud Developer
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  • Updated: Sep 03, 2025
  • Q & A: 265 Questions and Answers
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  • Exam Code: Professional-Cloud-Developer
  • Exam Name: Google Certified Professional - Cloud Developer
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  • Q & A: 265 Questions and Answers
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Deploying Apps

  • Deploy Cloud Functions: The next objective requires having the skills in securing Cloud functions, Cloud functions invoked through HTTP, and Cloud functions triggered through events from Google Cloud services.
  • Deploy Applications & Services to GKE: This subtopic includes the evaluation of one’s skills in deploying containerized applications to GCE, configuring Google Cloud IAM and Kubernetes RBAC relationships, identifying workload specifications, and configuring the Kubernetes namespaces, among others.
  • Use a Service Account: This one covers the students’ skills in downloading and utilizing service account private key files as well as constructing service accounts based on the ethics of least privilege.
  • Recommend the Relevant Deployment Strategies with the Relevant Tools for a Target Compute Environment: The consideration for this section includes traffic-splitting deployments, canary deployments, rolling deployments, and green/blue deployments.
  • Deploy Applications & Services on the Compute Engine: This area covers bootstrapping of applications, management of service accounts for virtual machines, management of the Compute Engine virtual machine binaries and images, and exporting of application metrics and logs.

Topics of Google Professional Cloud Developer Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our Google Professional Cloud Developer Dumps will include the following topics:

1. Designing highly scalable, available, and reliable cloud-native applications

Designing high-performing applications and APIs

  • Graceful shutdown on platform termination
  • Scaling velocity characteristics/tradeoffs of IaaS (infrastructure as a service) vs. CaaS (container as a service) vs. PaaS (platform as a service)
  • Deploying and securing API services
  • Defining a key structure for high-write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL
  • User session management
  • Loosely coupled applications using asynchronous Cloud Pub/Sub events
  • Google-recommended practices and documentation
  • Evaluating different services and technologies
  • Geographic distribution of Google Cloud services (e.g., latency, regional services, zonal services)
  • Microservices
  • Caching solutions

Designing secure applications

  • Securing service-to-service communications (e.g., service mesh, Kubernetes network policies, and Kubernetes namespaces)
  • Security mechanisms that secure/scan application binaries and manifests
  • Security mechanisms that protect services and resources
  • Certificate-based authentication (e.g., SSL, mTLS)
  • IAM roles for users/groups/service accounts
  • Set compute/workload identity to least privileged access
  • Google-recommended practices and documentation
  • Implementing requirements that are relevant for applicable regulations (e.g., data wipeout)
  • Storing and rotating application secrets using Cloud KMS
  • Authenticating to Google services (e.g., application default credentials, JWT, OAuth 2.0)

Managing application data

  • Strong vs. eventual consistency
  • Structured vs. unstructured data
  • Choosing data storage options based on use case considerations, such as:
  • Following Google-recommended practices and documentation
  • Frequency of data access in Cloud Storage
  • Defining database schemas for Google-managed databases (e.g., Cloud Firestore, Cloud Spanner, Cloud Bigtable, Cloud SQL)
  • Cloud Storage-signed URLs for user-uploaded content
  • Data volume

Refactoring applications to migrate to Google Cloud

  • Google-recommended practices and documentation
  • Using managed services
  • Migrating a monolith to microservices

2 Building and Testing Applications

Setting up your local development environment

  • Creating Google Cloud projects
  • Emulating Google Cloud services for local application development

Writing code

  • Unit testing
  • Efficiency
  • Algorithm design
  • Modern application patterns
  • Agile software development

Testing

  • Load testing
  • Integration testing
  • Performance testing

Building

  • Creating a Cloud Source Repository and committing code to it
  • Reviewing and improving continuous integration pipeline efficacy
  • Developing a continuous integration pipeline using services (e.g., Cloud Build, Container Registry) that construct deployment artifacts
  • Creating container images from code

3 Deploying applications

Recommend appropriate deployment strategies for the target compute environment (Compute Engine, Google Kubernetes Engine). Strategies include:

  • Canary deployments
  • Traffic-splitting deployments
  • Blue/green deployments
  • Rolling deployments

Deploying applications and services on Compute Engine

  • Modifying the VM service account
  • Manually updating dependencies on a VM
  • Managing Compute Engine VM images and binaries
  • Exporting application logs and metrics
  • Installing an application into a VM

Deploying applications and services to Google Kubernetes Engine (GKE)

  • Managing container lifecycle
  • Managing Kubernetes RBAC and Google Cloud IAM relationship
  • Define deployments, services, and pod configurations
  • Configuring application accessibility to user traffic and other services
  • Configuring Kubernetes namespaces and access control
  • Defining workload specifications (e.g., resource requirements)
  • Building a container image using Cloud Build
  • Deploying a containerized application to GKE

Deploying a Cloud Function

  • Cloud Functions that are triggered via an event (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)
  • Cloud Functions that are invoked via HTTP
  • Securing Cloud Functions

Using service accounts

  • Downloading and using a service account private key file
  • Creating a service account according to the principle of least privilege

4 Integrating Google Cloud Platform Services

Integrating an application with data and storage services

  • Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
  • Read/write data to/from various databases (e.g., SQL, JDBC)
  • Storing and retrieving objects from Cloud Storage
  • Connecting to a data store (e.g., Cloud SQL, Cloud Spanner, Cloud Firestore, Cloud Bigtable)
  • Writing an application that publishes/consumes data asynchronously (e.g., from Cloud Pub/Sub)

Integrating an application with compute services

  • Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
  • Reading instance metadata to obtain application configuration
  • Implementing service discovery in Google Kubernetes Engine and Compute Engine
  • Authenticating users by using OAuth2.0 Web Flow and Identity Aware Proxy

Integrating Google Cloud APIs with applications

  • Paginating results
  • Error handling (e.g., exponential backoff)
  • Restricting return data
  • Caching results
  • Making API calls with a Cloud Client Library, the REST API, or the APIs Explorer, taking into consideration:
  • Enabling a Google Cloud API
  • Using service accounts to make Google API calls
  • Batching requests

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

  • Debugging a custom VM image using the serial port
  • Inspecting resource utilization over time
  • Analyzing a failed Compute Engine VM startup
  • Analyzing logs
  • Sending logs from a VM to Cloud Monitoring
  • Viewing syslogs from a VM

Managing Google Kubernetes Engine workloads

  • Analyzing container lifecycle events (e.g., CrashLoopBackOff, ImagePullErr)
  • Configuring workload autoscaling
  • Configuring logging and monitoring
  • Analyzing logs
  • Using external metrics and corresponding alerts

Troubleshooting application performance

  • Graphing metrics
  • Exporting logs from Google Cloud
  • Creating a monitoring dashboard
  • Writing custom metrics and creating metrics from logs
  • Profiling performance of request-response
  • Profiling services
  • Viewing logs in the Google Cloud Console
  • Using Cloud Debugger
  • Using documentation, forums, and Google support
  • Reviewing application performance (e.g., Cloud Trace, Prometheus, OpenCensus)
  • Reviewing stack traces for error analysis
  • Monitoring and profiling a running application

This certification exam measures your ability to perform various tasks required for the successful functioning of different processes. The details of its topics are enumerated below:

Designing Highly Available, Reliable, and Scalable Cloud-Native Apps

  • Application Modernization: It covers the learners’ skills in using managed services, designing horizontally state-less scalable services, refactoring the monolith to micro-services, and understanding the Google-recommended practices and documentation.
  • Design Secure Applications: This topic covers the details, which include security mechanisms securing and protecting services and resources as well as app manifests & binaries. It also involves the skills in implementing the appropriate prerequisites for applicable applications. You should know about rotating & storing application keys & secrets, validating processes of the Google service, service-to-service communications, and IAM roles for groups/service/user accounts. The subtopic also covers your knowledge of how to run the services that have the least privileged access, data retention prerequisites, and certificate-based validation.
  • Manage Application Data: The considerations for this subdomain include data volume, structured versus unstructured data, strong versus eventual consistency, and data access frequency within Cloud Storage.
  • Design High Performing APIs and Applications: The considerations for this subject area include Microservices, scaling velocity tradeoffs/characteristics of IaaS vs. CaaS vs. PaaS, Geographic distribution of Google Cloud services, and user session management. It also covers the domains, such as caching solutions, securing & deploying API services, Google-recommended documentation & practices, and refined shutdown on the platform termination. The learners should also be able to explain the key structure of high-write apps with the use of Cloud Storage, Cloud SQL, Cloud Spanner, and Cloud Bigtable.

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Section 4: Integrating Google Cloud Services

The aim of this domain is to evaluate the learners based on their capacity to integrate an app with storage & data services, integrate an app with compute services, as well as integrate Cloud APIs with apps.

Reference: https://cloud.google.com/certification/cloud-developer

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