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How to book Google Professional Cloud Developer Exams

The registration for the Google Professional Cloud Developer Exam follows the steps given below.

• Step 1: Visit the Google Cloud Webassessor Website
• Step 2: Sign in or sign up to your Google Cloud Webassessor account
• Step 3: Search for the exam name Google Professional Cloud Developer
• Step 4: Take the date of the exam, choose exam center and make further payment using payment method like credit/debit etc.

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

Designing secure applications

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

Managing application data

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

Refactoring applications to migrate to Google Cloud

• Using managed services
• Google-recommended practices and documentation
• 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

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

Testing

• Load testing
• Integration testing
• Performance testing

Building

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

3 Deploying applications

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

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

Deploying applications and services on Compute Engine

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

Deploying applications and services to Google Kubernetes Engine (GKE)

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

Deploying a Cloud Function

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

Using service accounts

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

4 Integrating Google Cloud Platform Services

Integrating an application with data and storage services

• Writing an application that publishes/consumes data asynchronously (e.g., from Cloud Pub/Sub)
• 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)

Integrating an application with compute services

• Authenticating users by using OAuth2.0 Web Flow and Identity Aware Proxy
• 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

Integrating Google Cloud APIs with applications

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

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

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

Managing Google Kubernetes Engine workloads

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

Troubleshooting application performance

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

Deploying Apps

• 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.
• 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 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.
• 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.

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

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