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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

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

Designing secure applications

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

Managing application data

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

Refactoring applications to migrate to Google Cloud

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

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

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

Testing

• Load testing
• Performance testing
• Integration testing

Building

• Reviewing and improving continuous integration pipeline efficacy
• Creating a Cloud Source Repository and committing code to it
• Creating container images from code
• 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:

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

Deploying applications and services on Compute Engine

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

Deploying applications and services to Google Kubernetes Engine (GKE)

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

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

• 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

• Read/write data to/from various databases (e.g., SQL, JDBC)
• Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
• Writing an application that publishes/consumes data asynchronously (e.g., from Cloud Pub/Sub)
• 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

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

Integrating Google Cloud APIs with applications

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

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

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

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

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

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Aside from the mentioned training options, Google also provides a series of programs that will allow you to demonstrate competence in the following areas:

• Building and Managing APIs with Apigee
• Deploying to Kubernetes in Google Cloud
• Serverless Cloud Run Development
• Serverless Firebase Development

Through all the above-mentioned courses, exam-takers will obtain fundamental information relating to Cloud Shell, Cloud IAM, Container Registry, Spring Boot, App Engine, Firebase SDK, and many other tools and products. It should be mentioned that these courses have a total of 64 labs that will be helpful in validating your skills to manage the Google cloud environment in real-world scenarios.

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

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How to Prepare For Google Professional Cloud Developer Exam

Preparation Guide for Google Professional Cloud Developer Exam

Introduction

Google has designed different Role Based Certifications for the IT professionals to validate their skillset one among them is Google Professional Cloud Developer. This program gives Google cloud professionals a way to demonstrate their skills. The evaluation relies on a meticulous exam using industry standard methodology to validate aspirants proficiency standards to meet Google's proficiency standards.

According to Google, a Google Certified Professional Cloud Developer facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud developer and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

In this guide, we will cover the Google Professional Cloud Developer Exam, Google Professional Cloud Developer Certified Professionals salary and all aspects of the Google Professional Cloud Developer Certification.

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