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

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

Designing secure applications

• Security mechanisms that protect services and resources
• Authenticating to Google services (e.g., application default credentials, JWT, OAuth 2.0)
• Security mechanisms that secure/scan application binaries and manifests
• Implementing requirements that are relevant for applicable regulations (e.g., data wipeout)
• Google-recommended practices and documentation
• Storing and rotating application secrets using Cloud KMS
• 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
• Certificate-based authentication (e.g., SSL, mTLS)

Managing application data

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

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

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

Testing

• Performance testing
• Integration testing
• Load testing

Building

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

3 Deploying applications

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

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

Deploying applications and services on Compute Engine

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

Deploying applications and services to Google Kubernetes Engine (GKE)

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

Deploying a Cloud Function

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

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

• Storing and retrieving objects from Cloud Storage
• 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)
• Read/write data to/from various databases (e.g., SQL, JDBC)
• 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
• Implementing service discovery in Google Kubernetes Engine and Compute Engine
• Reading instance metadata to obtain application configuration
• Authenticating users by using OAuth2.0 Web Flow and Identity Aware Proxy

Integrating Google Cloud APIs with applications

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

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

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

Managing Google Kubernetes Engine workloads

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

Troubleshooting application performance

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

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Revision Books

Let’s now focus on the details of the revision books that will supplement the above training programs well:

• Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern Applications in the Cloud (1st Edition)

  This book is perfectly designed to cover everything there’s to know about Kubernetes. It is a valuable study material that addresses vital details starting with what Kubernetes is, its origin, and what the future holds for this platform. You will build a high-level knowledge of containers including how they work, how to manage them, and most importantly, the tips for designing cloud-native infrastructure and similar services.

  This guide suits both experienced IT professionals and beginner-level individuals who are only getting started with Kubernetes. Through this resource, candidates will gain important hands-on skills related to the writing and deployment of Kubernetes apps, configuration and operation of Kubernetes clusters, and cloud infrastructure automation using popular tools such as Helm. What’s more, this book will also help you build fundamental knowledge of Kubernetes security, including Role Based Access Control (RBAC). When opting to study using this book, be sure to get the official resource that’s written by John Arundel alongside Justin Domingus.

• Building Secure & Reliable Systems: Best Practices for Designing, Implementing, and Maintaining Systems (1st Edition)

  The authors of this book (Heather Adkins, Piotr Lewandoski, Betsy Beyer, Ana Oprea, and others) created this comprehensive self-study tool with an aim to help candidates learn how to accommodate security and reliability solutions in the lifecycle of systems and software. This material gives explicit knowledge of highly secure systems through coding, debugging, and testing practices, design techniques, and strategies required to address security incidents. Check it out from Amazon and get easy access to one of the most valuable study resources you will ever find for the Google Professional Cloud Developer exam preparation.

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

Google Professional-Cloud-Developer Exam Syllabus Topics: