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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

• Geographic distribution of Google Cloud services (e.g., latency, regional services, zonal services)
• 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)
• Caching solutions
• Google-recommended practices and documentation
• User session management
• Graceful shutdown on platform termination
• Defining a key structure for high-write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL
• Deploying and securing API services
• Microservices
• Loosely coupled applications using asynchronous Cloud Pub/Sub events

Designing secure applications

• 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
• Set compute/workload identity to least privileged access
• Security mechanisms that protect services and resources
• IAM roles for users/groups/service accounts
• Securing service-to-service communications (e.g., service mesh, Kubernetes network policies, and Kubernetes namespaces)
• Certificate-based authentication (e.g., SSL, mTLS)
• Authenticating to Google services (e.g., application default credentials, JWT, OAuth 2.0)
• Security mechanisms that secure/scan application binaries and manifests

Managing application data

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

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

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

Testing

• Integration testing
• Load testing
• Performance testing

Building

• Creating container images from code
• 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 a Cloud Source Repository and committing code to it

3 Deploying applications

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

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

Deploying applications and services on Compute Engine

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

Deploying applications and services to Google Kubernetes Engine (GKE)

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

Deploying a Cloud Function

• Securing Cloud Functions
• 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

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

• Storing and retrieving objects from Cloud Storage
• 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)
• Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools

Integrating an application with compute services

• 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
• Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools

Integrating Google Cloud APIs with applications

• Restricting return data
• Paginating results
• Batching requests
• Enabling a Google Cloud API
• 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
• Caching results
• Error handling (e.g., exponential backoff)

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

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

Managing Google Kubernetes Engine workloads

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

Troubleshooting application performance

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

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.

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

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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.