A Google Professional Cloud Developer certification is a credential that validates an individual’s expertise in designing, building, and deploying applications on the Google Cloud Platform (GCP). The certification is intended for developers who have experience with GCP and are able to use GCP services and tools to build scalable and highly available applications. The exam covers a variety of topics related to GCP, including cloud computing fundamentals, GCP services, application development on GCP, integration, and security, and best practices for GCP development.
- Becoming certified as a Google Professional Cloud Developer can provide several benefits, such as:
- Recognition of your skills and expertise in GCP application development
- Career advancement opportunities
- Increased earning potential
- Enhanced credibility with customers and employers
- Access to exclusive Google Cloud events and resources
Key Skills: Google Professional Cloud Developer
The Google Professional Cloud Developer certification covers a wide range of skills and knowledge related to designing, building, and deploying applications on Google Cloud Platform (GCP). Some key skills that are covered in the certification include:
- Cloud Computing Fundamentals: Understanding the basics of cloud computing and its benefits, as well as the different cloud deployment models and cloud service models.
- Google Cloud Platform (GCP) Services: Understanding the different GCP services and how to use them to build scalable and highly available applications. This includes computing services, storage services, database services, and networking services.
- Developing Applications on GCP: Creating and deploying applications on GCP using tools like Google Cloud SDK, Cloud Console, and Cloud Shell. This also involves implementing authentication and authorization, using GCP services in applications, and monitoring and logging in GCP.
- Integration and Security: Integrating GCP services with external systems and managing and securing data on GCP. This includes implementing security controls and compliance.
- Best Practices for GCP Development: Developing applications that are scalable, reliable, and cost-effective. This includes designing for high availability and disaster recovery, as well as developing for cost optimization.
Target Audience: Google Professional Cloud Developer Exam
The Google Professional Cloud Developer certification is intended for developers who have experience with Google Cloud Platform (GCP) and are able to use GCP services and tools to design, build, and deploy applications on the platform. Specifically, this certification is recommended for:
- Software Developers: Developers who are responsible for designing and building applications on GCP.
- Cloud Architects: Cloud architects who are responsible for designing and implementing GCP solutions for their organization.
- Solutions Engineers: Solutions engineers who are responsible for deploying and managing GCP solutions for their organization.
- DevOps Engineers: DevOps engineers who are responsible for automating the deployment and management of GCP applications and infrastructure.
To be successful in the Google Professional Cloud Developer exam, candidates should have at least 3 years of experience in software development and at least 1 year of experience developing applications on GCP. They should also have a strong understanding of cloud computing fundamentals, GCP services, application development on GCP, integration and security, and best practices for GCP development.
Study Guide: Google Cloud Professional Cloud Developer
As you commence your preparation for Google Professional Cloud Developer certification exam, there are some common-yet-powerful methods that are beneficial in your preparation. Learning from authentic and genuine resources that best suit your preparations is a must. We are providing a step by step guide to qualify the exam with flying colours.
Review All Exam Objectives
One must clearly understand what they are getting into before starting any quest. The most crucial aspect of your preparation, then, involves going over each and every exam goal. So, to get the test guide, be sure to go to the Google Cloud official website. You’ll be able to comprehend each and every topic in our test guide in great depth. This will assist you in thoroughly preparing each domain in line with the test. This test covers 5-course domains, including:
Topic 1: Designing highly scalable, available, and reliable cloud-native applications (33%)
1.1 Designing high-performing applications and APIs. Considerations include:
- Microservices (Google Documentation: Microservices Architecture on Google App Engine, Migrating a monolithic application to microservices on Google Kubernetes Engine)
- Choosing the appropriate platform based on the use case and requirements (e.g., IaaS [infrastructure as a service], CaaS [container as a service], PaaS [platform as a service], FaaS [function as a service])
- Application modernization (e.g., containerization)
- Understanding how Google Cloud services are geographically distributed (e.g., latency, regional services, zonal services) (Google Documentation: Geography and regions, Regions and Zones)
- User session management (Google Documentation: Handling sessions with Firestore, Managing sessions with external identities
- Caching solutions (Google Documentation: Memorystore)
- HTTP REST versus gRPC (Google Remote Procedure Call) (Google Documentation: gRPC vs REST)
- Incorporating Service Control capabilities offered by API services (e.g. Apigee) (Google Documentation: What is Apigee?)
- Loosely coupled asynchronous applications (e.g., Apache Kafka, Pub/Sub, Eventarc) (Google Documentation: Connect Pub/Sub to Apache Kafka, Eventarc)
- Instrumenting code to produce metrics, logs, and traces (Google Documentation: Instrument for Cloud Trace)
- Cost optimization and resource optimization
- Graceful handling of errors, disasters, and scaling events (Google Documentation: Data deletion on Google Cloud)
1.2 Designing secure applications. Considerations include:
- Implementing data lifecycle and residency requirements for applicable regulations
- Security mechanisms that protect services and resources (Google Documentation: Google Infrastructure Security Design Overview)
- Security mechanisms that identify vulnerabilities and protect services and resources (e.g., Identity Aware Proxy [IAP], Web Security Scanner) (Google Documentation: Setting up custom scans using Web Security Scanner)
- Security mechanisms that secure/scan application binaries, dependencies, and manifests (e.g., Container Analysis) (Google Documentation: Container scanning overview)
- Storing, accessing, and rotating application secrets and encryption keys (e.g., Secret Manager, Cloud Key Management Service) (Google Documentation: Enable customer-managed encryption keys for Secret Manager)
- Authenticating to Google Cloud services (e.g., application default credentials, JSON Web Token [JWT], OAuth 2.0) (Google Documentation: Authentication methods at Google)
- End-user account management and authentication using Identity Platform
- Identity and Access Management (IAM) roles for users, groups, and service accounts (Google Documentation: IAM Overview)
- Securing service-to-service communications (e.g., service mesh, Kubernetes Network Policies, and Kubernetes namespaces) (Google Documentation: Kubernetes best practices: Organizing with Namespaces)
- Running services with keyless and least privileged access (e.g., Workload Identity, Workload identity federation) (Google Documentation: Workload Identity)
- Certificate-based authentication (e.g., SSL, mTLS) (Google Documentation: SSL certificates overview, Mutual TLS authentication)
- Supply-chain Levels for Software Artifacts (SLSA)
1.3 Choosing storage options for application data. Considerations include:
- Time-limited access to objects (Google Documentation: Overview of access control)
- Data retention requirements (Google Documentation: Retention policies and retention policy locks)
- Structured versus unstructured data (e.g., SQL versus NoSQL)
- Strong versus eventual consistency (Google Documentation: Balancing Strong and Eventual Consistency with Datastore)
- Data volume (Google Documentation: Storage options)
- Data access patterns
- Online transaction processing (OLTP) versus data warehousing
Topic 2: Building and testing applications (26%)
2.1 Setting up your local development environment. Considerations include:
- Emulating Google Cloud services for local application development (Google Documentation: Using the Local Development Server)
- Using the Google Cloud console, Google Cloud SDK, Cloud Shell, and Cloud Workstations
- Using developer tooling (e.g., common IDEs, Cloud Code, Skaffold) (Google Documentation: Kubernetes development, simplified—Skaffold is now GA)
- Authenticating to Google Cloud services (e.g., Cloud SQL Auth proxy, AlloyDB Auth proxy)
2.2 Building. Considerations include:
- Source control management (Google Documentation: Cloud Source Repositories
- Creating secure container images from code (Google Documentation: Building Containers, Quickstart for Container Registry)
- Developing a continuous integration pipeline using services (e.g., Cloud Build, Artifact Registry) that construct deployment artifacts (Google Documentation: CI/CD on Google Cloud, Quickstart for Container Registry, Cloud Build)
- Code and test build optimization
2.3 Testing. Considerations include:
- Unit testing (Google Documentation: Local Unit Testing for Python 2, Testing Overview)
- Integration testing including the use of emulators
- Performance testing (Google Documentation: Testing Overview, Distributed load testing using Google Kubernetes Engine)
- Load testing (Google Documentation: Distributed load testing using Google Kubernetes Engine)
- Failure testing/chaos engineering
Topic 3: Deploying applications (19%)
3.1 Adopting appropriate feature rollout strategies. Considerations include:
- A/B testing (Google Documentation: Monitor and analyze A/B experiments)
- Feature flags
- Backward compatibility (Google Documentation: Compatibility)
- Versioning APIs (e.g., Apigee) (Google Documentation: What is Apigee API hub?)
3.2 Deploying applications to a serverless computing environment. Considerations include:
- Deploying applications from source code (Google Documentation: Deploy from source code)
- Using triggers to invoke functions (Google Documentation: Cloud Functions triggers)
- Configuring event receivers (e.g., Eventarc, Pub/Sub) (Google Documentation: Receive events using Pub/Sub messages (gcloud CLI))
- Exposing and securing application APIs (e.g., Apigee) (Google Documentation: Overview of Advanced API Security)
3.3 Deploying applications and services to Google Kubernetes Engine (GKE). Considerations include:
- Deploying a containerized application to GKE (Google Documentation: Deploying a containerized web application)
- Integrating Kubernetes role-based access control (RBAC) with IAM
- Defining workload specifications (e.g., resource requirements) (Google Documentation: Workload Identity)
- Building a container image using Cloud Build (Google Documentation: Building container images)
Topic 4: Integrating an application with Google Cloud services (22%)
4.1 Integrating an application with data and storage services. Considerations include:
- Managing connections to data stores (e.g., Cloud SQL, Cloud Spanner, Firestore, Bigtable, Cloud Storage)
- Reading/writing data to or from various datastores
- Writing an application that publishes/consumes data asynchronously (e.g., from Pub/Sub or streaming data sources) (Google Documentation: Writing and Responding to Pub/Sub Messages, Pub/Sub)
- Orchestrate application services with Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler
4.2 Integrating an application with Google Cloud APIs. Considerations include:
- Enabling Google Cloud services
- Making API calls using supported options (e.g., Cloud Client Library, REST API or gRPC, APIs Explorer) taking into consideration:
- Batching requests (Google Documentation: Batching requests)
- Restricting return data (Google Documentation: Working with Quotas, Usage limits)
- Paginating results (Google Documentation: Paging through table data, Paginating data with query cursors)
- Caching results (Google Documentation: Using cached query results)
- Error handling (e.g., exponential backoff) (Google Documentation: Truncated exponential backoff)
- Using service accounts to make Cloud API calls (Google Documentation: Service accounts)
- Integrating with Google Cloud’s operations suite
Understand the exam terms and concepts
The Google Professional Cloud Developer certification exam covers a wide range of topics related to developing and deploying applications on the Google Cloud Platform (GCP). Some of the key concepts and terminology you should be familiar with include:
- Google Cloud Platform (GCP): A collection of cloud computing services provided by Google, including compute, storage, databases, machine learning, and more.
- Cloud Computing: The delivery of computing services over the internet, including servers, storage, databases, networking, software, analytics, and more.
- Cloud Deployment Manager: A tool that helps you automate the deployment and management of GCP resources, including virtual machines, storage, and networking.
- App Engine: A fully managed platform for building and deploying web and mobile applications on GCP.
- Cloud Functions: A serverless compute service that lets you run your code in response to events and automatically manages the underlying infrastructure.
- Kubernetes Engine: A managed environment for deploying containerized applications using Kubernetes.
- Compute Engine: A virtual machine that runs on Google’s infrastructure.
- Cloud SQL: A fully managed database service that makes it easy to set up, maintain, manage, and administer relational databases on GCP.
- BigQuery: A fully managed, serverless data warehouse that lets you store, query, and analyze large datasets using SQL.
- Pub/Sub: A messaging service that allows you to send and receive messages between independent applications.
- Cloud Storage: A scalable and durable object storage service that lets you store and retrieve data from anywhere in the world.
- Identity and Access Management (IAM): A service that enables you to manage access control for your GCP resources.
- Cloud Build: A continuous integration/continuous delivery (CI/CD) platform that automates the building, testing, and deployment of your applications on GCP.
- Cloud SDK: A command-line tool that provides access to GCP services and resources.
- Stackdriver: A suite of monitoring, logging, and diagnostics tools that gives you visibility into your GCP infrastructure and applications.
Google Professional Cloud Developer Training
Some may find training not as important as books. But, let us remind you that GCP Training is the best training offered to candidates. With the help of training, you’ll able to conduct online on-demand classes without any hassle. Training Offered- ‘Developing Applications with Google Cloud Platform’
- Firstly, Best Practices for Application Development
- Secondly, Google Cloud Client Libraries, Google Firebase SDK and Google Cloud SDK
- Thirdly, Overview of Data Storage Options
- Then, Best Practices for Using Google Cloud Datastore
- Further, Performing Operations on Buckets and Objects
- Additionally, Best Practices for Using Google Cloud Storage
- Moreover, Handling Authentication and Authorization
- Also, Using Google Cloud Pub/Sub to Integrate Components of the Application
- Then, Adding Intelligence to Your Application
- Furthermore, Using Google Cloud Functions for Event-Driven Processing
- Subsequently, Managing APIs with Google Cloud Endpoints
- Not to mention, Deploying an Application with the help of Google Cloud Cloud Build, Google Cloud Container Registry, and Google Cloud Deployment Manager
- Then, Execution Environments for Your Application
- Also, Debugging, Tracking, and Tuning Performance with the help of Google Stackdriver
Practical experience with Hands-on labs
The next and most important stage is getting hands-on experience. The GCP Cloud Developer exam’s scenario-based questions call for prior practical experience. You may sign up for the GCP free tier as part of the GCP goods, services, and technologies free trial. The USD 300 in free credit can also be used to get practical experience. One can even sign up for paid hands-on training to gain deeper knowledge.
Self-Evaluation through Practice Tests
And, finally, it’s time for self-evaluation. Take it from us, Self Evaluation is most important step in your preparations. The more you’re going to practice, it’s better for you. Not only does it assists you in understanding the areas where you lack but also, ensures you’re improving your skills as well. So, keep on practicing as many tests as possible to boost your confidence. Lets Start Practising with Google Cloud Professional Cloud Developer Practice Exam to keep ahead
