Professional Cloud Developer Certification Training Course

Professional Cloud Developer training is a specialized course focused on teaching developers how to design, build, and deploy applications on the Google Cloud Platform (GCP). Covering cloud-native application development, security best practices, and performance optimization, this training equips participants with hands-on skills to utilize GCP tools effectively and prepares them for the Google Professional Cloud Developer certification.

1.1 Designing high-performing applications and APIs. Considerations include:

• Microservices architecture
• 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)
• User session management
• Caching solutions
• HTTP REST versus gRPC (Google Remote Procedure Call)
• Incorporating Service Control capabilities offered by API services (e.g. Apigee)
• Loosely coupled asynchronous applications (e.g., Apache Kafka, Pub/Sub, Eventarc)
• Instrumenting code to produce metrics, logs, and traces
• Cost optimization and resource optimization
• Graceful handling of errors, disasters, and scaling events

1.2 Designing secure applications. Considerations include:

• Implementing data lifecycle and residency for applicable regulatory requirements
• Security mechanisms that identify vulnerabilities and protect services and resources (e.g., Identity-Aware Proxy [IAP], Web Security Scanner)
• Security mechanisms that secure/scan application binaries, dependencies, and manifests (e.g., Container Analysis)
• Storing, accessing, and rotating application secrets and encryption keys (e.g., Secret Manager, Cloud Key Management Service)
• Authenticating to Google Cloud services (e.g., application default credentials, JSON Web Token [JWT], OAuth 2.0)
• End-user account management and authentication by using Identity Platform
• Identity and Access Management (IAM) roles for users, groups, and service accounts
• Securing service-to-service communications (e.g., service mesh, Kubernetes Network Policies, Kubernetes namespaces)
• Running services with keyless and least privileged access (e.g., Workload Identity, Workload identity federation)
• Certificate-based authentication (e.g., SSL, mTLS)
• Supply-chain Levels for Software Artifacts (SLSA)

1.3 Choosing storage options for application data. Considerations include:

• Time-limited access to objects
• Data retention requirements
• Structured versus unstructured data (e.g., SQL versus NoSQL)
• Strong versus eventual consistency
• Data volume
• Data access patterns
• Online transaction processing (OLTP) versus data warehousing

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