This course prepares experienced IT professionals to design and manage enterprise solutions on Google Cloud. Participants learn to translate business requirements into practical architecture decisions, select appropriate cloud services, and plan secure, reliable, scalable, and cost-effective solutions. The course covers infrastructure, application modernization, data platforms, AI integration, migration, and production operations. An integrated capstone brings these topics together through an enterprise architecture design.

The course scope follows the competencies covered by the Google Cloud Professional Cloud Architect certification.

Duration 6 Days – 42 hrs.

Objectives

• Translate business goals and technical constraints into cloud architecture requirements.
• Select suitable compute, networking, storage, and database services.
• Design secure and resilient solutions for enterprise workloads.
• Plan workload migration and application modernization.
• Incorporate data processing and AI capabilities into cloud solutions.
• Define infrastructure provisioning and application deployment approaches.
• Improve operational reliability, performance, and cloud expenditure.
• Produce an architecture proposal supported by clear design decisions.

 

Target Audience

• Cloud architects and solution architects.
• Cloud engineers and infrastructure engineers.
• Systems administrators and network engineers moving into architecture roles.
• DevOps engineers and site reliability engineers.
• Technical leads and enterprise application architects.
• IT professionals preparing for the Professional Cloud Architect certification.

 

Prerequisites

• Working knowledge of cloud computing and Google Cloud fundamentals.
• Familiarity with networking, operating systems, databases, and access management.
• Basic experience using the Google Cloud console and command-line tools.
• Understanding of application deployment, containers, and distributed systems.
• Experience supporting or designing IT infrastructure or applications.
• For certification preparation, Google recommends at least three years of industry experience, including at least one year designing and managing Google Cloud solutions; the certification has no mandatory prerequisites.

 

Course Outline

Day 1: Architecture Foundations and Business Requirements

Module 1: Google Cloud Architecture Foundations

• Regions, zones, and resource organization.
• Google Cloud Well-Architected Framework.
• Shared responsibility and enterprise governance.
• Architecture documentation and decision records.

 Module 2: Translating Requirements into Solution Designs

• Business goals, stakeholders, and success measures.
• Functional requirements and quality requirements.
• Capacity, availability, latency, and budget constraints.
• Service selection and architectural trade-offs.

 

Day 2: Networking and Compute Architecture

Module 3: Designing Enterprise Networks

• VPC networks, subnets, routing, and firewalls.
• Shared VPC and private service connectivity.
• Load balancing and traffic distribution.
• Hybrid connectivity and multicloud integration.

 Module 4: Selecting and Provisioning Compute Platforms

• Compute Engine and managed instance groups.
• Google Kubernetes Engine and container workloads.
• Cloud Run and event-driven computing.
• Autoscaling, resource sizing, and infrastructure as code.

  

Day 3: Storage, Data Platforms, and AI Integration

Module 5: Designing Storage and Database Solutions

• Object, file, relational, and nonrelational storage.
• Selecting databases according to application access patterns.
• Data lifecycle, retention, replication, and recovery.
• Data transfer and migration planning.

 Module 6: Architecting Data and AI Workloads

• Batch processing, streaming, and analytics architectures.
• Integrating managed AI services and Gemini models.
• Model selection, deployment, and application integration.
• AI infrastructure capacity, data protection, and cost considerations.

  

Day 4: Security, Reliability, and Recovery

Module 7: Enterprise Security and Compliance Design

• IAM, service identities, and least privilege.
• Organization policies and security boundaries.
• Encryption, key management, and secrets.
• Auditability, data residency, and AI security controls.

 Module 8: Building Resilient Cloud Solutions

• Availability targets and failure scenarios.
• Redundancy, failover, and graceful degradation.
• Recovery objectives and backup strategies.
• Disaster recovery and business continuity planning.

 

Day 5: Migration, Delivery, and Operational Optimization

Module 9: Migration and Implementation Planning

• Workload dependencies and migration sequencing.
• Rehosting, replatforming, and refactoring decisions.
• Deployment automation and release strategies.
• Cutover, rollback, and operational handover.

 Module 10: Managing and Optimizing Production Solutions

• Monitoring, logging, alerting, and troubleshooting.
• Service reliability indicators and objectives.
• Performance tuning and resource utilization.
• Cost governance, sustainability, and continuous improvement.

 

Day 6: Enterprise Architecture Integration and Capstone

Module 11: Architecture Decisions in Business Scenarios

• Interpreting enterprise requirements and constraints.
• Comparing alternative solution designs.
• Resolving competing business and technical priorities.
• Communicating recommendations to stakeholders.

 Module 12: Capstone—Enterprise Cloud Architecture Design

• Design a Google Cloud solution for an organization modernizing a customer-facing application.
• Produce an architecture diagram and service selection rationale.
• Define networking, access controls, data storage, and recovery arrangements.
• Incorporate analytics or an AI capability where it serves a business requirement.
• Develop a migration roadmap, deployment plan, and operational support approach.
• Document cost assumptions, design trade-offs, and future improvements.