Cloud-Driven Enterprise Architecture
Class Duration
35 hours of live training delivered over 5 days.
Student Prerequisites
- Basic understanding of cloud computing concepts
- Experience with organizational IT environments
- Familiarity with software development lifecycle
- Understanding of enterprise systems and architectures
Target Audience
This course is designed for software engineers, technical leads, solution architects, and enterprise architects who need to understand how cloud computing fundamentally transforms enterprise architecture decisions. Ideal participants are professionals responsible for guiding technical strategy, designing scalable systems, or leading cloud transformation initiatives within their organizations.
Description
Cloud-Driven Enterprise Architecture provides comprehensive training on how cloud computing reshapes enterprise architecture thinking, decision-making, and implementation. Participants will learn to navigate the complex landscape of cloud service models, understand how different cloud deployment models impact architectural decisions, and develop skills to align cloud strategies with business objectives and enterprise architecture principles.
The course covers practical aspects of cloud adoption strategy including portfolio assessment, the modern 7 Rs framework for application migration, and building comprehensive cloud adoption roadmaps. Participants will gain deep understanding of security, compliance, and governance in cloud environments, including shared responsibility models and regulatory considerations across major compliance frameworks.
A significant focus is placed on cost governance through the comprehensive FinOps Framework with its updated Cloud+ approach, covering all four Domains and 22 Capabilities across multiple cost scopes. The course also addresses organizational transformation aspects, including building cloud centers of excellence, platform engineering teams, and managing cultural shifts toward DevOps practices.
Emerging trends including AI/ML platforms, edge computing, and sustainability considerations are explored through an enterprise architecture lens, ensuring participants are prepared for the future of cloud-driven enterprise systems.
Learning Outcomes
- Analyze how different cloud deployment models (public, private, hybrid, multi-cloud) impact enterprise architecture decisions and trade-offs
- Compare and contrast major cloud provider ecosystems (AWS, Azure, GCP) from an enterprise architecture perspective
- Design cloud adoption strategies that align with business objectives and enterprise architecture principles
- Conduct comprehensive application portfolio assessments using the 7 Rs framework (rehost, relocate, replatform, refactor, repurchase, retire, retain)
- Develop cloud adoption roadmaps with appropriate sequencing, dependencies, and risk mitigation strategies
- Implement security and compliance frameworks including shared responsibility models and regulatory requirements
- Apply the complete FinOps Framework including Cloud+ approach across all Scopes, Domains, and Capabilities
- Design cloud governance frameworks incorporating policy-as-code and automated compliance monitoring
- Establish cloud centers of excellence and platform engineering teams for organizational transformation
- Evaluate emerging technologies (AI/ML, edge computing, sustainability) and their enterprise architecture implications
Training Materials
Comprehensive courseware is distributed online at the start of class. All students receive a downloadable MP4 recording of the training.
Software Requirements
- Web browser with access to cloud provider consoles (AWS, Azure, GCP)
- Access to cloud cost management tools (demos provided)
- Collaboration tools (Miro/Lucidchart for architecture diagramming)
- Spreadsheet software for portfolio assessments
- Note-taking application or PDF reader
Training Topics
Cloud Models and Enterprise Architecture Impact
- Public, private, hybrid, and multi-cloud architectural implications
- Cloud service models (IaaS, PaaS, SaaS) and their EA considerations
- Major cloud provider ecosystem analysis (AWS, Azure, GCP)
- Vendor lock-in vs. best-of-breed strategies
- Cloud-native vs. cloud-enabled architecture patterns
Cloud Adoption Strategy and Planning
- Cloud readiness assessment frameworks and methodologies
- Application portfolio assessment and discovery processes
- The 7 Rs framework: rehost, relocate, replatform, refactor, repurchase, retire, retain
- Cloud adoption roadmap development and sequencing
- Cloud architecture standards and reference architectures
- Migration wave planning and dependency mapping
Security, Compliance, and Governance
- Shared responsibility models across cloud providers
- Identity and access management in hybrid environments
- Zero trust architecture principles in cloud contexts
- Regulatory compliance (SOC 2, HIPAA, GDPR, FedRAMP)
- Cloud governance frameworks and policy engines
- Policy-as-code implementation and automation
- Risk assessment and mitigation strategies
Cost Governance and FinOps Framework
- Complete FinOps Framework with Cloud+ approach
- Key Scopes: public cloud, SaaS, data center, AI, and licensing
- Four Domains and 22 Capabilities detailed exploration
- Crawl-Walk-Run maturity model application
- Showback and chargeback implementation strategies
- Cost allocation and attribution methodologies
- Cloud financial forecasting and budgeting
Operational Excellence and Reliability
- Cloud operations architecture and observability design
- SLA and SLO design for cloud workloads
- Site reliability engineering (SRE) principles and practices
- Incident response and disaster recovery in cloud environments
- Performance monitoring and optimization strategies
- Automation and infrastructure-as-code practices
Organizational Change Management
- Building cloud centers of excellence (CCoE)
- Platform engineering team structures and responsibilities
- Skills transformation and training program development
- DevOps culture integration with enterprise architecture
- Change management strategies for cloud transformation
- Communication and stakeholder engagement approaches
Emerging Trends and Future Considerations
- AI and machine learning platform architecture
- AI cost governance and FinOps for AI workloads
- Edge computing architectural patterns and implications
- Sustainability considerations in cloud architecture
- Serverless and event-driven architecture evolution
- Container orchestration and microservices governance
- Data architecture in multi-cloud environments