Description

This curriculum spans the breadth of a multi-workshop technical governance program, addressing the same decision frameworks and coordination challenges seen in enterprise application modernization initiatives, from initial scoping through to system retirement.

Module 1: Strategic Alignment and Project Initiation

Selecting between greenfield development and brownfield modernization based on legacy system constraints and business continuity requirements.
Defining measurable success criteria in collaboration with business stakeholders to align technical deliverables with operational KPIs.
Conducting feasibility assessments that evaluate technical, financial, and resource constraints before project approval.
Establishing a cross-functional steering committee to resolve prioritization conflicts between IT, security, and business units.
Choosing project funding models (CAPEX vs. OPEX) based on organizational accounting policies and long-term ownership plans.
Documenting initial scope boundaries and change control thresholds to prevent uncontrolled feature creep during execution.

Module 2: Requirements Engineering and Stakeholder Analysis

Mapping user roles to functional permissions during requirements gathering to ensure compliance with least-privilege access models.
Resolving conflicting requirements from regional business units by establishing a centralized prioritization framework.
Integrating non-functional requirements (e.g., response time, uptime) into user stories to prevent performance gaps in production.
Using traceability matrices to link each requirement to test cases and regulatory obligations for audit readiness.
Deciding when to defer edge-case requirements based on usage analytics and implementation cost-benefit analysis.
Managing stakeholder expectations when technical limitations prevent fulfillment of requested capabilities.

Module 3: Architecture Design and Technology Selection

Evaluating containerization vs. virtual machines based on scalability needs, operational overhead, and existing infrastructure.
Selecting integration patterns (APIs, message queues, ETL) based on data latency requirements and system coupling tolerance.
Choosing between monolithic and microservices architectures considering team size, deployment frequency, and monitoring complexity.
Implementing failover mechanisms and disaster recovery paths during design to meet defined SLAs.
Standardizing technology stacks across projects to reduce long-term maintenance and skills fragmentation.
Assessing third-party component risks, including license compliance, support lifespan, and vulnerability history.

Module 4: Development Practices and Code Governance

Enforcing code review policies that balance quality gates with development velocity in CI/CD pipelines.
Managing branching strategies (e.g., GitFlow vs. trunk-based) based on release cadence and team coordination needs.
Integrating static code analysis tools into build processes to detect security flaws and anti-patterns early.
Defining coding standards that align with organizational maintainability goals and onboarding efficiency.
Handling technical debt accumulation by allocating sprint capacity for refactoring based on risk exposure.
Coordinating parallel development across distributed teams using feature toggles and environment isolation.

Module 5: Testing Strategy and Quality Assurance

Allocating test automation coverage across unit, integration, and end-to-end levels based on risk and maintenance cost.
Designing test data management strategies that protect PII while enabling realistic test scenarios.
Integrating performance testing into release pipelines to detect regressions before production deployment.
Managing test environment parity to reduce defects caused by configuration drift.
Deciding when to use contract testing for microservices to reduce dependency on full integration environments.
Establishing defect triage processes that prioritize fixes based on business impact and reproducibility.

Module 6: Deployment Planning and Release Management

Choosing deployment patterns (blue-green, canary, rolling) based on risk tolerance and rollback requirements.
Scheduling production releases to avoid conflicts with business-critical periods and batch processing windows.
Coordinating change advisory board (CAB) approvals for high-impact deployments in regulated environments.
Validating rollback procedures through dry runs to ensure recovery readiness during failed deployments.
Managing configuration drift by enforcing infrastructure-as-code templates across environments.
Communicating deployment timelines and potential outages to support teams and end-user groups in advance.

Module 7: Post-Release Support and Operational Handover

Transferring incident response ownership to operations teams with documented runbooks and escalation paths.
Establishing service level indicators (SLIs) and error budgets to guide post-launch performance management.
Conducting blameless post-mortems to identify systemic issues after production incidents.
Integrating application monitoring with centralized logging to reduce mean time to diagnose (MTTD).
Managing hotfix processes that balance urgency with change control and testing requirements.
Updating technical documentation based on operational feedback to reflect actual system behavior.

Module 8: Lifecycle Governance and Retirement Planning

Defining end-of-life criteria for applications based on usage trends, support costs, and technology obsolescence.
Executing data archival strategies that comply with retention policies and legal discovery obligations.
Coordinating decommissioning activities with interdependent systems to prevent integration failures.
Conducting knowledge transfer sessions to preserve institutional memory before team disbandment.
Reallocating infrastructure resources from retired applications to active projects.
Auditing licensing agreements to terminate subscriptions and avoid continued billing post-retirement.