Body
Purpose
The Enterprise Architecture Principles define the enduring decision-making guidelines that shape technology strategy, architecture, engineering, governance, and operations across the University.
The principles provide a common foundation for evaluating technology opportunities, risks, investments, and trade-offs. They guide the development of Architecture Controls, Architecture Decision Records, Standards, Patterns, Products, and technology implementations.
Architecture Principles are intentionally stable and technology-neutral. They describe how decisions should be approached rather than prescribing a specific platform, product, or implementation method. Technologies, regulations, and institutional priorities will change over time, but the principles provide a consistent framework for evaluating those changes.
Scope
These principles apply to:
- Enterprise technology strategies and roadmaps
- Business and technology capabilities
- Applications and application platforms
- Data platforms and information management
- Integrations, APIs, and messaging
- Cloud and on-premises infrastructure
- Identity, networking, monitoring, and security
- Shared services and enterprise platforms
- Infrastructure and Platform Products
- Technology acquisition and SaaS adoption
- Architecture reviews and change control
- Modernization and lifecycle decisions
- Regulated and non-regulated workloads
Using the Principles
Architecture Principles guide decisions. They do not replace University or Board of Trustees policies, regulatory requirements, risk assessments, Architecture Controls, Standards, or detailed technical design.
Not every principle will carry equal weight in every decision. Responsible architecture requires informed judgment, collaboration, and transparent documentation of significant trade-offs.
Enterprise Architecture Principles
1. Prioritize People and Outcomes Over Technology
Statement
Technology decisions must begin with the people, services, and University outcomes they are intended to support.
Rationale
Technology creates value when it enables teaching, learning, research, administration, service delivery, security, and effective operations. Selecting a product or platform before understanding the need can create unnecessary complexity and poorly aligned investments.
Implications
- Architecture work begins with a clearly stated need or outcome.
- Affected stakeholders participate in defining requirements and trade-offs.
- Designs consider accessibility, usability, supportability, and operational impact.
- Technology preferences do not replace an understanding of the problem.
- Success is measured through outcomes and adoption, not deployment alone.
2. Align Architecture With University Strategy
Statement
Architecture decisions must support University priorities, capabilities, risks, and long-term objectives.
Rationale
Architecture connects strategy to implementation. Solutions selected in isolation may provide short-term functionality while increasing duplication, cost, risk, or operational burden across the institution.
Implications
- Significant initiatives identify the business or institutional outcome they support.
- Technology roadmaps connect to strategic priorities.
- Cross-unit effects are considered before local optimization.
- Decisions identify immediate value and long-term consequences.
- Investments consider lifecycle cost, risk, and organizational readiness.
3. Make Decisions and Work Visible
Statement
Significant architecture decisions, requirements, relationships, ownership, and implementation status must be discoverable and traceable.
Rationale
Architecture loses value when it exists only in meetings, individual knowledge, source-code comments, or disconnected documents. Visible work allows teams to reuse prior decisions, coordinate changes, understand dependencies, and preserve institutional knowledge.
Implications
- Significant decisions are captured in Architecture Decision Records.
- Architecture artifacts are maintained as governed records.
- Ownership and lifecycle information remain current.
- Products are related to their source repositories and implemented solutions when practical.
- Product versions are represented in deployment metadata when practical.
- Architecture information should be both human-readable and machine-queryable.
4. Standardize Before Customizing
Statement
Teams should use approved enterprise Standards, Patterns, Products, and shared capabilities before creating custom alternatives.
Rationale
Standardization improves consistency, security, interoperability, supportability, and delivery speed. Custom solutions create long-term value only when they address a requirement that approved approaches cannot reasonably satisfy.
Implications
- Approved Products are the default starting point for implementation.
- Custom approaches require a documented business or technical rationale.
- Repeated compensating approaches trigger review of the applicable Standard, Pattern, or Product.
- Standards define durable requirements without unnecessarily prescribing implementation details.
- Variability is intentional and supported rather than accidental.
5. Reuse Enterprise Capabilities
Statement
Common capabilities should be provided and consumed as shared enterprise services when reuse is practical, secure, and operationally appropriate.
Rationale
Duplicating identity, monitoring, governance, automation, management, integration, and other common capabilities increases cost and operational complexity. Reuse improves consistency while allowing workload-specific isolation when necessary.
Implications
- Teams evaluate available enterprise capabilities before creating new services.
- Shared services have defined ownership, support expectations, governance, and lifecycle management.
- Reuse does not eliminate workload isolation, data-protection, or accountability requirements.
- Services that process regulated data follow applicable hosting and protection requirements.
- Shared capabilities provide documented and supportable integration mechanisms.
6. Leverage the Strengths of the Platform
Statement
Solutions should use the native strengths and supported capabilities of the selected platform rather than unnecessarily recreating those capabilities.
Rationale
Platforms provide built-in mechanisms for identity, governance, automation, observability, resilience, security, and lifecycle management. Using those capabilities generally improves supportability and operational consistency.
Implications
- Platform-native capabilities are evaluated before custom mechanisms are introduced.
- Platform-specific decisions are documented in ADRs, Standards, Patterns, and Products.
- Platform selection considers organizational skills, operations, security, cost, and lifecycle support.
- Portability is pursued when it provides identifiable value rather than as an automatic objective.
7. Automate Repeatable Work
Statement
Repeatable provisioning, configuration, governance, validation, and operational activities should be automated whenever practical.
Rationale
Automation reduces manual error, improves repeatability, makes implementation intent visible, and allows approved architecture to be delivered consistently.
Implications
- Infrastructure as Code is preferred for supported infrastructure deployments when practical.
- Products provide reusable and versioned deployment capabilities.
- Manual deployment does not become an undocumented default.
- Automation includes appropriate validation, ownership, change control, and traceability.
- Product versions are identifiable in deployment records or resource metadata when practical.
- Automation remains understandable and maintainable by responsible support teams.
8. Secure and Protect by Design
Statement
Security, privacy, data protection, and regulatory requirements must be incorporated into architecture from the beginning.
Rationale
Adding security after implementation creates avoidable risk, rework, and operational complexity. Security is a shared responsibility supported through identity, access control, isolation, monitoring, data protection, recovery, and governance capabilities.
Implications
- Data classification and regulatory scope are identified early.
- Access follows approved identity, authorization, and lifecycle processes.
- Data protection addresses confidentiality, integrity, availability, retention, and disposal.
- Security-relevant activities are observable and auditable.
- Security requirements apply to shared services and integrations as well as workload resources.
- Compensating controls and risk-mitigation measures are documented and reviewed when requirements cannot be implemented as written.
9. Design for Observability and Accountability
Statement
Solutions must provide sufficient operational, security, and audit visibility to understand their condition, activity, ownership, and impact.
Rationale
A solution that cannot be observed cannot be operated, secured, investigated, or improved effectively. Visibility also supports accountability and evidence-based decisions.
Implications
- Monitoring and logging requirements are included during design.
- Applications, infrastructure, identity, integrations, and data services emit appropriate telemetry.
- Ownership and support information are maintained.
- Alerts correspond to actionable operational or security conditions.
- Operational evidence supports reviews, investigations, and improvement.
- Enterprise monitoring capabilities are used when appropriate and available.
10. Design for Resilience and Recovery
Statement
Solutions must be designed with failure, recovery, continuity, and operational sustainability in mind.
Rationale
Components, services, integrations, and human processes can fail. Architecture accounts for those failures and provides recovery capabilities appropriate to the business need.
Implications
- Availability, recovery, and continuity requirements are defined with workload owners.
- Architecture identifies critical dependencies and failure modes.
- Backup is not treated as equivalent to validated recovery.
- Recovery procedures and capabilities are periodically validated.
- Monitoring supports failure detection and recovery operations.
- Resilience investments are proportionate to business impact and recovery requirements.
11. Optimize for the Full Lifecycle
Statement
Architecture decisions must consider acquisition, implementation, operation, support, change, cost, modernization, and retirement.
Rationale
Initial delivery represents only part of a solution's cost and impact. Decisions that accelerate delivery can create disproportionate operational expense, technical debt, fragility, or support burden later.
Implications
- Architecture evaluations include ownership and supportability.
- Cost is considered across the lifecycle.
- Unsupported technologies have modernization or retirement plans.
- Technical-debt decisions are visible and revisited.
- Decommissioning is considered part of the architecture lifecycle.
12. Prefer Simplicity and Reduce Unnecessary Complexity
Statement
Architectures should use the simplest approach that satisfies the required outcomes, Architecture Controls, and service expectations.
Rationale
Every additional platform, integration, customization, abstraction, and operational dependency creates cost and risk. Simplicity improves understanding, reliability, security, and the ability to change.
Implications
- New technology has a clearly identified purpose.
- Similar capabilities are consolidated when practical.
- Designs minimize unnecessary components and dependencies.
- Complexity required by a business or regulatory need is documented.
- Architecture distinguishes essential complexity from accidental complexity.
- Tools are not adopted solely because they are new or technically interesting.
13. Treat Data as an Enterprise Asset
Statement
Data must be governed, protected, understood, and made appropriately available throughout its lifecycle.
Rationale
Data supports institutional decisions, research, teaching, reporting, service delivery, and operational processes. Its value depends on quality, context, protection, stewardship, and appropriate access.
Implications
- Data ownership and stewardship are identified.
- Data classification and regulatory scope are understood.
- Authoritative sources are identified where practical.
- Data access is limited to approved purposes and identities.
- Integration and replication do not bypass protection or retention requirements.
- Data lifecycle decisions include retention, recovery, and disposal.
14. Interoperate Through Defined Interfaces
Statement
Systems and services should exchange information through documented, governed, and supportable interfaces.
Rationale
Point-to-point dependencies, undocumented data movement, and implementation-specific coupling make solutions difficult to change and support. Defined interfaces improve reuse, security, discoverability, and lifecycle independence.
Implications
- APIs, events, messages, files, and data exchanges have identified owners and consumers.
- Integrations are documented and versioned when appropriate.
- Authentication, authorization, data protection, monitoring, and failure handling are considered.
- Consumers do not depend on undocumented implementation details.
- Enterprise integration capabilities are reused when available.
15. Govern Through Collaboration and Shared Accountability
Statement
Architecture is a collaborative practice in which business, architecture, engineering, security, GRC, operations, and workload teams share responsibility for outcomes.
Rationale
Architecture cannot succeed through centralized authority alone. The people who own, implement, secure, govern, and operate solutions bring different knowledge needed to make durable decisions.
Implications
- Architecture decisions include stakeholders needed to understand impacts and trade-offs.
- Governance operates through established change control processes.
- CAB review provides a forum for informed decisions rather than functioning solely as a technical gate.
- Responsibilities and decision rights are explicit.
- Architecture does not replace business ownership, security authority, or operational accountability.
- Compensating controls and risk mitigation decisions have identified owners.
16. Commit to Iteration and Continuous Improvement
Statement
Architecture must evolve through feedback, measurement, learning, and controlled change.
Rationale
No architecture remains complete indefinitely. Business needs, regulations, technologies, risks, and operational experience change. Architecture must be durable without becoming static.
Implications
- Standards, Patterns, Products, and roadmaps are reviewed as conditions change.
- Implementation issues and recurring operational incidents inform architecture improvements.
- Product versions are governed throughout their lifecycle.
- New decisions build on existing knowledge rather than silently replacing it.
- Adoption and effectiveness are evaluated rather than assumed.
- Architecture enables incremental progress while preserving strategic direction.
Application and Governance
The principles should be considered when:
- Creating or revising an Architecture Decision Record
- Developing an Architecture Control
- Writing or updating a Standard
- Creating an implementation Pattern
- Designing an Infrastructure or Platform Product
- Selecting a cloud, SaaS, application, integration, or data platform
- Reviewing a workload through CAB
- Evaluating compensating controls and risk mitigation
- Planning modernization or retirement
- Developing technology roadmaps
- Reviewing operational findings and technical debt
Enterprise Architecture maintains the principles in collaboration with relevant business, engineering, security, GRC, operations, and workload stakeholders.
Changes to the principles follow the established change control process. Principles should change infrequently. Changes involving a technology, platform, implementation approach, or workload should normally be addressed through an ADR, Standard, Pattern, or Product rather than by revising the enterprise principles.
Desired Outcome
Successful application of the principles should result in solutions that align with University needs, reuse proven capabilities where practical, protect institutional data, support effective operations, and remain understandable and supportable throughout their lifecycle.