Core components of the architecture

– Enterprise Architecture: Holistic blueprint covering business processes, applications, data, and technology to ensure IT supports business strategy and cross-organizational consistency.
– Solution / Software Architecture: Design of individual systems and applications, including component boundaries, interfaces, patterns, and runtime behavior.
– Infrastructure / Technology Architecture: Physical and virtual platforms (servers, networks, cloud, virtualization) and their configuration for availability, cost, and performance.
– Data Architecture: Models, storage, integration, governance, and access patterns that guarantee integrity, lineage, and usability of data across systems.
– Security and Compliance: Cross-cutting controls, identity models, encryption, and audit requirements embedded into each architectural layer.

Design and delivery process (stages and key artifacts)

1. Understand context and requirements — capture business goals, functional and non-functional requirements, constraints, stakeholders, and KPIs.
2. High-level architecture (HLA) — define system context, major components, deployment zones, and integration patterns; produce context diagrams and capability maps.
3. Detailed design and pattern selection — choose styles (microservices, layered, event-driven), data flows, APIs, and infrastructure patterns; produce sequence diagrams, component diagrams, and data models.
4. Decision recording and trade-offs — document architectural decisions, rationale, alternatives, and impact on cost, performance, security, and time to market.
5. Validation and testing — validate architecture against non-functional requirements through prototypes, performance tests, security reviews, and compliance checks.
6. Communication and handover — deliver architecture blueprints, runbooks, deployment diagrams, and governance checklists to engineering and operations teams.

Key artifacts: capability maps, context diagrams, component and sequence diagrams, data models, non-functional requirements matrix, architecture decision records (ADRs), deployment and runbook documents.

Governance, roles, and skills

– Enterprise architects — set strategy, ensure alignment with business goals, and own cross-domain standards.
– Solution architects — design individual systems to meet functional and non-functional needs and map to enterprise constraints.
– Infrastructure architects / Cloud architects — specify platform choices, capacity, resilience, and cost models.
– Data architects and security architects — enforce data models, governance, privacy, and security controls across solutions.
– Governance bodies — architecture review board, standards council, and change advisory boards that approve ADRs and enforce lifecycle policies.

Required skills: strategic business understanding, system design, integration patterns, data modelling, cloud and infrastructure expertise, security, and effective stakeholder communication.

Principles, trade-offs, and common risks

– Principles: business-driven design, modularity, observability, resilience, automation, and change readiness.
– Typical trade-offs: speed vs. maintainability, centralization vs. autonomy, consistency vs. innovation, and up-front cost vs. lifecycle TCO.
– Common risks: misalignment with business priorities, over-engineering, ignoring non-functional requirements, poor documentation, and weak governance leading to fragmentation and technical debt.

KPIs, maturity and tooling

– KPIs: alignment score to business goals, time to market for features, system availability, mean time to recovery (MTTR), performance SLAs, deployment frequency, architecture debt index, and cost per transaction.
– Maturity model: ad-hoc → repeatable → defined → managed → optimized, with increasing emphasis on automated validation, measurable SLAs, and continuous architecture reviews.
– Tooling and practices: architecture modeling tools, ADR repositories, CI/CD pipelines, automated testing and security scans, observability stacks, API gateways, and cloud cost-management platforms.