nw-stress-analysis

name	nw-stress-analysis
description	Advanced architecture stress analysis methodology for designing systems that survive unknown stresses. Load on its semantic trigger — external/nondeterministic dependency, recovery/retry/compensation/degradation, contagion, infrastructure/substrate uncertainty, high-uncertainty socio-technical/business boundary — or on explicit --residuality (force-on).
user-invocable	false

Advanced Architecture Stress Analysis

Complexity science-based approach for architectures surviving unknown future stresses. Based on residuality theory by Barry M. O'Reilly (Former Microsoft Chief Architect, PhD Complexity Science) — primary sources and the synthesis boundary: ADR-SSOT-002 §6a.

Core paradigm: "Architectures should be trained, not designed."

When to Apply

Apply only on a semantic trigger, never as default ceremony: an external/ nondeterministic dependency; recovery/retry/compensation/degradation; contagion across components; infrastructure/substrate uncertainty; a high-uncertainty socio-technical/business boundary; or explicit --residuality (force-on).

Skip for: stable, simple targets where none of the triggers above fire.

Stressor derivation (mechanical entry path)

A stressor is the negation of a declared assumption. Derive the stressor list by enumerating the model's declared assumptions (fairness, atomic steps, closed types) and negating each -- no creativity required. The residue is measured by which laws fall after negation, and a tool answers that. The only irreducibly human step is deciding which stressors matter economically. Finds structural incoherence, never temporal holes -- a temporal gap needs the model checker (nw-review design-review question set, T5), not stressor negation.

Three Core Concepts

1. Stressors

Unexpected events challenging operation. Categories: technical (failures, scaling, breaches) | business model (pricing shifts, competitive disruption) | economic (funding, market crashes) | organizational (restructuring, skill gaps) | regulatory (compliance changes) | environmental (infrastructure failures)

Brainstorm extreme and diverse. Goal = discovery, not risk assessment.

2. Residues

Design elements surviving after breakdown. Ask: "What's left when [stressor] hits?"

Example -- e-commerce under payment outage: residue = browsing, cart, wishlist. Lost: checkout, payment. Stress-informed: allow "reserve order, pay later."

3. Attractors

States systems naturally tend toward under stress. Differ from designed intent. Discovered through testing, not predicted.

Example -- social media under growth: designed = proportional scaling, actual attractor = read-heavy CDN mode (reads survive, writes queue/fail). Design for this.

Process

Step 1: Create Naive Architecture

Straightforward solution for functional requirements. No speculative resilience. Document as baseline.

Step 2: Simulate Stressors

Brainstorm the smallest diverse set that covers the categories, under an explicit budget (time-box or count agreed up front). Include extremes. Engage domain experts. Prioritize by impact, not probability. Expand only when a new stressor yields a genuinely new residue/attractor — stop once additions repeat known findings. No fixed quota.

Step 3: Uncover Attractors

Walk each stressor with experts. Ask "What actually happens?" Identify emergent behaviors. Recognize cross-stressor patterns.

Step 4: Identify Residues

Per attractor: which components remain? Critical vs non-critical? Stress-only dependencies?

Step 5: Modify Architecture

Reduce coupling, add degradation modes, introduce redundancy, apply resilience patterns (circuit breakers, queues, caching) only where the residues found justify them — no universal threshold or default pattern; the fit is evidenced per system.

Step 6: Empirical Validation

Generate a second, unseen stressor set. Apply to both naive and modified. Modified must survive more unforeseen stressors — this evidences generalization, prevents overfitting to the discovery set, and is never skipped.

Practical Tools

Incidence Matrix

Rows: stressors. Columns: components. Mark affected cells. Reveals vulnerable components (high column count), high-impact stressors (high row count) and coupling indicators. Not a new persisted artifact — a working aid folded into the existing architecture brief (Step 5's heuristic 7).

Adjacency Matrix

Rows/columns: components. Mark direct connections. Coupling ratio = K/N is a relative indicator across this system's own stressor runs, not a universal threshold — compare naive vs modified architecture, never against a fixed cross-system number.

Contagion Analysis

Model as directed graph. Simulate failure. Trace cascade. Identify SPOFs. Add circuit breakers, timeouts, fallbacks.

Architectural Walking

Select stressor, walk behavior step-by-step with team, identify attractors/residues, propose modification, re-walk to validate, repeat.

Design Heuristics

1. Correctness and criticality are complementary, not alternatives: the accepted observable contract must hold, and the system must reconfigure toward what matters most when it cannot hold everything — optimize for both, never trade one for the other
2. Embrace strategic failure: some parts fail so critical parts survive
3. Solve random problems: diverse scenarios create more robust architectures than predicted-scenario optimization
4. Minimize connections: default loosely-coupled; tight only when essential
5. Design for business model attractor: how revenue/cost constraints shape behavior under stress
6. Train through iteration: iterative stress-test-modify beats upfront planning
7. Document stress context: the existing architecture brief (ADR-SSOT-002 §6a) carries stressor analysis and resilience rationale — no separate stressor field or matrix artifact

Integration with Other Practices

• DDD: stressor analysis deepens domain understanding; stress Event Storming reveals richer bounded contexts
• Microservices: incidence matrix validates service boundaries (low shared stressor impact = good)
• Event-Driven: async communication naturally reduces coupling
• Chaos Engineering: stressor brainstorming feeds chaos experiment design
• ADRs: include stressor analysis, attractors, resilience rationale

Algebra Bridge (ADR-SSOT-002 §6a)

Residuality discovers plausible behavior under uncertainty; algebra (nw-algebraic-design-protocol) owns observations, equality and laws within and across the residues found here. Per stressor s, a residue names its row: stressor | preserved observation | allowed degradation | forbidden outcome | recovery | boundary. The cross-residue kernel is the NAMED set of properties intentionally required across the selected residues — never a blind intersection. A transformation between residues is a structure-preserving morphism/refactoring only when its named preservation map is stated; partial preservation is controlled degradation; a changed user observation is a product/design change owned by its SSOT; absent preservation is replacement, not refactoring. Correctness of the accepted contract and criticality across stressors are complementary outcomes, never alternatives. Rows project into the existing DeliveryContract targets/boundary/obligations and derived tests — no new field, no persisted matrix. On the trigger, load nw-algebraic-design-protocol alongside this skill.

Differentiation from Risk Management

Traditional: predict and prevent specific failures. This: discover candidate residues under a diverse, budgeted stressor set and validate them against a second, unseen set — evidence of broader survival, never a guarantee against any stress. Question shifts from "What risks to prepare for?" to "What happens when this stressor hits, and does the residue generalize?"