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Cheat Cards

One-page printables to keep alongside your workstation or pin to a team wall. Each card is designed for A4 landscape. A LaTeX-rendered PDF is linked at each card heading; alternatively use your browser’s Print or Save as PDF (Ctrl/Cmd+P) on this page — the print stylesheet renders one card per landscape page.

A combined PDF of all cards is available: Download all cards (PDF).


| # | View | What it describes | Primary audience | |---|------|-------------------|------------------| | 3.1 | Logical View | Components, services, patterns — what the solution is | Architects, Developers | | 3.2 | Integration & Data Flow | Data flows, APIs, integrations — how components talk | Integrators, Architects | | 3.3 | Physical View | Hosting, compute, networking, environments — where it runs | Infrastructure, DevOps | | 3.4 | Data View | Data stores, classification, retention — what data it holds | Data Architects, Compliance | | 3.5 | Security View | IAM, encryption, monitoring, threats — how it’s protected | Security, CISO, Compliance | | 3.6 | Scenarios | Use cases, ADRs — how it behaves and why | All stakeholders |

Remember: No single view tells the full story. Together, they answer every reasonable question from any reasonable reviewer.


Tier 2: Quality Attributes (Section 4) — cross-cutting

Section titled “Tier 2: Quality Attributes (Section 4) — cross-cutting”

| # | Attribute | Assess across every view | Key questions | |---|-----------|--------------------------|---------------| | 4.1 | Operational Excellence | Can we operate it in production? | Observability, runbooks, alerts, incident response | | 4.2 | Reliability & Resilience | What happens when something fails? | RTO, RPO, DR strategy, backup, fault tolerance | | 4.3 | Performance Efficiency | Does it meet its targets at load? | P95/P99 latency, throughput, concurrency, growth | | 4.4 | Cost Optimisation | Is it priced to the value delivered? | Capex/opex, unit economics, commitment discounts, exit cost | | 4.5 | Sustainability | Is it environmentally responsible? | Carbon baseline, efficient resources, SCI metric |

Document tradeoffs explicitly — when one quality attribute constrains another, name the trade-off and the rationale.

Security is a View (3.5) — it’s cross-cutting enough to warrant its own structure, so don’t look for it here.


Section 6.1–6.5 Decision Making & Governance

Section titled “Section 6.1–6.5 Decision Making & Governance”

Constraints (6.1) — fixed limitations the design must work within

| ID | Constraint | Category | Impact | Last Assessed | |----|-----------|----------|--------|---------------| | C-001 | | regulatory / technical / commercial / organisational / time | | |

Assumptions (6.2) — things treated as true but not verified

| ID | Assumption | Impact if false | Certainty | Status | Owner | |----|-----------|----------------|-----------|--------|-------| | A-001 | | | high / medium / low | open / closed | |

Risks (6.3) — potential events with negative impact

| ID | Risk | Severity | Likelihood | Owner | Mitigation | Residual | |----|------|:---:|:---:|:---:|-----------|:---:| | R-001 | | H/M/L | H/M/L | | | H/M/L |

Dependencies (6.4) — external factors this design relies on

| ID | Dependency | Direction | Status | Owner | |----|-----------|-----------|--------|-------| | D-001 | | inbound / outbound | committed / not-committed / resolved | |

Issues (6.5) — problems that have already materialised

| ID | Issue | Impact | Owner | Resolution Plan | Status | |----|------|:---:|:---:|-----------------|:---:| | I-001 | | H/M/L | | | open / in-progress / resolved |

Golden rule: Every row needs an owner and a date. Anonymous = unaccountable.


| Score | Level | What it means | |:-----:|-------|---------------| | 0 | Not Addressed | No evidence for this area | | 1 | Acknowledged | Concern recognised, no design or evidence | | 2 | Partial | Some requirements met, significant gaps | | 3 | Mostly Addressed | Most requirements met, minor gaps (passing grade) | | 4 | Fully Addressed | All requirements met with evidence | | 5 | Exemplary | Reference-quality — best practice |

The overall score is the lowest individual section score, not an average. A solution with 5 in Performance but 1 in Security is a “1”, not a “3” — the Security gap is the concern.

14 sections: 1, 3.1–3.6, 4.1–4.5, 5, 6 (Executive Summary, the six Views, the five Quality Attributes, Lifecycle, Decision Making).

Organisation thresholds (suggested defaults)

Section titled “Organisation thresholds (suggested defaults)”
  • All sections ≥ 3 → production approval
  • All sections ≥ 4 → Tier 1/2 critical systems
  • Section = 0 or 1 → remediation plan required

| Depth | When to use | Typical effort | Governance gate | |-------|-------------|----------------|-----------------| | Minimum | PoC, dev/test systems, Tier 5 internal tools | 1–3 hours | Development review | | Recommended | Production-bound systems, Tier 3–4 | 1–2 days | Production approval | | Comprehensive | Regulated, Tier 1–2 critical | 1–2 weeks | Enterprise review |

  • Tier 1 Critical → Comprehensive
  • Tier 2 High → Comprehensive
  • Tier 3 Medium → Recommended
  • Tier 4 Low → Recommended
  • Tier 5 Minimal → Minimum

Over-documenting a simple tool burns goodwill. Under-documenting a critical system hides risk. Calibrate to risk, not to tradition.


Where carbon footprint is actually decided

Section titled “Where carbon footprint is actually decided”

Most of a SAD’s environmental impact is locked in by a small number of decisions. Get these right and Section 4.5 becomes evidence rather than aspiration.

| Decision | Where in the SAD | Quick win | |----------|------------------|-----------| | Cloud region | 3.3 Physical View | Pick a region with high renewable energy share. Carbon intensity varies 5–10× across regions of the same provider. | | Non-prod runtime | 3.3 + 5.5 Operations | Auto-shutdown dev/test out of hours. Typical saving: 60–70% of non-prod compute cost and carbon. | | Compute family | 3.3 Physical View | ARM (Graviton, Ampere, Cobalt) and latest-generation x86 deliver 20–40% better performance-per-watt than older instance types. | | DR posture | 3.3 + 4.2 Reliability | A warm standby running 24×7 doubles compute footprint. Match DR mode (cold / pilot light / warm / hot) to the actual RTO. | | Data retention | 3.4 Data View | Set a retention policy and automate expiry. Indefinite “keep just in case” is the most common waste. | | Cold storage tiering | 3.4 Data View | Move logs/snapshots/backups to archive tiers (S3 Glacier, Azure Archive). Cost and carbon both drop sharply. | | Caching & async | 3.1 Logical View | Avoid recomputation. Cache responses, debounce polls, replace busy-wait with events. | | Right-sizing cadence | 5.5 Operations | Quarterly right-sizing using cloud advisor tools catches drift. Without a cadence, over-provisioning grows linearly. |

| Principle | Meaning | Typical action | |-----------|---------|----------------| | Carbon efficiency | Emit the least carbon for a given output | Region choice, ARM compute, retention | | Energy efficiency | Use the least energy for a given task | Caching, async, code-level efficiency | | Carbon awareness | Do more when the grid is clean, less when it isn’t | Time-shift batch jobs, defer non-urgent work |

A Tier 5 internal tool running on shared SaaS doesn’t need a Software Carbon Intensity baseline. Match the depth of treatment to the system’s actual footprint. A 50-instance e-commerce platform deserves the full Section 4.5 treatment; a fortnightly batch job on shared compute does not.



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These cards are designed to sit alongside the full standard — not to replace it. Use them for reference during drafting and review; read the full standard pages for detail and context.