Every engineering choice has trade-offs — reliability vs. cost, performance vs. maintainability, speed vs. safety. Great engineers don’t chase the “perfect” design; they make informed, transparent decisions and leave a record for those who come next. This post explores how to capture those decisions using Architecture Decision Records (ADRs) and how to reason through trade-offs using Azure’s Well-Architected Framework and a lightweight ATAM (Architecture Trade-off Analysis Method) checklist.
Why Decision-Making Matters
Without a shared framework, context fades and teams' re-debate old choices.
ADRs solve that by recording the why behind design decisions — what problem we solved, what options we considered, and what trade-offs we accepted.
A good ADR:
- Lives next to the code in your repo.
- Explains reasoning in plain language.
- Survives personnel changes and version history.
Think of it as your team’s engineering memory.
The Five Pillars of Trade-offs
At Microsoft, we frame every major design discussion using the Azure Well-Architected pillars:
- Reliability – Will the system recover gracefully from failures?
- Performance Efficiency – Can it meet latency and throughput targets?
- Cost Optimization – Are we using resources efficiently?
- Security – Are we minimizing blast radius and exposure?
- Operational Excellence – Can we deploy, monitor, and fix quickly?
No decision optimizes all five. Great engineers make conscious trade-offs — and document them.
A Practical Decision Flow
| Step | What to Do | Output |
|---|---|---|
| 1. Frame It | Clarify the problem, constraints, and quality goals (SLOs, cost caps). | Problem statement |
| 2. List Options | Identify 2-4 realistic approaches. | Options list |
| 3. Score Trade-offs | Use a Decision Matrix to rate options (1–5) against pillars. | Table of scores |
| 4. ATAM-Lite Review | List scenarios, identify sensitivity points (small changes with big impact) and risks. | Risk notes |
| 5. Record It as an ADR | Capture everything in one markdown doc beside the code. | ADR file |
Example: Adding a Read-Through Cache
Decision: Add a Redis cache in front of Cosmos DB to reduce read latency.
Context: Average P95 latency from DB is 80 ms; target is < 15 ms.
Options:
A) Query DB directly
B) Add read-through cache using Redis
Trade-offs
- Performance: + Massive improvement in read speed.
- Cost: + Fewer RU/s on Cosmos DB.
- Reliability: − Risk of stale data if cache invalidation fails.
- Operational: + Added complexity for monitoring and TTLs.
Templates You Can Re-use
ADR Template
# ADR-001: Add Read-through Cache in Front of Cosmos DB Status: Accepted Date: 2025-10-21 Context: High read latency; P95 = 80ms, target <15ms Options: A) Direct DB reads B) Redis cache for hot keys ✅ Decision: Adopt Redis cache for performance and cost optimization. Consequences: - Improved read latency and reduced RU/s cost - Risk of data staleness during cache invalidation - Added operational complexity Links: PR#3421, Design Doc #204, Azure Monitor dashboard
Decision Matrix Example
| Pillar | Weight | Option A | Option B | Notes |
|---|---|---|---|---|
| Reliability | 5 | 3 | 4 | Redis clustering handles failover |
| Performance | 4 | 2 | 5 | In-memory reads |
| Cost | 3 | 4 | 5 | Reduced RU/s |
| Security | 4 | 4 | 4 | Same auth posture |
| Operational Excellence | 3 | 4 | 3 | More moving parts |
Weighted total = Σ(weight × score) → best overall score wins.
Team Guidelines
- Create a /docs/adr folder in each repo.
- One ADR per significant change; supersede old ones instead of editing history.
- Link ADRs in design reviews and PRs.
- Revisit when constraints change (incidents, new SLOs, cost shifts).
- Publish insights as follow-up blogs to grow shared knowledge.
Why It Works
This practice connects the theory of trade-offs with Microsoft’s engineering culture of reliability and transparency.
It improves onboarding, enables faster design reviews, and builds a traceable record of engineering evolution.
Join the Conversation
Have you tried ADRs or other decision frameworks in your projects?
Share your experience in the comments or link to your own public templates — let’s make architectural reasoning part of our shared language.
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