05Design patternsIntroduction
05 · Reusable pattern
Introduction
Map requirements to reusable data, coordination, delivery, and scaling patterns.Lesson spine
What you need to understand.
Patterns are reusable mechanisms earned by a requirement; they are not product-name templates.
Start from pressure
Classify the dominant problem as read scale, write scale, large objects, coordination, asynchronous work, real-time delivery, or specialized indexing.
Name the invariant
State what must never be violated before selecting locks, queues, replicas, caches, or projections.
Apply the mechanism
Draw the state owner, boundary, and data flow that make the pattern work in this system.
Price the cost
Every pattern adds lag, coordination, storage, operational state, or recovery complexity. Say which cost is acceptable.
Know the boundary
Describe when the pattern stops fitting and what signal would trigger a different architecture.
Before the boxes
Frame the decision.
What must work
Map requirements to reusable data, coordination, delivery, and scaling patterns.
What changes the design
Classify by access pattern · state owner · coordination boundary · failure budget
What owns the truth
Identify the component that commits authoritative state, then separate synchronous confirmation from derived work.
What stays simple
Do not add global coordination, multi-region writes, or a specialized store until a requirement earns the complexity.
Architecture map
Trace ownership, not just traffic.
Follow the decision from left to right. Every arrow should have a reason.
Names the pressure
Reveals recurring shape
Defines correctness
Supplies mechanism
Adds complexity
States when not to use it
Walk one representative request across every arrow. Say whether the handoff is synchronous or asynchronous, what identity makes a retry safe, and which step changes authoritative state.
- 01
Requirement — Names the pressure Define the output contract before moving to the next owner.
- 02
Signal — Reveals recurring shape Define the output contract before moving to the next owner.
- 03
Invariant — Defines correctness Define the output contract before moving to the next owner.
- 04
Pattern — Supplies mechanism Define the output contract before moving to the next owner.
- 05
Cost — Adds complexity Define the output contract before moving to the next owner.
- 06
Boundary — States when not to use it Confirm the result and emit the evidence needed to reconcile it.
Decision table
Make the trade-offs explicit.
| Decision | Defensible position | Cost to acknowledge |
|---|---|---|
| Primary mechanism | Patterns are hypotheses, not answers; requirements must earn each mechanism. | The stronger guarantee usually adds coordination, latency, state, or operational work. |
| Sync vs. async | Keep only correctness-critical confirmation synchronous. Move derived views, notifications, analytics, and cleanup behind a durable boundary. | Async work needs idempotency, lag monitoring, replay, and a product definition for partial completion. |
| Simple vs. scaled | Begin with one logical owner and a clear API. Partition or replicate only the resource proven to be the first bottleneck. | Migration requires stable identities, versioned contracts, backfill, and a rollback path. |
Failure review
Design the recovery path.
Topic-specific risk
Cargo-cult matching by product name misses the real bottleneck.
ResponsePersist enough identity and state to distinguish retry, resume, compensation, and operator repair.
Dependency timeout
A timeout is ambiguous: the remote side may have failed, succeeded, or still be running.
ResponseUse deadlines, bounded backoff with jitter, idempotency keys, and a status or reconciliation path.
Overload or skew
Average capacity can look healthy while a tenant, key, partition, region, or expensive request saturates one owner.
ResponseExpose queue depth and hot-key share, apply backpressure, isolate tenants, and degrade optional work before correctness.
Evidence + level bar
Prove the design can be operated.
Health of the promise
Measure user-visible latency or freshness, correctness drift, saturation, retry volume, and time to recover. Alert on the failed promise—not only CPU.
Complete and clear
Finish the happy path, identify the state owner, choose reasonable building blocks, and explain one scale mechanism.
Trade-offs and failure
Separate read and write paths, define consistency, explain partitioning, and make duplicate or partial failure safe.
Evolution and operations
Discuss multi-region boundaries, migration, tenant isolation, capacity, observability, and how the architecture changes over time.
Interview language
Open the deep dive with a claim.
“For Introduction, the decision I want to make explicit is this: Patterns are hypotheses, not answers; requirements must earn each mechanism. I’ll trace the state-changing path first, show where the result becomes durable, then test the design against the highest-risk failure and our target scale.”
08 · Retrieval check
Can you defend it without the page?
- For Introduction, where is the correctness boundary and which failure would you test first?
- Which component owns committed truth, and what event or response proves the commit?
- Where is the first scaling or coordination bottleneck under the stated envelope?
- What happens after an ambiguous timeout or duplicate operation?
- Which complexity would you remove at one hundredth of the scale?