02Key conceptsHigh Level Design
02 · Core method
High Level Design
Trace read and write paths through the smallest architecture that can satisfy the target scale.Lesson spine
What you need to understand.
High-level design should prove one request can cross the system and satisfy the contract, not display a component inventory.
Start with data flow
Place the client, entry boundary, state owner, and response path. Trace a numbered request before adding scale mechanisms.
Separate writes and reads
Show where a mutation becomes durable and how a query assembles its answer. Different workloads often deserve different paths.
Add scale only where pressure appears
Replicate reads, partition writes, cache hot data, queue bursty work, or precompute expensive results only after naming the bottleneck.
Draw failure boundaries
Duplicate critical stateless services, isolate regional or tenant failure, and give asynchronous work a retry and dead-letter path.
Present in layers
Begin with the happy path, then annotate consistency, partition keys, caches, queues, and recovery so the interviewer can follow the evolution.
Before the boxes
Frame the decision.
What must work
Trace read and write paths through the smallest architecture that can satisfy the target scale.
What changes the design
Show one write path · one read path · one first-order scaling mechanism
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.
Initiates a named flow
Authenticates and routes
Owns business decisions
Commits truth
Decouples derived work
Serves latency-sensitive queries
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
Client — Initiates a named flow Define the output contract before moving to the next owner.
- 02
Edge — Authenticates and routes Define the output contract before moving to the next owner.
- 03
Service — Owns business decisions Define the output contract before moving to the next owner.
- 04
State store — Commits truth Define the output contract before moving to the next owner.
- 05
Async bus — Decouples derived work Define the output contract before moving to the next owner.
- 06
Read model — Serves latency-sensitive queries 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 | Separate reads and writes only when access patterns or guarantees differ. | 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
Unlabeled arrows hide protocol, ownership, synchrony, and commit boundaries.
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 High Level Design, the decision I want to make explicit is this: Separate reads and writes only when access patterns or guarantees differ. 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 High Level Design, 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?