Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteApproach a system design interview in a deliberate sequence: clarify the requirements, estimate the scale, define interfaces and data, sketch the end-to-end design, then deep-dive into the most consequential components and trade-offs. The sequence keeps the discussion tied to the problem instead of turning it into an unstructured tour of technologies. It is a flexible framework, not a universal interview script.
What should you clarify before drawing the architecture?
Start by turning the prompt into an agreed scope. Ask what the system must do, who uses it, and which capabilities matter most. Then make exclusions explicit. An open-ended request such as “design a photo-sharing service” could mean uploads and feeds, or it could also include messaging, recommendations, moderation, and analytics. You cannot design all of those equally well in one interview.
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Separate functional requirements from constraints
- Functional requirements: the actions the system must support, such as creating a post, viewing a feed, or searching.
- Non-functional requirements: qualities that shape the design, such as latency, availability, consistency, durability, privacy, and cost.
- Out of scope: capabilities you and the interviewer agree not to design in depth.
Prioritize a small set of core user flows. If two requirements pull in different directions, ask which matters more. For example, a system that prioritizes serving reads during a network partition may make a different consistency trade-off from one that must reject stale results.
Interview formats differ by company and interviewer. Treat clarification as a conversation: confirm assumptions, listen for constraints, and adjust the depth and order of the framework rather than insisting on a fixed script.
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How much should you estimate?
Estimate only enough to explain choices that depend on scale. Rough, stated assumptions are more useful than false precision. Identify the quantities likely to affect the architecture: users, request rates, read-to-write mix, data size, retention, and—when relevant—bandwidth or peak traffic.
Make assumptions visible
Say what you are assuming before using a number. For instance, distinguish active users from registered users, average load from peak load, and retained data from total historical data. If the prompt gives no figures, ask for an input or offer a clearly labeled assumption that the interviewer can correct.
Connect the estimate to a decision
An estimate earns its place when it changes the design. A high read rate might motivate a cache or read replicas; growing retained data might affect partitioning and storage; large media objects could make bandwidth and object storage central concerns. If an estimate does not influence a choice, keep it brief.
Use order-of-magnitude reasoning and show the logic. Do not present an illustrative calculation as an industry benchmark or measured fact. The goal is to make your assumptions and their architectural consequences understandable.
How do interfaces and data connect the requirements to the design?
Once the scope and rough workload are clear, define how clients interact with the system and what information the system must retain. This is the bridge between user needs and architecture: interfaces describe operations, while entities and access patterns help determine storage and service boundaries.
Sketch the core interface
Write a few representative operations rather than an exhaustive API. For each, identify its inputs, output, and important behavior: what happens when the requested item is missing, whether the operation is idempotent, and whether the caller needs an immediate result. The exact format matters less than showing how the core use cases map to system actions.
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Name the important entities and access patterns
Identify the main records and relationships, then ask how the system reads and writes them. A feed, for example, may need to fetch recent items for a user; that access pattern differs from retrieving one item by its identifier. Consider expected volume and query needs before choosing a schema or partition key.
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A useful design explanation ties each significant data choice to a requirement. Avoid listing databases or APIs without showing why the system needs them.
How should you sketch the end-to-end system?
Draw the major components and trace the data through them for the core use cases. Start at the client and show the principal request path through entry points, application services, storage, and any supporting systems the requirements justify. Keep the first diagram at a level where the interviewer can follow the whole system.
Rank #4
Trace a normal request
Walk through one representative write and one representative read if both matter. Explain what each component receives, changes, stores, or returns. This catches gaps that a box diagram can hide—for example, a write path that saves data but never explains how a read finds it.
Add complexity only when it earns its place
Introduce caches, queues, replicas, search indexes, or background workers when they address an identified workload or constraint. Show where data is created, propagated, and consumed. If a component is asynchronous, explain what the caller sees before processing finishes and how the system handles delayed work.
The high-level drawing is a map, not an implementation specification. Keep low-level details for the components that most affect the requirements.
Best Value
Which components deserve a deep dive, and how do you explain trade-offs?
Choose one or two components whose behavior is especially important to the stated workload or constraints. Explain the normal path, likely bottleneck, failure behavior, and the cost of the design choice. A focused deep dive is stronger than briefly naming many technologies.
Compare options against the actual requirements
When multiple designs are plausible, compare them using the dimensions that matter for this prompt:
- Workload and access patterns
- Expected scale and growth
- Latency and data freshness
- Availability and consistency
- Failure recovery and durability
- Storage, partitioning, and operational complexity
- Cost
State the requirement driving your preference, then name what the alternative would improve or make harder. For example, a cache may reduce repeated read work but introduce freshness and invalidation questions. A queue can separate a request from slower processing, but now the design must address retries, duplicate work, and delayed completion.
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Discuss failure behavior, not just the happy path
For the chosen component, ask what happens if it is slow, unavailable, or returns incomplete data. Explain whether requests fail, retry, fall back, or continue with reduced functionality. Consider how the system recovers and what consistency the user observes. The right answer depends on the agreed requirements; no single availability, consistency, or latency target applies to every prompt.
How can you use this framework in the interview?
- Clarify: agree on core features, exclusions, users, and the constraints that matter.
- Estimate: state rough workload assumptions and use them to motivate design choices.
- Define: outline the key operations, entities, and access patterns.
- Sketch: draw the major components and trace the main data flows.
- Deep-dive: examine the most important components, including bottlenecks, failures, and trade-offs.
Use the steps to keep the conversation coherent, not to prevent it from changing direction. If the interviewer redirects you to a failure case or a particular constraint, follow that thread and then connect it back to the larger design.
What about the six worked examples in the title?
The indexed preview of Shohruh Sharipov’s article identifies it as a five-step framework with six worked examples, but the article’s full text and the examples themselves are not available for verification here. The framework above is a general synthesis of established interview guidance; it does not identify or reproduce Sharipov’s six examples. Examples from other system-design guides should not be mistaken for his.
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