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Before implementing a backend, sketch its boundary, the systems and people around it, the parts inside it, and one important interaction from request to response. Then draft the central API and data concepts and record decisions that would be costly to rediscover. A notebook or whiteboard is enough: the aim is to make assumptions visible, not to produce a large design document or prove that a design is correct.
What should you design before coding a backend?
Start with the questions that shape implementation: who needs the system, what outcome they need, what is outside its boundary, and which external services it relies on. Then sketch the deployable parts and data stores that matter, trace a representative request or event, and write down the API and data assumptions that affect behavior.
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The C4 model offers a vocabulary for this work: a system-context view shows the system and its relationships; a container view shows the applications and data stores within it. In C4, a “container” means an application or data-store boundary, not necessarily a Docker container. The model is intended for bespoke software and can describe monolithic as well as distributed systems.
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1. State the problem and draw the boundary
Write a brief statement of who needs the backend and what they need to accomplish. Note what is out of scope, then list the people or roles and external systems that interact with it. Draw a box around the system being designed and label each relationship so its meaning is clear; an unlabeled arrow can conceal an important assumption about who initiates an action or what information moves.
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2. Sketch the applications and data stores
Inside the system boundary, draw the applications and data stores relevant to the proposed design. Name technologies only when they are known or materially affect a decision. This view should show meaningful boundaries and responsibilities, not every class, table, or implementation detail.
C4 organizes its views from software system to container, component, and code. Teams do not need every level: its guidance says context and container diagrams are sufficient for most software development teams. Add a component or code-level view only when a specific design question, risky change, or onboarding need warrants the extra detail. Other supporting views include system landscape, dynamic, and deployment diagrams.
3. Trace one important request or event
Choose a representative interaction and follow it through the backend: caller, API boundary, internal responsibility, persistence or external dependency, and response or side effect. Label the arrows with the action or information exchanged. A dynamic diagram can help communicate this flow, but no particular sequence-diagram notation is required for a useful sketch.
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4. Draft the API contract
For the central interactions, list operations, inputs, outputs, and expected error cases. This forces questions about behavior to surface before callers and implementation depend on different assumptions.
For HTTP APIs, an OpenAPI document provides a language-agnostic description of the interface. The specification is intended to help people and tools discover and understand an API; it can be used by documentation, code-generation, and testing tools. Choose a version compatible with the team’s tooling. The OpenAPI Initiative’s v3.0.4 specification is dated 2024-10-24, but that version is not a recommendation to use it in every project: check the official specification and your tools when choosing a version: OpenAPI Specification v3.0.4.
5. Sketch the core data concepts
List the important entities or records, their relationships, who owns them, and the lifecycle questions that affect API behavior. Ask what is created, updated, retained, or removed and which responsibility is authoritative for each piece of data. Treat this as a way to expose assumptions, not as a prescribed schema notation or a reason to choose a particular database.
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6. Record consequential decisions
When a choice will affect architecture or be expensive to revisit, capture its context, the decision, and its consequences in an architectural decision record (ADR). Examples include where a responsibility belongs, whether to rely on a managed dependency, or what consistency an API promises. AWS Prescriptive Guidance defines an ADR as “a document that describes a choice the team makes about a significant aspect of the software architecture they’re planning to build.” Its guidance treats accepted records as immutable; when new information warrants a change, a later decision supersedes the earlier one. See AWS Prescriptive Guidance: Architectural decision record process.
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Use the diagrams and notes to ask concrete questions, rather than treating a tidy picture as proof of correctness:
- Can each actor achieve the intended outcome?
- Are dependencies and data ownership visible?
- What happens when a dependency fails, a request is repeated, or a retry occurs?
- Do deployment, security, observability, or operational responsibilities need a closer view?
C4 describes diagrams as useful for communication, architecture review, risk identification, and threat modeling. Those are reasons to inspect a design together, not guarantees that a sketch will prevent defects.
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How much detail is enough?
Make each diagram answer one question. A context view can clarify who and what the backend interacts with; a container view can show its important applications and data stores; a dynamic view can explain a selected interaction. Trying to show every concern in one drawing makes boundaries and flows harder to read.
Start with context and container views, then zoom in only where the design needs it. C4 is one useful vocabulary, not a requirement to adopt a particular architecture style or notation. Its FAQ identifies embedded firmware and heavily customized packaged products as less suitable cases; for other systems, use the views that help the people involved understand the design.
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What a paper design can—and cannot—tell you
A sketch can reveal missing actors, ambiguous boundaries, unexamined dependencies, unclear API behavior, and decisions whose consequences deserve discussion. It gives a team something concrete to review before those assumptions are embedded in code.
It cannot establish that the design is correct, that implementation will be faster, or that defects will be prevented. Keep it lightweight and revise it when evidence or requirements change. The useful result is not a polished document; it is a clearer set of responsibilities, interactions, contracts, and open decisions before implementation begins.
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