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Build a Resumable Upload Service

Resumable Upload Service — a complete walkthrough of large file upload, covering upload session, chunk receiver, offset tracker, and testing.

resumable_upload_service/
├── src/index.ts
├── src/upload-session.ts
├── src/chunk-receiver.ts
├── tests/resumable_upload_service.test.ts
└── package.json

// Upload session: large file upload core
export function uploadsession(input: UploadsessionInput): UploadsessionResult {
  // Build the upload session that anchors large file upload and defines the core data shape.
  return processUploadsession(input);
}

// Chunk receiver — handles large file upload Add the chunk receiver so
export class Chunkreceiver {
  constructor(private opts: ChunkreceiverOptions) {}
  async run(ctx: Context): Promise<ChunkreceiverOutput> {
    return this.execute(ctx);
  }
}

// Offset tracker: large file upload stage
export const offsettracker = (next: Next) => async (req: Request) => {
  const out = await transform(req);
  return next(out);
};

// Integrity checker for large file upload
export async function integritychecker(stream: AsyncIterable<Chunk>): Promise<Aggregate> {
  let acc = init();
  for await (const c of stream) acc = merge(acc, c);
  return acc;
}

// Completion assembler: large file upload finalization
export function completionassembler(state: State): Result {
  validate(state);
  return finalize(state);
}

Project overview

This project builds a large file upload system whose reason for existing is accepting chunked uploads that can resume after a network drop without re-sending completed chunks. The temptation in large file upload is to bolt the interesting part onto a working prototype and discover the hard cases in production; this build inverts that order and treats a client that resumes at the wrong offset after a partial write and corrupts the assembled file as the first thing designed, not the last.

You will implement Upload session, Chunk receiver, Offset tracker, Integrity checker, and Completion assembler, each as a module with one responsibility and a test that proves it in isolation. The large file upload pipeline is then the wiring that composes them, and the integration test is where the composition is shown to survive a client that resumes at the wrong offset after a partial write and corrupts the assembled file.

The walkthrough is written for a developer who has used a large file upload system but has not had to make one honest. It favors explicit data shapes over clever abstractions, and it names the failure each design choice prevents rather than presenting the choice as a style preference.

Each phase ends with something observable — a upload session that returns the right shape, a chunk receiver that rejects bad input, an integration test that goes green — so you can stop at any point and still have a large file upload system that works for the cases covered so far.

What you will build

The finished large file upload system exposes five capabilities, each with a focused test:

• Upload session
• Chunk receiver
• Offset tracker
• Integrity checker
• Completion assembler

Upload session is the foundation that every later stage assumes; Chunk receiver is where large file upload correctness lives; Offset tracker handles a client that resumes at the wrong offset after a partial write and corrupts the assembled file; Integrity checker makes the system observable; and Completion assembler is the graceful-degradation layer that keeps overload from becoming corruption.

The build keeps the large file upload logic in ordinary modules you can read in one sitting, and pulls in dependencies only for the parts that are genuinely tedious to hand-roll. That keeps the diff between the tutorial and a real codebase small, and keeps the failure modes visible in code rather than hidden behind a framework.

Architecture and data model

The system is organized around Upload session, Chunk receiver, and Offset tracker, with Integrity checker tying them together. Data flows as a session with a list of received chunk offsets and checksums, assembled into the final file only when every chunk is present.

Each component is a module with a pure interface where practical: the same input produces the same output, and side effects are pushed to the edges. That discipline is what makes the phases independently testable, because a test for Offset tracker does not need to stand up Upload session and Chunk receiver to exercise the interesting branch.

The data model is deliberately explicit. A session with a list of received chunk offsets and checksums, assembled into the final file only when every chunk is present Keeping the shape written down — in a schema, a type, or a fixture — means a change to the shape is a visible diff rather than a silent runtime shift, and it means the integration test can assert against a concrete shape instead of guessing.

Configuration and code are kept apart: the configuration says what large file upload should do, the modules say how. A reviewer can change a threshold or a policy without reading the implementation, which keeps the risky changes small and lets the diff stand as the review.

The failure path through Offset tracker is designed before the happy path is finished, because a client that resumes at the wrong offset after a partial write and corrupts the assembled file is the case that distinguishes a large file upload system from a demo. Every component declares what it does when its inputs are wrong, and the integration test asserts each of those declarations.

Prerequisites and dependencies

Have these ready before you install anything, so the large file upload setup is not blocked by a missing tool:

• Node.js 20 LTS or later
• Familiarity with large file upload fundamentals
• A local environment to run the test suite

The runtime dependencies are chosen to keep the large file upload datapath legible:

• fastify (^5.0.0) — Upload API
• blake3 (^0.2.0) — Chunk checksums
• lmdb (^3.2.0) — Chunk store

# setup for resumable-upload-service
pnpm init
pnpm add fastify blake3 lmdb
pnpm add -D typescript tsx vitest

Versions are pinned to a major range so the large file upload install is reproducible; commit the lockfile. The upload session reads its operational parameters from the environment and validates them at startup, so a missing value fails the boot rather than the first large file upload request.

Directory structure

Keep each large file upload component in its own file so it can be tested without starting the others:

resumable_upload_service/
├── src/index.ts
├── src/upload-session.ts
├── src/chunk-receiver.ts
├── tests/resumable_upload_service.test.ts
└── package.json

Phase 1: Upload session

Build the upload session that anchors large file upload and defines the core data shape.

// Upload session: large file upload core
export function uploadsession(input: UploadsessionInput): UploadsessionResult {
  // Build the upload session that anchors large file upload and defines the core data shape.
  return processUploadsession(input);
}

After this phase the upload session works in isolation and is covered by a unit test. The upload session defines the data shape that every later stage assumes, so getting it right first means the later phases compile against a stable contract.

Treat the upload session as the single source of truth for the large file upload data shape. Validate inputs at the boundary and reject early, so a malformed value never reaches Chunk receiver or Offset tracker where its effect would be harder to localize.

Phase 2: Chunk receiver

Add the chunk receiver so large file upload can accepting chunked uploads that correctly.

// Chunk receiver — handles large file upload Add the chunk receiver so
export class Chunkreceiver {
  constructor(private opts: ChunkreceiverOptions) {}
  async run(ctx: Context): Promise<ChunkreceiverOutput> {
    return this.execute(ctx);
  }
}

After this phase the chunk receiver works in isolation and is covered by a unit test. This is where large file upload correctness lives: the chunk receiver is what makes accepting chunked uploads that can resume after a network drop without re-sending completed chunks true, and its test is the proof.

Keep the chunk receiver pure where you can. A function that takes an input and returns an output is trivial to test and impossible to mock wrong; a class with hidden state is the opposite. Push side effects to the caller and keep the chunk receiver about the transformation.

Phase 3: Offset tracker

Wire the offset tracker to handle a client that resumes without losing data.

// Offset tracker: large file upload stage
export const offsettracker = (next: Next) => async (req: Request) => {
  const out = await transform(req);
  return next(out);
};

After this phase the offset tracker works in isolation and is covered by a unit test. The offset tracker is the difference between a large file upload system that works on the happy path and one that survives a client that resumes at the wrong offset after a partial write and corrupts the assembled file.

Design the failure before the success. Decide what offset tracker does when a client that resumes at the wrong offset after a partial write and corrupts the assembled file: reject, retry, shed, or degrade — and write that test first. A large file upload system whose failure behavior is unspecified will pick one at random under pressure, and it is usually the wrong one.

Phase 4: Integrity checker

Integrate the integrity checker to make large file upload observable and testable end to end.

// Integrity checker for large file upload
export async function integritychecker(stream: AsyncIterable<Chunk>): Promise<Aggregate> {
  let acc = init();
  for await (const c of stream) acc = merge(acc, c);
  return acc;
}

After this phase the integrity checker works in isolation and is covered by a unit test. Observability is not a finishing touch; it is how you know the large file upload system is doing what it claims in production.

Emit one structured event per meaningful action, with enough context to localize a failure without a second round-trip. The integrity checker is what turns “something is slow” into “the chunk receiver is slow for inputs matching this shape,” which is the difference between an alert and an investigation.

Phase 5: Completion assembler

Finalize the completion assembler so the large file upload system degrades gracefully under overload.

// Completion assembler: large file upload finalization
export function completionassembler(state: State): Result {
  validate(state);
  return finalize(state);
}

After this phase the completion assembler works in isolation and is covered by a unit test. The completion assembler is what keeps overload from becoming corruption: when the large file upload system is asked for more than it can do, it degrades in a defined way instead of failing in an undefined one.

Pick a degradation strategy for completion assembler — shed, queue, or backpressure — and make it explicit in code and in a test. Leaving the behavior to chance is how a large file upload traffic spike becomes a data loss incident.

Testing

Each phase has a focused test: upload session, chunk receiver, and offset tracker are exercised in isolation, then an integration test drives the full large file upload pipeline and asserts the a client that resumes case is handled.

Start with unit tests that pin each component’s contract: the upload session returns the documented shape, the chunk receiver transforms correctly, and the offset tracker fails in the documented way. These tests are fast and they localize regressions to the component that broke.

Then add an integration test that composes the components and drives a realistic large file upload scenario end to end. Assert the happy path first, then deliberately trigger a client that resumes at the wrong offset after a partial write and corrupts the assembled file and assert the system degrades rather than corrupts. Because the components are pure where practical, the integration test stays deterministic rather than flaky.

A large file upload suite must also prove the negative: bad input is rejected at the boundary, overload is shed rather than queued indefinitely, and a partial failure does not leave the system in an inconsistent state. These are the tests that catch the regressions a happy-path suite never would.

The entire large file upload suite runs with no external service; every dependency is either in-process or stubbed, so every case is reproducible in CI. That is what lets the offset tracker failure-mode assertions live as tests rather than as a manual checklist that drifts out of date.

# run the large file upload test suite
pnpm vitest run

Deployment and operations

Run at least two large file upload instances behind a load balancer and share state in Redis. Set resource limits so large file upload overload surfaces as backpressure rather than failure.

Run at least two stateless instances behind a load balancer, and move any shared state into a shared store so the large file upload behavior is global rather than per instance. Size limits so the system sheds load before it runs out of memory, because a large file upload system that OOMs under load fails in a way that is hard to reason about.

Drain on deploy: stop accepting new work, let in-flight large file upload operations finish, then exit. Because the system holds no state that cannot be reconstructed, a rollout is a matter of cycling instances one at a time while watching the error rate.

When a dependency is unavailable, decide explicitly whether the large file upload system fails closed or degrades. Leaving that choice to chance is how a dependency outage becomes a silent data loss, so make the choice visible in code and in a test.

Security considerations

Validate all large file upload inputs at the boundary, reject oversized payloads before buffering them, and keep secrets in the environment rather than the repository.

The large file upload system is a choke point, so it is the right place to reject malformed input before it reaches chunk receiver or offset tracker. Validate the shape and the size at the edge, and let the inner components assume what they receive is well-formed.

Never log secrets or full payloads; log enough to localize a failure without recording data that should not be on disk. Treat any external call as untrusted and validate its response before using it, because a large file upload system that trusts its inputs blindly is one malformed response away from corruption.

Keep dependencies pinned and run an audit in CI. A transitive dependency with a known vulnerability is still a vulnerability in your large file upload system, and the lockfile is what makes the audit meaningful.

Observability

Emit one structured event per large file upload operation with the inputs’ shape, the outcome, and a correlation id. Track error rate and latency per component and alert on a step change rather than a single spike.

The correlation id is the thread that ties a user-visible symptom to the large file upload decision and to the component log entry for the same operation. Without it, an investigation starts from a timestamp and a guess.

Watch the offset tracker failure rate separately from the overall error rate. A jump in offset tracker failures usually means a client that resumes at the wrong offset after a partial write and corrupts the assembled file, not a bug in chunk receiver, and the two have different owners and different fixes.

Chart the share of large file upload operations that shed, queue, or succeed. A change in the mix points at the cause faster than an aggregate latency can, because each class has a different root.

Troubleshooting

A client that resumes at the wrong offset after a partial write and corrupts the assembled file. Reproduce with a minimal fixture, then add a guard test so the large file upload system rejects the condition loudly.

Performance regresses under large file upload load. Profile with the sampling analyzer, locate the hot path in chunk receiver, and add a targeted benchmark to lock the regression.

Keep the large file upload dashboards separate from dependency dashboards. When an operation fails, the correlation id lets you decide in seconds whether the fault is upload session, chunk receiver, or offset tracker, instead of guessing from a timeout.

Limitations and next steps

• Single-region; multi-region replication is out of scope.
• The upload session is in-process and not horizontally shared by default.
• No auth layer; assume deployment behind an edge that enforces identity.

The large file upload system is single-region by design; extending to multi-region means making upload session shareable across regions, which is a real change to the consistency model rather than a config flag. The offset tracker is in-process, which is correct for one instance but must move to a shared store before scaling out.

There is no authentication or authorization layer; the system assumes it is deployed behind an edge that enforces identity. Adding one is straightforward but out of scope for this build, and doing it here would distract from the large file upload correctness that is the point.

The natural next step, once the large file upload pipeline is trusted in production, is to add a short-TTL cache for idempotent reads and a richer integrity checker that exports histograms rather than counters. Both are additive and neither changes the contracts this build establishes.