Distributed File Storage


Difficulty	Advanced
Team Size	3-5 people
Time	~40-50 hours
Demo-ready by	Step 5
Prerequisites	Node.js or Go, networking, storage concepts
Built by	AWS S3, MinIO, Google Cloud Storage, Backblaze B2

Skills you'll earn: Object storage design, replication strategies, consistency models, multipart upload, metadata indexing

Start by uploading a file to a single server. End with an S3-like object storage system with replication, consistency guarantees, metadata management, and a REST API.

Step 1: Upload and download files via an API (~2-3 hours)

The simplest object store: files in, files out.

Build an HTTP API: PUT /objects/:key (upload), GET /objects/:key (download), DELETE /objects/:key
Store files on disk in a flat directory, keyed by a hash of the object key
Return proper content types and status codes
Use Express or Fastify

You now have: A single-node file server.

Step 2: Metadata management (~3-4 hours)

You need to know what's stored, how big it is, and when it was uploaded.

Store metadata per object: key, size, content type, created timestamp, checksum (SHA-256)
Use SQLite or PostgreSQL for the metadata store
GET /objects lists objects with pagination and prefix filtering
Verify checksums on upload and download to detect corruption

You now have: An object catalog.

Step 3: Chunking large files (~4-5 hours)

A 10GB file as a single blob is impractical to transfer and replicate.

Split uploads into fixed-size chunks (e.g., 8MB)
Store each chunk as a separate file on disk
Metadata tracks the ordered list of chunk IDs per object
Reassemble chunks on download, streaming to the client

You now have: Chunked storage.

Step 4: Replication across nodes (~4-5 hours)

One disk failure loses data permanently.

Run three storage nodes, each with its own disk
On upload, write each chunk to N nodes (replication factor)
Metadata tracks which nodes hold which chunks
On download, read from any node that has the chunk (prefer the closest/fastest)

You now have: Redundant storage.

Step 5: Consistency and repair (~4-5 hours)

Replicas can drift if a write fails on one node.

On read, compare checksums from multiple replicas (read repair)
Background process scans for under-replicated chunks and copies them to healthy nodes
Handle node failures: mark as unavailable, re-replicate its chunks to remaining nodes
Consistency model: read-after-write consistency for the uploading client

You now have: Self-healing storage.

Step 6: Buckets and access control (~4-5 hours)

Group objects into buckets (namespaces)
Per-bucket access policies: public-read, private, authenticated-read
Presigned URLs for time-limited access to private objects
API keys per user with bucket-level permissions

Step 7: Multipart uploads (~4-5 hours)

Client uploads chunks independently with upload IDs
Complete the upload by listing all parts
Abort incomplete uploads after a timeout
Enables resumable uploads over unreliable connections

Useful Resources

Where to go from here

Object versioning (keep previous versions, restore deleted objects)
Lifecycle policies (auto-delete after N days, move to cold storage)
Erasure coding (more storage-efficient than full replication)
CDN integration (cache popular objects at edge nodes)
Event notifications (trigger a webhook on upload/delete)

Distributed File Storage ​

Step 1: Upload and download files via an API (~2-3 hours) ​

Step 2: Metadata management (~3-4 hours) ​

Step 3: Chunking large files (~4-5 hours) ​

Step 4: Replication across nodes (~4-5 hours) ​

Step 5: Consistency and repair (~4-5 hours) ​

Step 6: Buckets and access control (~4-5 hours) ​

Step 7: Multipart uploads (~4-5 hours) ​

Useful Resources ​

Where to go from here ​