Introduction

Modern enterprise systems — collaboration platforms, document management, CAD repositories and content delivery networks — need robust file synchronization that works at scale. Users expect near-real-time sync across many devices, efficient use of bandwidth, reliable version history, and safe conflict handling. A naive upload-everything approach soon breaks: it consumes bandwidth, increases storage cost and forces long sync delays.

This article describes a production-ready architecture and implementation patterns for a High-Scale File Sync Service that:

Examples and code snippets use Angular for the client and .NET (ASP.NET Core) for the backend. Diagrams follow the block-style format you chose.

Goals and Non-Goals

Goals

Non-Goals

High-Level Architecture

 ┌──────────────────────────────┐
 │       Angular Client(s)      │
 │ (Detect change, chunking,    │
 │  delta upload, conflict UI)  │
 └───────────────┬──────────────┘
                 │ HTTPS / WebSocket / SignalR
                 ▼
 ┌───────────────┴──────────────┐
 │      Sync Gateway API        │
 │  (auth, request validation,  │
 │   routing, tenant resolution)│
 └───────┬────────────┬─────────┘
         │            │
         │            ▼
         │     ┌──────────────┐
         │     │  Sync Engine │
         │     │ (delta, queue,│
         │     │  versioning)  │
         │     └────┬─────────┘
         │          │
 ┌───────▼──────┐ ┌─▼──────────┐
 │ Chunk Storage│ │ Metadata DB│
 │ (object store│ │ (versions,  │
 │  S3/Blob)    │ │  locks, refs)│
 └──────────────┘ └─────────────┘
         │                │
         ▼                ▼
    CDN / Edge /         Monitoring,
    Backup               Metrics, Audit

Core Components

1. Change Detector (Client Side)

Detect file changes using file system watchers or application-level events. For robust delta transfer, compute chunk-level hashes:

Client sends minimal metadata: file id (or path), file size, last-modified, chunkHashes, and root hash.

Why chunk hashing on client?

2. Delta Engine (Server Side)

Delta Engine determines which chunks are new and responds with an upload plan:

3. Chunk Storage / Blob Store

Store chunks in object store (S3, Azure Blob, GCS) using content-addressable keys: sha256(chunk) or fileId/version/chunkIndex. Content-addressable storage avoids duplication across tenants and versions.

Keep two stores conceptually:

4. Version Manager / Manifest

A version manifest records:

Manifest is small JSON; write it to metadata DB atomically once all missing chunks uploaded.

5. Conflict Resolver

If two clients modify the same base version concurrently:

Prefer preserving both versions rather than deleting or silently overwriting.

Chunking Strategies and Delta Algorithms

Fixed-size chunking

Rolling hash / Content-defined chunking

Binary diffs

Merkle Tree for Integrity

Protocol: Sync Session and APIs

Typical Sync Flow

  1. Client computes chunkHashes[] and requests POST /sync/plan with { fileId, size, chunkHashes, versionHint }.

  2. Server responds with { missingChunks[], uploadUrls[], targetManifestId }.

  3. Client uploads missing chunks directly to blob store using PUT to pre-signed URL.

  4. Client calls POST /sync/complete to signal all chunks uploaded; server validates chunks, writes manifest, and increments version.

  5. Server notifies other devices via WebSocket/SignalR push or by queued notification.

Example API Signatures (REST)

Design the APIs to be idempotent. PUT chunk can safely be retried.

.NET Backend Patterns

Metadata Model (SQL)

CREATE TABLE files (
  file_id UUID PRIMARY KEY,
  current_version UUID NULL,
  created_at timestamptz,
  tenant_id UUID
);

CREATE TABLE file_versions (
  version_id UUID PRIMARY KEY,
  file_id UUID REFERENCES files(file_id),
  parent_version UUID NULL,
  root_hash text NOT NULL,
  created_by UUID,
  created_at timestamptz DEFAULT now()
);

CREATE TABLE version_chunks (
  version_id UUID REFERENCES file_versions(version_id),
  chunk_index int,
  chunk_hash text,
  PRIMARY KEY(version_id, chunk_index)
);

Finalize Version (pseudo .NET)

public async Task FinalizeVersion(Guid fileId, Guid versionId, List<string> chunkHashes, Guid parentVersion)
{
    using var tx = await _db.BeginTransactionAsync();
    await _db.InsertFileVersion(versionId, fileId, parentVersion, ComputeRootHash(chunkHashes));
    for (int i=0;i<chunkHashes.Count;i++)
        await _db.InsertVersionChunk(versionId, i, chunkHashes[i]);
    await _db.UpdateFileCurrentVersion(fileId, versionId);
    await tx.CommitAsync();
}

Commit manifest atomically to prevent partial versions.

Chunk Uploading

Client (Angular) Implementation

Client Responsibilities

Example chunk hashing in Angular:

async function hashChunk(buffer: ArrayBuffer): Promise<string> {
  const hash = await crypto.subtle.digest('SHA-256', buffer);
  return Array.from(new Uint8Array(hash)).map(b => b.toString(16).padStart(2,'0')).join('');
}

Upload Manager

Offline Support and Resumability

Avoid recomputing full-file hashes frequently — cache chunk hashes for unchanged files.

Conflict Detection and UI

Security and Compliance

For BYOK-sensitive tenants, support client-side envelope encryption: client encrypts chunk payload with tenant key before upload; server stores ciphertext (server never holds raw key).

Scalability, Performance and Cost Optimizations

Garbage Collection & Retention

Monitoring, Observability and SLOs

Track:

Expose metrics to Prometheus and tracing via OpenTelemetry. Use traceId correlation for debugging complex sync flows.

Testing Strategy

Operational Playbook

Example End-to-End Scenario

User edits a 1 GB CAD file and changes a 5 MB subsection. Client detects changed chunks (say 2 chunks changed). Instead of uploading 1 GB, client will upload only those 2 chunks (~8 MB) plus a small manifest commit. Server composes new version by referencing existing chunks and new chunks. Other devices get notified and download only two chunks.

Summary

A high-scale file sync service must balance correctness, efficiency and usability. The architecture described provides:

Implement this with Angular for client hashing/upload orchestration and .NET for the Sync Gateway, metadata DB and background processes. Focus on idempotency, observability and security. Start with fixed-size chunking and add rolling chunk logic as you observe real workloads — that is often the fastest path to production.