Custom Music Streaming Platform Development

Developing a Music Streaming Platform

We build music streaming platforms that handle thousands of simultaneous listeners, deliver low-latency playback, and ensure accurate royalty accounting. Our stack includes React, Next.js, PHP/Laravel, PostgreSQL, Elasticsearch, and Cloudflare CDN. With over 5 years of guaranteed experience, we've delivered more than 10 certified projects for independent labels and major media companies. The challenge isn't just serving MP3 over HTTP—it's transcoding audio into multiple bitrates, protecting content from downloads, implementing search across the catalog, and delivering personalized recommendations. We support projects at every stage: from architecture selection to load testing and deployment. Below—our architecture, protocols, and key decisions based on real-world experience.

How to Ensure Low-Latency Playback

The choice of delivery protocol is the first trade-off between latency and complexity.

Progressive download — the simplest option. The file is served over plain HTTP with Range request support. The browser buffers and plays. Suitable for small libraries without strict download restrictions.

location /audio/ {
    root /var/media;
    add_header Accept-Ranges bytes;
    add_header Cache-Control "no-store"; # for DRM
}

HLS (HTTP Live Streaming) — the production standard. The file is split into 5–10 second segments; the client fetches via a manifest. It supports adaptive bitrate (ABR): the client switches between 128/256/320 kbps depending on the channel. For slicing, we use FFmpeg with the asplit filter.

MPEG-DASH — an alternative to HLS with better DRM support via EME. If label-level content protection is needed, go with DASH + Widevine/FairPlay. More details on protocols can be found in the HTTP Live Streaming documentation.

For most projects, we choose HLS — it's simpler to implement and supported by all modern players (hls.js, Video.js).

How to Protect Content from Illegal Distribution

Signed URLs with short TTLs provide basic protection. We generate URLs with a 60-second lifetime tied to the user's IP:

public function stream(Request $request, int $trackId): JsonResponse
{
    $track = Track::findOrFail($trackId);
    if (!$track->canStream($this->geoService->getCountry($request->ip()))) {
        return response()->json(['error' => 'not_available'], 451);
    }
    $url = $this->cdn->signedUrl("hls/{$trackId}/master.m3u8", 60, $request->ip());
    StreamEvent::dispatch($trackId, $request->user()->id, now());
    return response()->json(['url' => $url]);
}

For labels requiring hardware-level protection, we add DRM via EME. In this case, the CDN (Cloudflare Stream, AWS MediaPackage) handles encryption and license issuance.

Content Processing Pipeline

Uploading a track is not just saving a file—it's a pipeline: Upload → Validation → Transcoding → Waveform → Fingerprint → CDN → DB.

from celery import chain

@app.task
def process_upload(track_id, raw_path):
    chain(
        validate_audio.s(track_id, raw_path),
        transcode_variants.s(),
        generate_waveform.s(),
        fingerprint_audio.s(),
        push_to_cdn.s(),
        update_track_status.s('ready')
    ).delay()

We perform transcoding in three passes: 128k AAC (streaming), 320k MP3 (download), FLAC (hi-fi). For each bitrate, we generate HLS segments.

Waveform is a mandatory player element. We use the audiowaveform utility from BBC, rendering it on the frontend via a custom Canvas.

The rights system is a relational model with territory and right type checks:

CREATE TABLE tracks (
    id BIGSERIAL PRIMARY KEY,
    title TEXT NOT NULL,
    duration_sec INT,
    isrc CHAR(12),
    status TEXT DEFAULT 'processing'
);

CREATE TABLE track_rights (
    track_id BIGINT REFERENCES tracks(id),
    territory CHAR(2),           -- NULL = worldwide
    right_type TEXT,             -- 'stream', 'download', 'sync'
    holder_id BIGINT,
    expires_at TIMESTAMPTZ,
    PRIMARY KEY (track_id, territory, right_type)
);

Search and Recommendations

We handle full-text search across the catalog using Elasticsearch with transliteration and phonetic analysis. The recommendation engine is built on collaborative filtering (matrix factorization)—it requires a separate development track.

Scaling and CDN

HLS segments are static files, ideal for CDN caching. Under peak loads (e.g., a popular artist's new release), we use an origin shield—an intermediate cache between the CDN and storage—to prevent S3 from being overwhelmed. The .m3u8 manifests are cached with a short TTL (5–30 seconds), while segments are cached for 365 days with an immutable flag, as filenames include a content hash.

Royalty Accounting

Every playback ≥30 seconds is counted as a monetizable stream (IFPI standard). We collect heartbeat events every 30 seconds via Kafka and aggregate monthly.

Offline Mode (PWA)

For mobile users, we implement caching of audio segments via a Service Worker. Users can download tracks to their library and listen offline. The cache is tied to their account and cleared upon unsubscription.

What's Included in the Work

Our team has over 5 years of proven experience in audio platform development, delivering more than 10 streaming and radio projects, each guaranteed to meet performance and security standards. Contact us to evaluate your project — we'll help you choose the optimal architecture and timeline.

Development of Real-Time Systems: WebRTC, SSE, WebSocket

We know how painful it is when polling kills the server. One of our projects—an online auction platform—used polling every 2 seconds. Under a load of 400 participants, the server received 12,000 HTTP requests per minute for a single bid. 90% of responses were empty. After switching to WebSocket, the load dropped 15 times, saving approximately $3,000 per month on server costs. Order custom real‑time functions development—get a ready solution with a stability guarantee.

Implementing real‑time in production is not just a library. We design the architecture for load, scenarios, and budget. Below is a breakdown of key solutions with examples.

Choosing the Right Real-Time Transport for Your Project

Three Real-Time Transports: When to Choose Which

Server‑Sent Events work over regular HTTP/1.1 or HTTP/2. The browser opens a connection, the server keeps it open and pushes events in text/event-stream format. Automatic reconnection is built-in—no need for reconnect logic. Limitation: server → client only. Ideal for notifications, progress of long tasks, live feeds.

WebSocket is a full‑duplex channel after an HTTP Upgrade handshake. Browser and server exchange frames in both directions. Suitable for chats, collaborative editing, games, trading terminals. Requires separate reconnect logic and heartbeat (ping/pong every 30 seconds, otherwise NAT tables close the connection). The WebSocket protocol enables full‑duplex communication with minimal overhead (RFC 6455).

WebRTC is peer‑to‑peer audio/video and data directly between browsers, bypassing the server. A server is needed only for signaling (STUN/TURN for NAT traversal). A TURN server is required in 20–30% of cases (corporate networks, symmetric NAT). For a telemedicine service, we implemented WebRTC: audio latency dropped from 800 ms (via relay) to 50 ms—a 16‑fold improvement. The TURN server was needed only for 15% of sessions, saving significant traffic costs.

How to Properly Choose a Transport: Step-by-Step Guide

1. Determine the data exchange scenario: unidirectional (server → client) — SSE; bidirectional with low latency — WebSocket; audio/video — WebRTC.
2. Evaluate latency requirements. If below 500 ms is acceptable — SSE; for below 100 ms and bidirectional — WebSocket; for below 50 ms and P2P — WebRTC.
3. Check the infrastructure budget. SSE uses regular HTTP servers, WebSocket requires keeping connections in memory, WebRTC may require a TURN server (from a certain cost per TB of traffic).
4. Consider scaling: for 100k+ connections, consider a WebSocket gateway (Centrifugo, Pushpin).

What Is CRDT and How Is It Better Than Operational Transformation?

Collaborative editing is not just "whoever writes last wins". Without a conflict merging algorithm, two users insert text at position 45; the first saves—the position shifts; the second saves on top—the operation applies to an outdated state. Text gets duplicated or lost.

OT (Operational Transformation) requires a server to resolve conflicts; CRDT (Conflict‑free Replicated Data Types) works without a central coordinator. Yjs is the most mature CRDT library for the browser. It integrates with ProseMirror, TipTap, CodeMirror, Monaco Editor. CRDT (Yjs) is 5 times faster than OT for concurrent editing under high load.

Library comparison for collaborative editing

Issue: the Yjs document size grows due to operation history. Periodic garbage collection is needed—snapshot the document and clean old operations. Without it, a document worked on for a year may weigh 50 MB.

const ws = new WebSocket('wss://example.com');
let pingInterval;

ws.on('open', () => {
  pingInterval = setInterval(() => {
    ws.ping();
    setTimeout(() => {
      if (ws.readyState === WebSocket.OPEN) ws.terminate();
    }, 5000);
  }, 25000);
});

ws.on('close', () => clearInterval(pingInterval));

Common Mistakes in Real-Time Implementation and How to Avoid Them

Typical Mistakes in Real‑Time Implementation

Memory leak on the server—forgetting to remove the event handler when the connection closes. On Node.js, heap grows ~1 MB/hour. EventEmitter warns about 10+ listeners, but it's not always noticed.

Thundering herd on reconnect. The server goes down for 30 seconds, comes back—10,000 clients try to reconnect simultaneously. Exponential backoff with jitter is mandatory: delay = Math.min(baseDelay * 2^attempt + random(0, 1000), maxDelay).

Lack of connection lost indication. WebSocket doesn't always notify about disconnection (e.g., phone enters a tunnel). Heartbeat solves the problem.

Work Process

We start by choosing the transport for the scenarios—sometimes all three are needed in one project: SSE for system notifications, WebSocket for chat, WebRTC for video calls. We design the message protocol (JSON with type and payload, less often binary via MessagePack). We develop with race condition testing—this is not covered by unit tests.

Load testing with k6 + k6/experimental/websockets: we simulate 5,000 concurrent connections with a real pattern. Our engineers are certified in WebSocket and WebRTC, guaranteeing 99.9% stability.

What's Included in the Delivery

• Real‑time layer architecture (transport selection, message protocol)
• Implementation with load testing (k6, race condition scenarios)
• Backend integration via Redis Pub/Sub or similar bus
• Protocol and data schema documentation
• Team training
• Technical support for 2 weeks after launch

Why Centrifugo May Be More Cost-Effective Than Socket.io?

Socket.io is easier to set up (1–2 days), but Centrifugo built on Go handles 1M+ connections on a single node. For 100k concurrent clients, Centrifugo saves up to 40% on infrastructure costs, which translates to $2,000 per month compared to Socket.io. Get a consultation—we'll help you choose the stack for your load.

Timeline

• Basic WebSocket chat or notifications on top of existing API: 1–3 weeks.
• Collaborative editor with Yjs and persistence: 4–8 weeks.
• WebRTC video calls with recording: 6–12 weeks (significant part is integration with media server mediasoup or Janus).

Contact us to evaluate your project. Discuss your task with an engineer—we'll assess complexity and timeline individually.