SSE Streaming Reliability Kit
Production-ready SSE toolkit with reconnection, exponential backoff, Last-Event-ID resume, heartbeat detection, and Prometheus-compatible observability.
Overview
A production-ready Server-Sent Events (SSE) reliability toolkit that solves the real-world problems of SSE at scale: dropped connections, duplicate messages, missed events after reconnect, and invisible stream failures. Zero runtime dependencies on the client.
The Problem
SSE is simple to implement but hard to make reliable. Buffering middleware drops events, load balancers kill idle connections, clients reconnect without knowing what they missed, and failures are invisible without instrumentation. Most implementations paper over these problems — this toolkit solves them properly.
What I Built
- 1Reconnection with exponential backoff and configurable jitter — prevents thundering herd when a server restarts.
- 2Gap-free resume via Last-Event-ID tracking with a server-side replay buffer — clients reconnecting after a drop receive every event they missed.
- 3Bounded LRU deduplication — guarantees each event ID is delivered exactly once, even across reconnects with overlapping replay windows.
- 4Heartbeat-based liveness detection — the client knows within seconds if the stream has gone silent, triggering reconnect before the user notices.
- 5Stream correlation IDs for distributed tracing — every event carries a trace ID so you can follow a stream across server restarts in your observability stack.
- 6Prometheus-compatible metrics with structured JSON logging — event counts, reconnect rates, buffer utilization, and liveness status all exposed as metrics.
- 7Pluggable storage layer — swap the in-memory event buffer for Redis or any persistent store without changing client code.
- 8Fault-injection test harness covering server restarts, dropped connections, and liveness recovery.
Key Technical Decisions
Zero-dependency client
The client library has zero runtime dependencies. It wraps the native EventSource API with a state machine that handles reconnection, deduplication, and liveness detection transparently.
Replay buffer with LRU eviction
The server maintains a bounded ring buffer of recent events. On reconnect, the client sends its last seen event ID and the server replays only the events it missed — no duplicates, no gaps.
Prometheus-compatible observability
Exposes metrics in the Prometheus text format so existing monitoring infrastructure can track stream health without custom instrumentation.
Outcome
A robust SSE toolkit demonstrating deep understanding of distributed systems failure modes, observability, and protocol-level reliability engineering.
What I Learned
The hardest problem was the replay + deduplication combination — getting the event ID windows right so a client that reconnects multiple times doesn't receive duplicates or miss events required careful state machine design.