Architectural Invariant Design: Bun 1.2 Native WebSocket Backpressure and TCP Drain Invariant
Bun 1.2 Native WebSocket Backpressure and TCP Drain Invariant defines an industrial-grade behavioral standard for backend engineering. Enforces deterministic backpressure handling in Bun 1.2 native WebSocket servers by evaluating the integer byte return value of `ws.send()`. Failure to inspect send results or handle socket buffer saturation causes silent, unbounded heap accumulation during high-fanout broadcasts, leading to catastrophic OOM termination under slow client conditions. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | Ignoring `ws.send()` return codes and lacking `drain()` handler causing silent unbounded queue buffering | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
Engineers MUST ALWAYS inspect the integer return value of `ws.send(data)` to determine the bytes enqueued or if the frame was dropped (return value <= 0).
Engineers MUST ALWAYS inspect the integer return value of `ws.send(data)` to determine the bytes enqueued or if the frame was dropped (return value <= 0).
Engineers MUST NOT invoke `server.publish()` or `ws.send()` in unbounded loops without backpressure thresholds and slow-client disconnection or queue-eviction strategies.
Engineers MUST NOT invoke `server.publish()` or `ws.send()` in unbounded loops without backpressure thresholds and slow-client disconnection or queue-eviction strategies.
Services MUST define the native `drain(ws)` hook in `Bun.serve({ websocket
Services MUST define the native `drain(ws)` hook in `Bun.serve({ websocket: { drain(ws) { ... } } })` to resume queued streaming once the kernel/uSockets write buffer clears.
Engineers MUST track pending client backpressure using `ws.data` context, setting a maximum buffer threshold (`maxBackpressureBytes`) before disconnecting misbehaving slow consumers.
Engineers MUST track pending client backpressure using `ws.data` context, setting a maximum buffer threshold (`maxBackpressureBytes`) before disconnecting misbehaving slow consumers.
Engineers MUST NEVER assume `server.publish()` inherently handles per-client slow-drain eviction
Engineers MUST NEVER assume `server.publish()` inherently handles per-client slow-drain eviction; topic subscribers experiencing backpressure must be isolated or shed.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Bun 1.2 Native WebSocket Backpressure and TCP Drain Invariant critical for AI coding assistants?
Enforces deterministic backpressure handling in Bun 1.2 native WebSocket servers by evaluating the integer byte return value of `ws.send()`. Failure to inspect send results or handle socket buffer saturation causes silent, unbounded heap accumulation during high-fanout broadcasts, leading to catastrophic OOM termination under slow client conditions. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (Ignoring `ws.send()` return codes and lacking `drain()` handler causing silent unbounded queue buffering) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.