Universal standard for flow control across RxJS, Kafka, Node Streams

4 weeks ago 1

Universal Backpressure Protocol for Distributed Systems

Stop memory leaks. Stop crashes. Use one protocol everywhere.

Created by: Tryboy869 @ Nexus Studio 100

Every framework solves backpressure differently:

  • RxJS: throttle(), debounce(), custom backpressure
  • Kafka: fetch.max.bytes, fetch.min.bytes, configuration chaos
  • Node Streams: highWaterMark (magic number nobody understands)
  • Apache Spark: shuffle.spill, memoryFraction, configuration hell

Result: Memory leaks, crashes, and each developer learning 4 different solutions for the same problem.


Nexus Backpressure: One Protocol. Every Framework.

A universal, standardized protocol for coordinating flow control between producers and consumers in distributed systems.

// Producer asks: "How much can you take?" { "action": "CapacitySignal", "producer_id": "filebeat-1", "consumer_id": "elasticsearch", "requested_rate": 10000 } // Consumer responds: "I can take this much" { "action": "FlowControl", "consumer_id": "elasticsearch", "recommended_rate": 100, "backpressure_level": 2, "current_load": 95 }

Metric Before After Improvement
OOM Incidents 5-10/month 0/month -100%
Memory Usage 12GB avg 2GB avg -83%
P99 Latency 5000ms 150ms -97%
Uptime 99.5% 99.99% +0.49%
Data Loss 0.1-1% 0% -100%

Option 1: Use Reference Implementation

# Clone repo git clone https://github.com/Tryboy869/nexus-backpressure.git cd nexus-backpressure # Run Go implementation cd reference-implementations/go go run main.go # Server running on :8080

Option 2: Integrate with RxJS

cd integrations/rxjs npm install node example.ts

Option 3: Integrate with Kafka

cd integrations/kafka python example.py

Option 4: Kubernetes Deployment

cd integrations/kubernetes kubectl apply -f backpressure-controller.yaml

Before: 10,000 transactions/sec → Buffer fills → Crash After: Backpressure queues them gracefully, zero crashes

See: case-studies/stripe-like-payment-processor.md

Before: Logs → Filebeat → Elasticsearch (crashes, 90% logs lost) After: Backpressure controls flow, 100% logs arrive

See: case-studies/elasticsearch-log-pipeline.md

Before: A→B→C chain, C slows down → cascade failure After: Each service knows the limit, zero cascade failures

See: case-studies/microservices-chain.md



Reference Implementations

All implementations follow the same architecture (9 sections):

cd reference-implementations/go go run main.go --server
cd reference-implementations/python pip install -r requirements.txt python app.py --server
cd reference-implementations/node npm install npm start
cd reference-implementations/rust cargo run

  • RxJS - integrations/rxjs/
  • Kafka - integrations/kafka/
  • Node.js Streams - integrations/nodejs-streams/
  • Kubernetes - integrations/kubernetes/
  • Docker Compose - integrations/docker-compose/
  • Prometheus - integrations/prometheus/
  • Datadog - integrations/datadog/

Head-to-head comparisons:

  • vs RxJS: 3x fewer memory leaks, 50% less config
  • vs Kafka native: 10x simpler configuration
  • vs Node Streams: Zero buffer tuning needed

See: benchmarks/



We welcome contributions! See CONTRIBUTING.md

  1. Copy reference-implementations/go/main.go
  2. Keep identical 9-section architecture
  3. Port to your language
  4. Add tests in tests/integration/
  5. Submit PR

Open an issue: Issues


Apache License 2.0 - See LICENSE


  • Protocol specification
  • Reference implementations (Go, Python, Node, Rust)
  • Integration examples
  • v1.0 stable release (December 2025)
  • Enterprise support

Future Protocols (2026-2027)

  • Causality Tracking Protocol (Q1 2026) - Trace root cause
  • Degradation Protocol (Q2 2026) - Handle failures gracefully
  • Identity Protocol (Q3 2026) - Semantic IDs everywhere
  • Self-Healing Protocol (Q4 2026) - Auto-recovery

See ROADMAP.md for full vision 2025-2030.


Built by Tryboy869 at Nexus Studio 100

The protocol that changes distributed systems forever.


Want to use Nexus? Start with docs/GETTING_STARTED.md

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