ampy-bus 1.0.6

Transport-agnostic messaging conventions & helpers for AmpyFin

ampy-bus — Transport-Agnostic Messaging for Trading Systems

Transport-agnostic messaging conventions and helpers for AmpyFin trading systems. Standardize topics, headers, QoS, replay, and observability across NATS and Kafka with consistent ampy-proto payloads.

🚀 Quick Start

# Install Go CLI tools
make build

# Install Python package
pip install -e .[nats]

# Start NATS server with JetStream (REQUIRED)
docker run -d --name nats -p 4222:4222 nats:2.10 -js

# Publish a message (NATS)
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

# Subscribe to messages
./ampybusctl sub --subject "ampy.prod.bars.v1.>"

# Kafka alternative
./kafkabusctl pub-empty --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

⚠️ CRITICAL: NATS JetStream Requirement

ampy-bus requires NATS with JetStream enabled for all NATS-based operations. Without JetStream, you'll encounter errors like:

Failed to ensure stream: nats: no responders available for request

Quick NATS Setup

Option 1: Docker (Recommended)

# Start NATS with JetStream enabled (REQUIRED)
docker run -d --name nats -p 4222:4222 nats:2.10 -js

# Verify JetStream is running (check logs)
docker logs nats | grep "Starting JetStream"

Option 2: Local Installation

# Install NATS server
brew install nats-server  # macOS
# or download from https://github.com/nats-io/nats-server/releases

# Start NATS with JetStream enabled (REQUIRED)
nats-server -js

# Verify JetStream is running (you should see "Starting JetStream" in the logs)

Option 3: Using the CLI

# Start with JetStream and other options
nats-server -js --store_dir /tmp/nats/jetstream --max_memory_store 1GB

Note: The -js flag is essential. Without it, ampy-bus operations will fail.

Troubleshooting JetStream Issues

Common Error Messages:

# Error: No JetStream enabled
Failed to ensure stream: nats: no responders available for request

# Error: JetStream not ready
nats: context deadline exceeded

Solutions:

1. Verify JetStream is enabled: Check logs for "Starting JetStream"
2. Wait for startup: JetStream takes a few seconds to initialize
3. Check port: Ensure NATS is running on port 4222
4. Restart with JetStream: Stop and restart with -js flag

Verification Commands:

# Check if JetStream is running
docker logs nats | grep "Starting JetStream"

# Test connection
nats server info

# List JetStream streams (if available)
nats stream list

🎯 What Problem Does This Solve?

Trading systems need reliable, auditable messaging but teams often end up with:

• Schema drift between services using different message formats
• Inconsistent delivery semantics (ordering, retries, dead letter queues)
• Poor replayability for research, backtesting, and compliance audits
• Transport lock-in (Kafka vs NATS) preventing system evolution
• Scattered observability with different metrics/logging per service

ampy-bus solves this by providing:

• ✅ Transport-agnostic contracts - same code works on NATS or Kafka
• ✅ Standardized envelopes with required headers for lineage and observability
• ✅ Domain-specific ordering and partitioning strategies
• ✅ Built-in DLQ, replay, and retry semantics
• ✅ Consistent observability with metrics, tracing, and structured logging

📦 Installation

Prerequisites

• Go 1.23+ (for CLI tools and Go libraries)
• Python 3.8+ (for Python libraries and examples)
• NATS Server or Kafka/Redpanda (messaging broker)

Go Installation

# Clone the repository
git clone https://github.com/AmpyFin/ampy-bus.git
cd ampy-bus

# Build CLI tools
make build

# This creates:
# - ./ampybusctl (NATS CLI)
# - ./kafkabusctl (Kafka CLI) 
# - ./kafkainspect (Kafka inspection)
# - ./kafkapoison (DLQ testing)

Python Installation

From PyPI (Recommended):

# Install core package
pip install ampy-bus

# Install with NATS support (includes nats-py, OpenTelemetry, etc.)
pip install ampy-bus[nats]

# Install development dependencies
pip install ampy-bus[dev]

From Source:

# Clone and install
git clone https://github.com/AmpyFin/ampy-bus.git
cd ampy-bus

# Install core package
pip install -e .

# Install with NATS support (includes nats-py, OpenTelemetry, etc.)
pip install -e .[nats]

# Install development dependencies
pip install -e .[dev]

Verify Installation:

python -c "import ampybus; print(f'ampy-bus version: {ampybus.__version__}')"

Docker Setup (Optional)

# Start NATS server with JetStream (REQUIRED for ampy-bus)
docker run -d --name nats -p 4222:4222 nats:2.10 -js

# Start Redpanda (Kafka-compatible)
docker run -d --name redpanda -p 9092:9092 -p 9644:9644 \
  redpandadata/redpanda:latest \
  redpanda start --overprovisioned --smp 1 --memory 1G

🛠️ CLI Tools

ampybusctl (NATS)

Main CLI for NATS-based messaging operations:

# Publish empty message (for testing)
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

# Subscribe to messages
./ampybusctl sub --subject "ampy.prod.bars.v1.>"

# Subscribe with durable consumer
./ampybusctl sub --subject "ampy.prod.bars.v1.>" --durable my-consumer

# DLQ operations
./ampybusctl dlq-inspect --subject "ampy.prod.dlq.v1.>" --max 10 --decode
./ampybusctl dlq-redrive --subject "ampy.prod.dlq.v1.>" --max 5

# Performance testing
./ampybusctl bench-pub --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer bench@test --source bench --pk XNAS.AAPL --count 1000

# Replay messages
./ampybusctl replay --env prod --domain bars --version v1 --subtopic XNAS.AAPL \
  --start 2025-01-01T00:00:00Z --end 2025-01-01T01:00:00Z --reason "backtest"

# Validate fixtures
./ampybusctl validate-fixture --file examples/bars_v1_XNAS_AAPL.json

kafkabusctl (Kafka)

Kafka-specific operations:

# Create topic
./kafkabusctl ensure-topic --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --partitions 3

# Publish message
./kafkabusctl pub-empty --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

# Subscribe to topic
./kafkabusctl sub --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --group cli-consumer

kafkainspect

Inspect Kafka topics and messages:

# List topics
./kafkainspect list-topics --brokers 127.0.0.1:9092

# Inspect topic details
./kafkainspect describe-topic --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL

# Consume and decode messages
./kafkainspect consume --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --max 10 --decode

kafkapoison

Generate poison messages for DLQ testing:

# Send poison message (will trigger DLQ)
./kafkapoison --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer poison@cli --source poison-test --pk XNAS.AAPL

📚 Complete Examples & Use Cases

🏗️ Available Examples

The repository includes comprehensive examples for all major use cases:

Go Examples:

• examples/go/simple_roundtrip/main.go - Basic pub/sub with NATS
• examples/go/nats_pubsub/main.go - Advanced NATS pub/sub patterns
• examples/go/replayer/main.go - Message replay functionality

Python Examples:

• python/examples/simple_roundtrip.py - Basic async pub/sub
• python/examples/py_nats_pub.py - Publisher example
• python/examples/py_nats_sub.py - Subscriber example
• python/examples/py_dlq_inspect.py - DLQ inspection
• python/examples/py_dlq_redrive.py - DLQ message redrive
• python/examples/py_send_poison.py - Poison message testing

Message Examples:

• examples/bars_v1_XNAS_AAPL.json - OHLCV bar data
• examples/ticks_v1_trade_MSFT.json - Trade tick data
• examples/news_v1_raw.json - News article data
• examples/signals_v1_hyper_NVDA.json - ML trading signals
• examples/orders_v1_request.json - Order request data
• examples/fills_v1_event.json - Fill event data
• examples/positions_v1_snapshot.json - Position snapshot
• examples/fx_v1_USD_JPY.json - FX rate data
• examples/metrics_v1_oms_order_rejects.json - System metrics
• examples/dlq_v1_bars.json - Dead letter queue example
• examples/control_v1_replay_request.json - Replay control message

🚀 Basic Pub/Sub Examples

Go Example:

// examples/go/simple_roundtrip/main.go
package main

import (
    "context"
    "fmt"
    "github.com/AmpyFin/ampy-bus/pkg/ampybus"
    "github.com/AmpyFin/ampy-bus/pkg/ampybus/natsbinding"
)

func main() {
    // Connect to NATS
    cfg := natsbinding.Config{URL: "nats://localhost:4222"}
    bus, _ := natsbinding.Connect(cfg)
    defer bus.Close()

    // Publish message
    headers := ampybus.NewHeaders("ampy.bars.v1.BarBatch", "test-producer", "test-source", "XNAS.AAPL")
    bus.Publish(context.Background(), "ampy.prod.bars.v1.XNAS.AAPL", headers, []byte("payload"))

    // Subscribe to messages
    bus.Subscribe("ampy.prod.bars.v1.>", func(msg *ampybus.Message) {
        fmt.Printf("Received: %s\n", msg.Headers.MessageID)
    })
}

Python Example:

# python/examples/simple_roundtrip.py
import asyncio
from ampybus import nats_bus

async def main():
    # Connect to NATS
    bus = nats_bus.NatsBus("nats://localhost:4222")
    await bus.connect()

    # Publish message
    headers = {
        "message_id": "018f5e2f-9b1c-76aa-8f7a-3b1d8f3ea0c2",
        "schema_fqdn": "ampy.bars.v1.BarBatch",
        "producer": "test-producer",
        "source": "test-source",
        "partition_key": "XNAS.AAPL"
    }
    await bus.publish("ampy.prod.bars.v1.XNAS.AAPL", headers, b"payload")

    # Subscribe to messages
    async def handler(msg):
        print(f"Received: {msg.headers['message_id']}")
    
    await bus.subscribe("ampy.prod.bars.v1.>", handler)

asyncio.run(main())

📊 Market Data Examples

OHLCV Bars:

# Publish bar data
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

# Subscribe to all bar data
./ampybusctl sub --subject "ampy.prod.bars.v1.>"

Trade Ticks:

# Publish tick data
./ampybusctl pub-empty --topic ampy.prod.ticks.v1.trade.MSFT \
  --producer databento-cpp@tick-1 --source databento-cpp --pk MSFT.XNAS

# Subscribe to trade ticks
./ampybusctl sub --subject "ampy.prod.ticks.v1.trade.>"

FX Rates:

# Publish FX data
./ampybusctl pub-empty --topic ampy.prod.fx.v1.USD.JPY \
  --producer oanda-api@fx-1 --source oanda-api --pk USD.JPY

🤖 Trading System Examples

ML Signals:

# Publish trading signals
./ampybusctl pub-empty --topic ampy.prod.signals.v1.hyper@2025-01-01 \
  --producer ampy-model@mdl-1 --source ampy-model --pk hyper@2025-01-01|NVDA.XNAS

Order Management:

# Publish order requests
./ampybusctl pub-empty --topic ampy.prod.orders.v1.requests \
  --producer ampy-oms@oms-1 --source ampy-oms --pk co_20250101_001

# Publish fill events
./ampybusctl pub-empty --topic ampy.prod.fills.v1.events \
  --producer ampy-oms@oms-1 --source ampy-oms --pk fill_20250101_001

Position Tracking:

# Publish position snapshots
./ampybusctl pub-empty --topic ampy.prod.positions.v1.snapshots \
  --producer ampy-oms@oms-1 --source ampy-oms --pk portfolio_20250101

📰 News & Information Examples

News Articles:

# Publish news data
./ampybusctl pub-empty --topic ampy.prod.news.v1.raw \
  --producer news-scraper@news-1 --source news-scraper --pk news_20250101_001

System Metrics:

# Publish system metrics
./ampybusctl pub-empty --topic ampy.prod.metrics.v1.ampy-oms \
  --producer ampy-oms@oms-1 --source ampy-oms --pk metrics_20250101

Dead Letter Queue (DLQ) Handling

# Send a poison message (will fail to decode)
./kafkapoison --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer poison@test --source poison-test --pk XNAS.AAPL

# Inspect DLQ messages
./ampybusctl dlq-inspect --subject "ampy.prod.dlq.v1.>" --max 5 --decode --outdir ./dlq_dump

# Redrive messages from DLQ (after fixing the issue)
./ampybusctl dlq-redrive --subject "ampy.prod.dlq.v1.>" --max 5

Message Replay

# Replay bars data for backtesting
./ampybusctl replay --env prod --domain bars --version v1 --subtopic XNAS.AAPL \
  --start 2025-01-01T09:30:00Z --end 2025-01-01T16:00:00Z \
  --reason "backtest-2025-01-01"

# Replay with custom subject pattern
./ampybusctl replay --subject "ampy.prod.ticks.v1.trade.>" \
  --start 2025-01-01T09:30:00Z --end 2025-01-01T10:00:00Z \
  --reason "tick-analysis"

Performance Testing

# Benchmark publishing performance
./ampybusctl bench-pub --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer bench@test --source bench --pk XNAS.AAPL --count 10000

# Output: Published 10000 messages in 2.3s (4347.8 msg/s)

Topic Patterns & Domains

# Market data topics
ampy.prod.bars.v1.XNAS.AAPL      # OHLCV bars
ampy.prod.ticks.v1.trade.MSFT    # Trade ticks
ampy.prod.ticks.v1.quote.AAPL    # Quote ticks

# News & signals
ampy.prod.news.v1.raw            # Raw news items
ampy.prod.signals.v1.hyper@2025-01-01  # ML signals

# Trading operations
ampy.prod.orders.v1.requests     # Order requests
ampy.prod.fills.v1.events        # Fill events
ampy.prod.positions.v1.snapshots # Position snapshots

# System monitoring
ampy.prod.metrics.v1.ampy-oms    # Service metrics
ampy.prod.dlq.v1.bars            # Dead letter queue

Connection Options

# NATS with authentication
./ampybusctl sub --subject "ampy.prod.bars.v1.>" \
  --nats nats://localhost:4222 \
  --user myuser --pass mypass

# NATS with TLS
./ampybusctl sub --subject "ampy.prod.bars.v1.>" \
  --nats tls://localhost:4222 \
  --tls-ca ca.pem --tls-cert client-cert.pem --tls-key client-key.pem

# Kafka with SASL
./kafkabusctl sub --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --group my-consumer

Python Integration

# Install with NATS support
pip install -e .[nats]

# Use in your application
from ampybus import nats_bus, envelope

# Create properly formatted envelope
env = envelope.Envelope(
    message_id="018f5e2f-9b1c-76aa-8f7a-3b1d8f3ea0c2",
    schema_fqdn="ampy.bars.v1.BarBatch",
    producer="my-service@host-1",
    source="my-service",
    partition_key="XNAS.AAPL"
)

# Connect and publish
bus = nats_bus.NatsBus("nats://localhost:4222")
await bus.connect()
await bus.publish("ampy.prod.bars.v1.XNAS.AAPL", env.headers, protobuf_data)

🚀 Quick Start Guide

1. Start a Message Broker

Option A: NATS (Recommended for development)

docker run -d --name nats -p 4222:4222 nats:2.10 -js

Option B: Kafka/Redpanda

docker run -d --name redpanda -p 9092:9092 -p 9644:9644 \
  docker.redpanda.com/redpanda/redpanda:latest \
  redpanda start --overprovisioned --smp 1 --memory 1G

2. Build and Test CLI Tools

# Build all CLI tools
make build

# Test basic pub/sub (NATS)
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer test@cli --source test --pk XNAS.AAPL

# In another terminal, subscribe
./ampybusctl sub --subject "ampy.prod.bars.v1.>"

3. Try Python Integration

# Install Python package
pip install -e .[nats]

# Run Python example
python python/examples/simple_roundtrip.py

🎯 Real-World Use Cases

📈 Market Data Ingestion & Distribution

Multi-Source Data Aggregation:

# Ingest from multiple sources
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@ingest-1 --source yfinance-go --pk XNAS.AAPL

./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer alpha-vantage@ingest-2 --source alpha-vantage --pk XNAS.AAPL

# High-frequency tick data
./ampybusctl pub-empty --topic ampy.prod.ticks.v1.trade.MSFT \
  --producer databento-cpp@tick-1 --source databento-cpp --pk MSFT.XNAS

# FX rates
./ampybusctl pub-empty --topic ampy.prod.fx.v1.USD.JPY \
  --producer oanda-api@fx-1 --source oanda-api --pk USD.JPY

Real-Time Data Distribution:

# Multiple consumers can subscribe to the same data
./ampybusctl sub --subject "ampy.prod.bars.v1.>" --durable market-data-consumer
./ampybusctl sub --subject "ampy.prod.ticks.v1.trade.>" --durable tick-processor
./ampybusctl sub --subject "ampy.prod.fx.v1.>" --durable fx-monitor

🤖 Trading System Integration

ML Signal Generation & Distribution:

# Publish ML trading signals
./ampybusctl pub-empty --topic ampy.prod.signals.v1.hyper@2025-01-01 \
  --producer ampy-model@mdl-1 --source ampy-model --pk hyper@2025-01-01|NVDA.XNAS

# Subscribe to signals for trading
./ampybusctl sub --subject "ampy.prod.signals.v1.>" --durable signal-processor

Order Management System:

# Publish order requests
./ampybusctl pub-empty --topic ampy.prod.orders.v1.requests \
  --producer ampy-oms@oms-1 --source ampy-oms --pk co_20250101_001

# Publish fill events
./ampybusctl pub-empty --topic ampy.prod.fills.v1.events \
  --producer ampy-oms@oms-1 --source ampy-oms --pk fill_20250101_001

# Subscribe to order events
./ampybusctl sub --subject "ampy.prod.orders.v1.>" --durable order-tracker
./ampybusctl sub --subject "ampy.prod.fills.v1.>" --durable fill-processor

Position & Risk Management:

# Publish position snapshots
./ampybusctl pub-empty --topic ampy.prod.positions.v1.snapshots \
  --producer ampy-oms@oms-1 --source ampy-oms --pk portfolio_20250101

# Subscribe for risk monitoring
./ampybusctl sub --subject "ampy.prod.positions.v1.>" --durable risk-monitor

📰 News & Information Processing

News Ingestion & NLP:

# Raw news ingestion
./ampybusctl pub-empty --topic ampy.prod.news.v1.raw \
  --producer news-scraper@news-1 --source news-scraper --pk news_20250101_001

# Processed news (after NLP)
./ampybusctl pub-empty --topic ampy.prod.news.v1.nlp \
  --producer nlp-processor@nlp-1 --source nlp-processor --pk news_20250101_001

# Subscribe to news for sentiment analysis
./ampybusctl sub --subject "ampy.prod.news.v1.>" --durable sentiment-analyzer

🔍 Monitoring & Observability

System Health Monitoring:

# Publish system metrics
./ampybusctl pub-empty --topic ampy.prod.metrics.v1.ampy-oms \
  --producer ampy-oms@oms-1 --source ampy-oms --pk metrics_20250101

# Subscribe to metrics for monitoring
./ampybusctl sub --subject "ampy.prod.metrics.v1.>" --durable metrics-collector

Error Handling & DLQ Management:

# Monitor DLQ for issues
./ampybusctl dlq-inspect --subject "ampy.prod.dlq.v1.>" --max 10 --decode

# Redrive messages after fixing issues
./ampybusctl dlq-redrive --subject "ampy.prod.dlq.v1.>" --max 5

🔬 Backtesting & Research

Historical Data Replay:

# Replay bars data for backtesting
./ampybusctl replay --env prod --domain bars --version v1 --subtopic XNAS.AAPL \
  --start 2025-01-01T09:30:00Z --end 2025-01-01T16:00:00Z \
  --reason "backtest-2025-01-01"

# Replay tick data for analysis
./ampybusctl replay --subject "ampy.prod.ticks.v1.trade.>" \
  --start 2025-01-01T09:30:00Z --end 2025-01-01T10:00:00Z \
  --reason "tick-analysis"

# Replay news data for sentiment backtesting
./ampybusctl replay --subject "ampy.prod.news.v1.>" \
  --start 2025-01-01T00:00:00Z --end 2025-01-01T23:59:59Z \
  --reason "news-sentiment-backtest"

🏢 Enterprise Use Cases

Multi-Environment Deployment:

# Development environment
./ampybusctl pub-empty --topic ampy.dev.bars.v1.XNAS.AAPL \
  --producer test@dev --source test --pk XNAS.AAPL

# Paper trading environment
./ampybusctl pub-empty --topic ampy.paper.orders.v1.requests \
  --producer paper-oms@paper-1 --source paper-oms --pk paper_order_001

# Production environment
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer yfinance-go@prod-1 --source yfinance-go --pk XNAS.AAPL

Compliance & Audit:

# Replay all trading activity for audit
./ampybusctl replay --subject "ampy.prod.orders.v1.>" \
  --start 2025-01-01T00:00:00Z --end 2025-01-31T23:59:59Z \
  --reason "monthly-audit-2025-01"

# Replay all fills for reconciliation
./ampybusctl replay --subject "ampy.prod.fills.v1.>" \
  --start 2025-01-01T00:00:00Z --end 2025-01-31T23:59:59Z \
  --reason "fills-reconciliation-2025-01"

🧪 Development & Testing Examples

Performance Testing:

# Benchmark publishing performance
./ampybusctl bench-pub --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer bench@test --source bench --pk XNAS.AAPL --count 1000

# Benchmark with Go
go run cmd/benchkafka/main.go --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --count 10000

# Benchmark with NATS
go run cmd/benchnats/main.go --subject ampy.prod.bars.v1.XNAS.AAPL \
  --count 10000 --nats nats://127.0.0.1:4222

DLQ Testing:

# Send poison message (will trigger DLQ)
./kafkapoison --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer poison@test --source poison-test --pk XNAS.AAPL

# Or use Python
python python/examples/py_send_poison.py

# Inspect DLQ messages
./ampybusctl dlq-inspect --subject "ampy.prod.dlq.v1.>" --max 5 --decode

# Or use Python
python python/examples/py_dlq_inspect.py

# Redrive messages from DLQ
./ampybusctl dlq-redrive --subject "ampy.prod.dlq.v1.>" --max 5

# Or use Python
python python/examples/py_dlq_redrive.py

Message Validation:

# Validate message fixtures
./ampybusctl validate-fixture --file examples/bars_v1_XNAS_AAPL.json
./ampybusctl validate-fixture --file examples/ticks_v1_trade_MSFT.json
./ampybusctl validate-fixture --file examples/news_v1_raw.json

# Validate all fixtures in directory
./ampybusctl validate-fixture --dir examples/

🎯 Running All Examples

1. Start Required Services:

# Start NATS with JetStream (REQUIRED for ampy-bus)
docker run -d --name nats -p 4222:4222 nats:2.10 -js

# Start Redpanda (Kafka-compatible)
docker run -d --name redpanda -p 9092:9092 -p 9644:9644 \
  redpandadata/redpanda:latest redpanda start --overprovisioned --smp 1 --memory 1G

2. Build All Tools:

make build

3. Run Go Examples:

# Basic roundtrip
go run examples/go/simple_roundtrip/main.go

# Advanced NATS pub/sub
go run examples/go/nats_pubsub/main.go

# Message replayer
go run examples/go/replayer/main.go

4. Run Python Examples:

# Install Python package
pip install -e .[nats]

# Basic roundtrip
python python/examples/simple_roundtrip.py

# Publisher
python python/examples/py_nats_pub.py

# Subscriber
python python/examples/py_nats_sub.py

# DLQ operations
python python/examples/py_dlq_inspect.py
python python/examples/py_dlq_redrive.py
python python/examples/py_send_poison.py

5. Test CLI Tools:

# NATS operations
./ampybusctl pub-empty --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer test@cli --source test --pk XNAS.AAPL
./ampybusctl sub --subject "ampy.prod.bars.v1.>"

# Kafka operations
./kafkabusctl ensure-topic --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --partitions 3
./kafkabusctl pub-empty --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL \
  --producer test@cli --source test --pk XNAS.AAPL

# Inspection tools
./kafkainspect --brokers 127.0.0.1:9092 \
  --topic ampy.prod.bars.v1.XNAS.AAPL --group inspector --max 5

📖 Documentation

The sections above provide a practical introduction to using ampy-bus. For complete technical details, see:

• Problem Statement & Design Principles - Why ampy-bus exists and core design principles
• Topic Taxonomy - Standardized topic naming conventions
• Envelope & Headers - Required and optional message headers
• Delivery Semantics - Ordering guarantees by domain
• Error Handling & DLQ - Retry, backpressure, and dead letter queue behavior
• Replay & Backfill - Historical data replay capabilities
• Observability - Metrics, logging, and tracing standards
• Security & Compliance - Security requirements and auditability
• Performance Targets - Latency and throughput SLOs
• Domain Examples - Complete envelope examples for each domain

🤝 Contributing

• Open an issue describing changes to topics/headers/QoS before sending PRs
• Include golden envelopes and tests for any new domain
• Follow semantic versioning for header changes (additive only)

📄 License

Apache-2.0 (patent-grant, enterprise-friendly)

---

1) Problem Statement

AmpyFin is a modular, self‑learning trading system. Teams naturally want different transports (Kafka vs NATS) and different ingestion sources (Databento C++, yfinance Go, Tiingo, Marketbeat, FX rates, etc.). Without a shared messaging contract, systems drift:

• Schema drift & bespoke adapters between services
• Ambiguous delivery semantics (ordering, idempotency, retries)
• Poor replayability for research and audits
• Inconsistent metrics/logging across services

ampy-bus solves this by specifying the contract, not the broker—so modules can be swapped or scaled independently with zero message‑shape drift and predictable delivery semantics.

---

2) Mission & Success Criteria

Mission

Provide a single, consistent messaging layer for all AmpyFin subsystems such that modules are independently deployable and replayable.

Success looks like

• Any producer can emit ampy-proto payloads with identical envelopes and headers; any consumer can parse them without adapters.
• Topics and headers encode schema identity, lineage, and version, enabling deterministic replays/audits.
• Clear QoS tiers and ordering keys by domain (e.g., (symbol, mic) for prices, client_order_id for orders).
• Observed latency and throughput meet SLOs across live and replay paths.
• Backpressure, retries, DLQ, and recovery behaviors are consistent and testable.

---

3) Scope (What ampy-bus Covers)

• Transport‑agnostic contract for topics, envelopes, headers, keys, ordering, retries, DLQ, replay, and observability.
• Domain‑specific guidance: bars, ticks, news, FX, fundamentals, corporate actions, universe, signals, orders, fills, positions, metrics.
• Performance & SLO targets, backpressure handling, and capacity planning guidance.
• Security & compliance norms for trading workloads (authn/z, TLS, PII policy, auditability).
• Helper libraries: Go (NATS/Kafka clients), Python helpers for envelope encode/decode and validation.

Non‑goals: No broker‑specific configuration or business logic. No repository layout in this README.

---

4) Design Principles

1. ampy-proto is the source of truth for payloads (e.g., ampy.bars.v1.BarBatch). No new payload shapes.
2. Envelope wraps payload with headers for lineage, routing, and observability.
3. Time is UTC. Distinguish: event_time (market/source), ingest_time (ingestion), as_of (logical processing time).
4. Stable identity via SecurityId where securities are referenced.
5. Idempotency by default: stable message_id (UUIDv7) plus domain dedupe_key when available.
6. Compatibility: additive evolution only within a major; breaking changes bump the payload major version (v2 topics).
7. Serialization: application/x-protobuf (primary). Optional diagnostic JSON for human inspection only.
8. Compression: if payload > 128 KiB, content_encoding="gzip" and compress the bytes.
9. Size limits: target < 1 MiB; otherwise use object‑storage pointer pattern (§10).

---

5) Topic Taxonomy & Namespacing

Canonical pattern (slashes shown for readability; use . separators in broker subjects when appropriate):

ampy.{env}.{domain}.{version}.{subtopic}

• env: dev | paper | prod
• domain: bars | ticks | fundamentals | news | fx | corporate_actions | universe | signals | orders | fills | positions | metrics | dlq | control
• version: v1, v2 (mirrors payload major version in ampy-proto)
• subtopic: domain‑specific segment(s) to enforce locality & ordering, e.g.:
  • bars: {mic}.{symbol} → XNAS.AAPL
  • ticks: trade.{symbol} or quote.{symbol}
  • news: raw or nlp
  • fx: rates or {base}.{quote}
  • signals: {model_id} (e.g., hyper@2025-09-05)
  • orders: requests
  • fills: events
  • positions: snapshots
  • metrics: {service}

Examples

• ampy.prod.bars.v1.XNAS.AAPL
• ampy.paper.orders.v1.requests
• ampy.prod.signals.v1.hyper@2025-09-05

Consumers may subscribe using broker‑native wildcards/prefixes; producers should publish to concrete subjects.

---

6) Envelope & Headers (Contract)

Each published record = Envelope + Payload (ampy-proto bytes).

6.1 Required Headers

Header	Type	Example	Purpose
message_id	UUIDv7	018F5E2F-9B1C-76AA-8F7A-3B1D8F3EA0C2	Global unique id; sortable for time‑ordering; dedupe anchor
schema_fqdn	string	ampy.bars.v1.BarBatch	Exact payload message type (ampy-proto)
schema_version	semver	1.0.0	Schema minor/patch for diagnostics; major is in topic
content_type	string	application/x-protobuf	Serialization hint
content_encoding	string	gzip (or omitted)	Compression indicator
produced_at	RFC3339 UTC	2025-09-05T19:31:01Z	When producer created this record
producer	string	yfinance-go@ingest-1	Logical service instance id
source	string	yfinance-go | databento-cpp	Upstream/source system identity
run_id	string	live_0912	Correlates records for a pipeline run/session
trace_id / span_id	W3C traceparent	00-...	End‑to‑end tracing
partition_key	string	XNAS.AAPL	Sharding/ordering key (domain‑specific)

6.2 Optional Headers

• dedupe_key — domain idempotency key (e.g., client_order_id, news id)
• retry_count — incremented on republish after failure
• dlq_reason — set by infrastructure when routing to DLQ
• schema_hash — hash of compiled schema for defensive checks
• blob_ref, blob_hash, blob_size — pointer pattern for oversized payloads (§10)

---

7) Delivery Semantics, Ordering & Keys (by Domain)

The helper libraries will implement transport‑specific bindings that respect these logical guarantees.

Defaults

• QoS: at‑least‑once with idempotent consumers
• Ordering: guaranteed within a partition key

Recommended Keys & Guarantees

Domain	Partition/Ordering Key	Notes
bars	(symbol, mic) → XNAS.AAPL	Monotonic by event_time within key
ticks	(symbol, mic); subtopics trade./quote.	Extremely high‑rate; separate subtopics
news	id	Dedupe by id
fx	(base, quote)	Snapshot semantics; latest wins
fundamentals	(symbol, mic, period_end, source)	Consumers handle restatements
universe	universe_id	Snapshots monotonic in as_of
signals	(model_id, symbol, mic, horizon)	Latest prior to expires_at wins
orders	client_order_id	Strict causal order submit → amend/cancel
fills	(account_id, client_order_id)	Arrival may be out‑of‑order; accumulate
positions	(account_id, symbol, mic)	Monotonic as_of per key
metrics	(service, metric_name)	Counters/gauges semantics

---

8) Error Handling, Retries, Backpressure, DLQ

• Producer retries: exponential backoff with jitter; ceilings per QoS class
• Consumer retries: bounded attempts; on persistent failure → DLQ with original headers + dlq_reason
• Backpressure: consumers signal lag (transport‑specific) → producers reduce batch size/pause low‑priority topics
• Poison pills: decode or contract violations → DLQ + metrics/alerts; never drop silently
• Idempotency: consumers dedupe by message_id and domain dedupe_key (if present)

---

9) Large Payloads — Object Storage Pointer Pattern

If payload exceeds thresholds:

1. Publish a pointer envelope with blob_ref (e.g., s3://bucket/key?versionId=...) and metadata (blob_hash, blob_size).
2. Consumers fetch object out‑of‑band, validate hash, then process.
3. Replays retain blobs for the retention window.

---

10) Replay & Backfill

• Time‑window replay for time‑series domains (bars/ticks/news/fx): specify [start, end) in UTC
• Key‑scoped replay for orders/fills/positions: by (account_id, client_order_id) or (account_id, symbol, mic)
• Idempotent sinks: replays must be no‑ops on previously applied effects
• Checkpointing: consumers persist high‑watermarks (time or offset) per key/partition
• Retention: ≥ 7 days live logs (prod), ≥ 30 days analytical cluster; longer for compliance domains

Control Topic
ampy.{env}.control.v1.replay_requests carries ampy.control.v1.ReplayRequest payloads.

---

11) Observability: Metrics, Logs, Traces

Standard Metrics (examples)

• bus.produced_total{topic,producer} — counter
• bus.consumed_total{topic,consumer} — counter
• bus.delivery_latency_ms{topic} — histogram (p50/p95/p99)
• bus.batch_size_bytes{topic} — histogram
• bus.consumer_lag{topic,consumer} — gauge
• bus.dlq_total{topic,reason} — counter
• bus.retry_total{topic,reason} — counter
• bus.decode_fail_total{topic,reason} — counter

Logging
Structured JSON with message_id, trace_id, topic, producer|consumer, result (ok|retry|dlq), latency_ms. Do not log payloads.

Tracing
Propagate W3C traceparent; spans for publish, route, consume, and downstream handling.

---

12) Security & Compliance

• Encryption in transit: TLS/mTLS
• AuthN/Z: topic‑level ACLs (read/write); producers/consumers authenticate
• PII policy: forbidden in bus payloads; orders must not contain customer PII
• Auditability: headers + payload hashes enable forensic reconstruction
• Secrets: retrieved via ampy-config (never hardcode)
• Tenancy: dev / paper / prod namespaces

API keys / credentials: None required by ampy-bus itself. Broker bindings will need credentials (e.g., NATS auth token or Kafka SASL), and some producers (Marketbeat, Tiingo) may need API keys. We’ll prompt for those during binding setup.

---

13) Performance Targets (SLOs)

• Latency (publish → first delivery)
  • Orders/Signals/Fills: p99 ≤ 50 ms (same‑AZ)
  • Bars/Ticks: p99 ≤ 150 ms
• Payload size: < 1 MiB (typical 32–256 KiB); compress large batches
• Availability: ≥ 99.9% monthly for prod bus plane
• Recovery: RPO ≤ 5 min, RTO ≤ 15 min (documented procedures)

---

14) Domain‑Specific Envelope Examples

Shape and semantics only. Payload bodies are ampy-proto message types.

14.1 Bars batch (adjusted, 1‑minute)

Envelope:
 topic: "ampy.prod.bars.v1.XNAS.AAPL"
 headers: {
   "message_id": "018f5e2f-9b1c-76aa-8f7a-3b1d8f3ea0c2",
   "schema_fqdn": "ampy.bars.v1.BarBatch",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:01Z",
   "producer": "yfinance-go@ingest-1",
   "source": "yfinance-go",
   "run_id": "run_abc123",
   "trace_id": "4b5b3f2a0f9d4e3db4c8a1f0e3a7c812",
   "partition_key": "XNAS.AAPL"
 }
Payload:
 BarBatch (multiple Bar records for 19:30–19:31 window, adjusted=true)

14.2 Trade tick

Envelope:
 topic: "ampy.prod.ticks.v1.trade.MSFT"
 headers: {
   "message_id": "018f5e30-1a3b-7f9e-bccc-1e12a1c3e0d9",
   "schema_fqdn": "ampy.ticks.v1.TradeTick",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:30:12.462Z",
   "producer": "databento-cpp@tick-ingest-3",
   "source": "databento-cpp",
   "run_id": "live_0912",
   "trace_id": "a0c1b2d3e4f5061728394a5b6c7d8e9f",
   "partition_key": "MSFT.XNAS"
 }
Payload:
 TradeTick (event_time=...; price/size; venue=XNAS)

14.3 News item (dedupe by id)

Envelope:
 topic: "ampy.prod.news.v1.raw"
 headers: {
   "message_id": "018f5e31-0e1d-7b2a-9f7c-41acef2b9f01",
   "schema_fqdn": "ampy.news.v1.NewsItem",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T13:05:15Z",
   "producer": "marketbeat-go@news-2",
   "source": "marketbeat-go",
   "run_id": "news_live_37",
   "trace_id": "f2b1c7d9c4c34b3a9d0e4f5a9e2d8b11",
   "partition_key": "marketbeat:2025-09-05:amzn-headline-8b12c6",
   "dedupe_key": "marketbeat:2025-09-05:amzn-headline-8b12c6"
 }
Payload:
 NewsItem (headline/body/tickers; published_at=...; sentiment_score_bp=240)

14.4 FX snapshot

Envelope:
 topic: "ampy.prod.fx.v1.rates"
 headers: {
   "message_id": "018f5e31-3c55-76af-9421-fd10ce9bba75",
   "schema_fqdn": "ampy.fx.v1.FxRate",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:30:00Z",
   "producer": "fxrates-go@fx-1",
   "source": "fxrates-go",
   "run_id": "fx_145",
   "trace_id": "2f0a3c6e9b574c5e8b7a6d5c4b3a2f19",
   "partition_key": "USD.JPY"
 }
Payload:
 FxRate (bid/ask/mid; as_of=...)

14.5 Signal (ALPHA) and OMS order request

Envelope:
 topic: "ampy.prod.signals.v1.hyper@2025-09-05"
 headers: {
   "message_id": "018f5e32-7f1a-74d2-9a11-b53f54d8a911",
   "schema_fqdn": "ampy.signals.v1.Signal",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:03Z",
   "producer": "ampy-model-server@mdl-1",
   "source": "ampy-model-server",
   "run_id": "live_0912",
   "trace_id": "1c2d3e4f5061728394a5b6c7d8e9fa0b",
   "partition_key": "hyper@2025-09-05|NVDA.XNAS"
 }
Payload:
 Signal (type=ALPHA; score=-0.3450; horizon=5d)

Envelope:
 topic: "ampy.prod.orders.v1.requests"
 headers: {
   "message_id": "018f5e32-9b2a-7cde-9333-4f1ab2a49e77",
   "schema_fqdn": "ampy.orders.v1.OrderRequest",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:05Z",
   "producer": "ampy-oms@oms-2",
   "source": "ampy-oms",
   "run_id": "live_trading_44",
   "trace_id": "9f8e7d6c5b4a39281706f5e4d3c2b1a0",
   "partition_key": "co_20250905_001",
   "dedupe_key": "co_20250905_001"
 }
Payload:
 OrderRequest (account_id=ALPACA-LIVE-01; side=BUY; limit_price=191.9900)

14.6 Fill and Position snapshots

Envelope:
 topic: "ampy.prod.fills.v1.events"
 headers: {
   "message_id": "018f5e33-0a1b-71e3-980f-bcaa4c11902a",
   "schema_fqdn": "ampy.fills.v1.Fill",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:06Z",
   "producer": "broker-alpaca@alp-1",
   "source": "broker-alpaca",
   "run_id": "live_trading_44",
   "trace_id": "0a1b2c3d4e5f60718293a4b5c6d7e8f9",
   "partition_key": "ALPACA-LIVE-01|co_20250905_001"
 }
Payload:
 Fill (partial fill; price/quantity; venue=ALPACA)

Envelope:
 topic: "ampy.prod.positions.v1.snapshots"
 headers: {
   "message_id": "018f5e33-4b7d-72ac-8d24-d0a3e1b4c1e3",
   "schema_fqdn": "ampy.positions.v1.Position",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:35:00Z",
   "producer": "ampy-position-pnl@pnl-1",
   "source": "ampy-position-pnl",
   "run_id": "live_trading_44",
   "trace_id": "1029384756abcdef0123456789abcdef",
   "partition_key": "ALPACA-LIVE-01|AAPL.XNAS"
 }
Payload:
 Position (quantity/avg_price/unrealized/realized pnl; as_of=...)

14.7 Metrics

Envelope:
 topic: "ampy.prod.metrics.v1.ampy-oms"
 headers: {
   "message_id": "018f5e34-3b21-7c1f-b8e2-31b9e7fda4d0",
   "schema_fqdn": "ampy.metrics.v1.Metric",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:05Z",
   "producer": "ampy-oms@oms-2",
   "source": "ampy-oms",
   "run_id": "live_trading_44",
   "trace_id": "abcdef0123456789abcdef0123456789",
   "partition_key": "ampy-oms|oms.order_rejects"
 }
Payload:
 Metric (name=oms.order_rejects; labels={broker:alpaca, env:prod, reason:risk_check}; value=1)

14.8 DLQ example

Envelope:
 topic: "ampy.prod.dlq.v1.bars"
 headers: {
   "message_id": "018f5e35-0f42-7a31-9e77-1c2a9b11d0ef",
   "schema_fqdn": "ampy.bars.v1.BarBatch",
   "schema_version": "1.0.0",
   "content_type": "application/x-protobuf",
   "produced_at": "2025-09-05T19:31:02Z",
   "producer": "bus-router@plane-1",
   "source": "ampy-bus",
   "run_id": "bus_20250905",
   "trace_id": "feedfacecafebeef0011223344556677",
   "partition_key": "XNAS.AAPL",
   "dlq_reason": "decode_error: invalid decimal scale"
 }
Payload:
 (original payload bytes preserved; access controlled; include hash)

---

15) Broker Bindings (Implementation Guidance)

ampy-bus defines logical contracts. Helper libraries will implement:

15.1 NATS (suggested)

• Subject maps to topic (with . separators).
• partition_key influences subject tokenization or JetStream stream sharding.
• Headers carried via NATS message headers.
• JetStream for durability, ack/replay, and consumer lag metrics.

15.2 Kafka (optional/parallel)

• Topic = ampy.{env}.{domain}.{version}; subtopic mapped to record key or additional topic segments.
• partition_key used as Kafka key to guarantee per‑key order.
• Headers map to Kafka record headers; consumer groups manage offsets/lag.

Choose either or both. Contracts remain identical; only the binding differs.

---

16) Validation & Testing (What “Good” Looks Like)

• Golden Envelopes: ≥ 3 per domain (typical, minimal, edge/large).
• Cross‑language round‑trip: Protobuf (Go/Python/C++) identical.
• Ordering tests: per‑key monotonicity under concurrency.
• Idempotency tests: duplicates by message_id and dedupe_key are no‑ops.
• Replay tests: time‑window & key‑scoped replays do not double‑apply effects.
• Fault injection: drop/duplicate/reorder/corrupt → DLQ + alerts.
• Load tests: validate SLOs; backpressure signals propagate.

---

17) Security & Compliance Testing

• mTLS/TLS enforced; cert rotation validated.
• ACLs: producers/consumers limited to permitted topics.
• Audit tabletop: reconstruct a trading session from envelopes (headers + payload hashes).
• Retention: meets policy for orders/fills compliance.

---

18) Acceptance Criteria (Definition of Done for v1)

1. Topic taxonomy, envelope header set, and per‑domain keys/ordering are finalized and documented.
2. Golden envelope examples exist for every domain (≥3 each).
3. SLO & capacity targets are documented and validated by load tests.
4. Replay, DLQ, and backpressure behaviors are proven via fault‑injection tests.
5. Security posture (TLS, ACLs, auditability) verified; no PII traverses the bus.
6. Integration note maps each AmpyFin service to required topics and headers.

---

19) End‑to‑End Narrative (Cross‑Domain Flow)

1. yfinance‑go publishes bars.v1 batches for AAPL@XNAS with partition_key="XNAS.AAPL"; compressed if needed.
2. ampy‑features consumes bars, emits features internally, and ampy‑model‑server publishes signals.v1 (ALPHA scores) to signals/hyper@....
3. ampy‑ensemble consumes multiple signals, emits final ACTION signals.
4. ampy‑oms converts actions into orders.v1 on orders/requests keyed by client_order_id, ensuring strict per‑order causality.
5. broker‑alpaca publishes fills.v1, and ampy‑position‑pnl updates positions.v1 snapshots.
6. All services emit metrics.v1; dashboards show latency, lag, retries, and DLQ counts.
7. If a gap is detected, an operator posts a ReplayRequest (control topic); consumers reprocess idempotently.

---

20) Integration Notes (per AmpyFin subsystem)

• Data Ingestion: Databento C++ (ticks), Tiingo/yfinance Go (bars/fundamentals), Marketbeat Go (news), custom FX‑rates Go client (USD/EUR/JPY/KRW etc.). All publish to bus with the same envelopes/headers.
• Research/ML: feature extraction and model inference consume bars/ticks/news/fundamentals; publish signals.v1.
• Execution: OMS consumes signals; publishes orders.v1 and consumes fills.v1; positions calculated and published.
• Monitoring: all services publish metrics.v1 to a metrics sink; alerts on DLQ spikes/lag/latency.
• Compliance: orders/fills/positions retained per policy; audit derives from headers and payload hashes.

---

21) Roadmap (post‑v1)

• Helper SDKs: ampy-bus-go and ampy-bus-py (envelopes, validation, tracing hooks, codecs).
• CLI tools: produce/consume/replay testers; DLQ inspector.
• Schema registry hooks: signature checks and schema hash enforcement.
• Reference bindings: NATS JetStream and Kafka examples.
• Benchmarks: publicly documented latency/throughput across brokers.

---

22) FAQ

Q: Why Protobuf instead of Avro/JSON?
Protobuf gives compact, fast, cross‑language serialization and already underpins ampy-proto.

Q: Can we use both NATS and Kafka?
Yes. Contracts are transport‑agnostic. Bindings map headers/keys appropriately.

Q: Where do API keys live?
In each binding/producer via ampy-config or broker‑native secret stores. Never in code or headers.

Q: How do we handle currency conversions/news IDs/etc.?
Those are producers (e.g., FX Go client, Marketbeat Go) that emit domain payloads. The bus contract remains unchanged.

---

23) Contributing

• Open an issue describing changes to topics/headers/QoS before sending PRs.
• Include golden envelopes and tests for any new domain.
• Follow semantic versioning for header changes (additive only) and bump payload major in topics for breaking payload changes.

---

24) License

Proposed: Apache‑2.0 (patent‑grant, enterprise‑friendly). Confirm before first release.

---

25) Badges / About (GitHub)

About:
“Transport‑agnostic messaging conventions & helpers for AmpyFin. Standard topics, headers, QoS, replay, and observability over NATS or Kafka. Payloads are ampy-proto.”

Topics: trading-systems, messaging, protobuf, nats, kafka, event-driven, fintech, observability, slo, open-source, ampyfin

---