HFT Pipeline Architecture: Complete Guide

Date: 2024-12-18 Status: Production-Ready Design Target: <200ms execution (quote → profit in wallet)

Overview
Quote Service Integration
NATS 4-Stream Architecture
Event Flow: Scanner → Planner → Executor
TwoHopArbitrageEvent Design
Scanner Implementation
Planner Implementation (Future)
Executor Implementation (Future)
Deployment & Configuration
Performance Targets
Migration Checklist

Overview

Four-Stage Pipeline

QUOTE-SERVICE (Go) (Quote Generation - <10ms per quote)
    ↓ Queries pools, caches quotes, streams via gRPC/NATS
    ↓ Publishes: MARKET_DATA stream (optional NATS) + gRPC streaming
SCANNER (Fast Pre-Filter - <10ms)
    ↓ Filters noise, detects patterns
    ↓ Publishes: OPPORTUNITIES stream
PLANNER (Deep Validation - 50-100ms with RPC simulation)
    ↓ Validates profitability, chooses execution method
    ↓ Publishes: PLANNED stream
EXECUTOR (Dumb Submission - <20ms)
    ↓ Just signs and sends
    ↓ Publishes: EXECUTED stream

Key Principle: Quote-Service = data (cached), Scanner = detect (cheap), Planner = validate (expensive), Executor = execute (dumb)

Performance Goals

Stage	Current	Target	Achieved
Scanner	8ms	<10ms	✅
Planner	-	50-100ms	⏳ Future
Executor	-	<20ms	⏳ Future
Total	-	<200ms	🎯 Goal

NATS 6-Stream Architecture (FlatBuffers)

Stream Overview

┌────────────────────────────────────────────────────────────┐
│                  NATS Server (Single Instance)              │
├────────────────────────────────────────────────────────────┤
│                                                             │
│  1. MARKET_DATA (Quote-Service → market data)               │
│     ├─ Throughput: 10,000 events/sec                        │
│     ├─ Retention: 1 hour                                    │
│     ├─ Storage: Memory (sub-1ms latency)                    │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: market.swap_route.*, market.price.*        │
│                                                             │
│  2. OPPORTUNITIES (Scanner → detected opportunities)        │
│     ├─ Throughput: 500 events/sec                           │
│     ├─ Retention: 24 hours                                  │
│     ├─ Storage: File (2-5ms latency)                        │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: opportunity.two_hop.*, opportunity.triangular.* │
│                                                             │
│  3. PLANNED (Planner → validated plans)                      │
│     ├─ Throughput: 50 events/sec                            │
│     ├─ Retention: 1 hour (ephemeral)                        │
│     ├─ Storage: File (2-5ms latency)                        │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: execution.planned.*, execution.rejected.*  │
│                                                             │
│  4. EXECUTED (Executor → execution results)                 │
│     ├─ Throughput: 50 events/sec                            │
│     ├─ Retention: 7 days (audit trail)                      │
│     ├─ Storage: File (5-10ms latency)                       │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: executed.completed.*, executed.failed.*    │
│                                                             │
│  5. METRICS (Performance metrics)                           │
│     ├─ Throughput: 1,000-5,000 events/sec                   │
│     ├─ Retention: 1 hour                                    │
│     ├─ Storage: Memory (sub-1ms latency)                    │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: metrics.latency.*, metrics.throughput.*    │
│                                                             │
│  6. SYSTEM (Lifecycle & health events)                      │
│     ├─ Throughput: 1-10 events/sec                          │
│     ├─ Retention: 30 days (audit trail)                     │
│     ├─ Storage: File (persistence critical)                 │
│     ├─ Format: FlatBuffers (zero-copy)                      │
│     └─ Subjects: system.lifecycle.*, system.health.*        │
│                                                             │
└────────────────────────────────────────────────────────────┘

FlatBuffers Performance Benefits

Metric	JSON	FlatBuffers	Improvement
Encode Time	5-10μs	1-2μs	5-10x faster
Decode Time	8-15μs	0.1-0.5μs	20-150x faster
Message Size	450-600 bytes	300-400 bytes	30% smaller
Zero-Copy Read	❌ No	✅ Yes	Eliminates copies
Memory Allocation	❌ High	✅ Minimal	Reduces GC pressure

Expected Latency Reduction: 10-20ms per event (5-10% of 200ms budget)

Why 6 Separate Streams?

1. Different Throughput Rates

Quote-Service → 10,000 events/sec (quotes to MARKET_DATA)
                  ↓ (Scanner consumes via gRPC or NATS)
Scanner       →    500 events/sec (98% filtered by detectArbitrage)
                  ↓ (opportunities to OPPORTUNITIES)
Planner       →     50 events/sec (90% rejected after RPC simulation)
                  ↓ (validated plans to PLANNED)
Executor      →     50 events/sec (results to EXECUTED)
                  ↓ (metrics aggregation)
Metrics       →  1,000-5,000 events/sec (latency, throughput, PnL to METRICS)
                  ↓ (lifecycle events)
System        →      1-10 events/sec (start, shutdown, kill switch to SYSTEM)

Filtering efficiency: 99.5% (10k quotes → 50 executions/sec) Metrics throughput: High-frequency performance data (every trade + periodic) System throughput: Low-frequency operational events (lifecycle only)

2. Different Retention Policies

MARKET_DATA:     1 hour   (noisy raw data, delete fast)
OPPORTUNITIES:  24 hours  (debugging opportunity detection)
PLANNED:         1 hour   (execution plans, short-lived)
EXECUTED:        7 days   (audit trail, PnL reporting)
METRICS:         1 hour   (short-lived, aggregated to Prometheus)
SYSTEM:         30 days   (regulatory compliance, audit trail)

Benefit:

Save disk space: PLANNED/METRICS are ephemeral (execute once and done)
Long retention: EXECUTED (7 days) for PnL analysis, SYSTEM (30 days) for compliance
Operational clarity: System lifecycle events separate from trading events

3. Independent Replay

# Replay opportunities to test new strategy logic
nats stream replay OPPORTUNITIES --since "2024-12-17T00:00:00Z"

# Replay execution plans to test executor changes (dry-run mode)
nats stream replay PLANNED --since "2024-12-17T00:00:00Z"

# Replay execution results for PnL recalculation
nats stream replay EXECUTED --since "2024-12-17T00:00:00Z"

4. Complete Fault Isolation

If Scanner crashes:
├─ MARKET_DATA: ⚠️ No new data (expected)
├─ OPPORTUNITIES: ⚠️ No new opportunities (expected)
├─ PLANNED: ✅ Planner buffers old opportunities
└─ EXECUTED: ✅ Executor keeps processing

If Planner crashes:
├─ MARKET_DATA: ✅ Scanner unaffected
├─ OPPORTUNITIES: ✅ Buffer fills with new opportunities
├─ PLANNED: ⚠️ No new plans (expected)
└─ EXECUTED: ✅ Executor processes buffered plans

If Executor crashes:
├─ MARKET_DATA: ✅ Scanner unaffected
├─ OPPORTUNITIES: ✅ Planner unaffected
├─ PLANNED: ✅ Buffer fills with validated plans
└─ EXECUTED: ⚠️ No new results (expected)

Stream Configurations

Stream 1: MARKET_DATA

{
  name: 'MARKET_DATA',
  subjects: ['market.swap_route.>', 'market.price.>', 'market.pool.>'],
  retention: 'limits',
  max_age: 3600 * 1e9,         // 1 hour
  max_msgs: 100000,            // 100k messages
  max_bytes: 1073741824,       // 1 GB
  storage: 'memory',           // ⚡ In-memory for speed
  replicas: 1,
  discard: 'old',
  duplicate_window: 5 * 1e9,   // 5 second deduplication
}

Stream 2: OPPORTUNITIES

{
  name: 'OPPORTUNITIES',
  subjects: ['opportunity.two_hop.>', 'opportunity.triangular.>'],
  retention: 'limits',
  max_age: 86400 * 1e9,        // 24 hours
  max_msgs: 10000,             // 10k messages
  max_bytes: 104857600,        // 100 MB
  storage: 'file',             // 💾 Persistent for debugging
  replicas: 1,
  discard: 'old',
  duplicate_window: 10 * 1e9,  // 10 second deduplication
}

Stream 3: PLANNED

{
  name: 'PLANNED',
  subjects: ['execution.planned.>', 'execution.rejected.>'],
  retention: 'limits',
  max_age: 3600 * 1e9,         // 1 hour (short-lived)
  max_msgs: 1000,              // 1k messages
  max_bytes: 10485760,         // 10 MB
  storage: 'file',             // 💾 Persistent
  replicas: 1,
  discard: 'old',
  duplicate_window: 10 * 1e9,  // 10 second deduplication
}

Stream 4: EXECUTED

{
  name: 'EXECUTED',
  subjects: ['executed.started.>', 'executed.completed.>', 'executed.failed.>'],
  retention: 'limits',
  max_age: 604800 * 1e9,       // 7 days
  max_msgs: -1,                // Unlimited (up to max_bytes)
  max_bytes: 1073741824,       // 1 GB
  storage: 'file',             // 💾 Persistent for audit
  replicas: 1,
  discard: 'old',
  duplicate_window: 60 * 1e9,  // 60 second deduplication
}

Stream 5: METRICS

{
  name: 'METRICS',
  subjects: ['metrics.latency.>', 'metrics.throughput.>', 'metrics.pnl.>', 'metrics.strategy.>'],
  retention: 'limits',
  max_age: 3600 * 1e9,         // 1 hour
  max_msgs: 50000,             // 50k messages
  max_bytes: 104857600,        // 100 MB
  storage: 'memory',           // ⚡ In-memory for speed
  replicas: 1,
  discard: 'old',
  duplicate_window: 5 * 1e9,   // 5 second deduplication
}

Stream 6: SYSTEM

{
  name: 'SYSTEM',
  subjects: ['system.lifecycle.>', 'system.killswitch.>', 'system.health.>'],
  retention: 'limits',
  max_age: 2592000 * 1e9,      // 30 days
  max_msgs: 10000,             // 10k messages
  max_bytes: 52428800,         // 50 MB
  storage: 'file',             // 💾 Persistent for compliance
  replicas: 1,
  discard: 'old',
  duplicate_window: 60 * 1e9,  // 60 second deduplication
}

Subject Hierarchy

# MARKET_DATA stream
market.swap_route.<tokenIn>.<tokenOut>
market.price.<symbol>
market.pool.<dex>.<poolId>

# OPPORTUNITIES stream
opportunity.two_hop.detected.<tokenStart>.<tokenIntermediate>
opportunity.triangular.detected.<tokenA>.<tokenB>.<tokenC>

# PLANNED stream
execution.planned.<opportunityId>
execution.rejected.<opportunityId>.<reason>

# EXECUTED stream
executed.started.<opportunityId>
executed.completed.<opportunityId>.<status>
executed.failed.<opportunityId>.<error>

# METRICS stream
metrics.latency.<component>.<operation>
metrics.throughput.<component>.<metric_type>
metrics.pnl.<strategy>.<token_pair>
metrics.strategy.<strategy_name>.<performance_metric>

# SYSTEM stream
system.lifecycle.start.<environment>
system.lifecycle.shutdown.<reason>
system.killswitch.<trigger>
system.health.slot_drift.<severity>
system.health.stalled.<component>
system.health.connection.<connection_type>.<status>

Event Flow: Quote-Service → Scanner → Planner → Executor

Complete Pipeline Diagram

┌─────────────────────────────────────────────────────────────────────┐
│ STAGE 0: QUOTE-SERVICE (Go)                                        │
│ ─────────────────────────────────────────────────────────────────── │
│ Input: On-chain pool data (RPC + cached)                           │
│                                                                     │
│ Processing (<10ms per quote):                                      │
│ • Query all pools for token pair                                   │
│ • Calculate optimal routing                                        │
│ • Cache quotes (30s refresh)                                       │
│                                                                     │
│ Publishes to NATS:                                                 │
│ • Stream: MARKET_DATA                                              │
│ • Subject: market.swap_route.<tokenIn>.<tokenOut>                  │
│ • Event: SwapRouteEvent                                            │
│                                                                     │
│ Also provides:                                                     │
│ • gRPC: QuoteService.StreamQuotes() - streaming quotes             │
│ • HTTP: GET /quote?input=<>&output=<>&amount=<>                    │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘
                            │
                            │ NATS: market.swap_route.* (optional)
                            │ OR gRPC streaming (primary)
                            ↓
┌─────────────────────────────────────────────────────────────────────┐
│ STAGE 1: SCANNER (Fast Pre-Filter)                                 │
│ ─────────────────────────────────────────────────────────────────── │
│ Subscribes to NATS:                                                │
│ • Stream: MARKET_DATA (optional, primary is gRPC)                  │
│   └─ Subjects: market.swap_route.>                                 │
│ • Stream: SYSTEM (for lifecycle events) ⚠️ CRITICAL                │
│   └─ Subjects: system.killswitch.>, system.lifecycle.shutdown.*    │
│                                                                     │
│ Input Options:                                                     │
│ • Option A: gRPC quote stream from quote-service (primary)         │
│ • Option B: NATS MARKET_DATA stream (alternative)                  │
│                                                                     │
│ Processing (<10ms):                                                │
│ • detectArbitrage() - Simple math, no RPC                          │
│ • Calculate rough profit estimates                                 │
│ • Build complete execution path (SwapHop[])                        │
│ • Confidence: 0.5-0.8 (rough, pre-filter only)                     │
│ • Handle KillSwitch: Stop scanning immediately on trigger          │
│ • Handle Shutdown: Graceful cleanup on system shutdown             │
│                                                                     │
│ Publishes to NATS:                                                 │
│ • Stream: OPPORTUNITIES                                            │
│   └─ Subject: opportunity.two_hop.detected.<tokenStart>.<tokenIntermediate> │
│   └─ Event: TwoHopArbitrageEvent (FlatBuffers)                     │
│ • Stream: METRICS                                                  │
│   └─ Subject: metrics.latency.scanner.*                            │
│   └─ Event: LatencyMetricEvent (FlatBuffers)                       │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘
                            │
                            │ NATS: opportunity.two_hop.*
                            ↓
┌─────────────────────────────────────────────────────────────────────┐
│ STAGE 2: PLANNER (Deep Validation / Strategy Framework)            │
│ ─────────────────────────────────────────────────────────────────── │
│ Subscribes to NATS:                                                │
│ • Stream: OPPORTUNITIES (opportunities to validate)                │
│   └─ Subjects: opportunity.>                                       │
│   └─ Events: TwoHopArbitrageEvent, TriangularArbitrageEvent (FlatBuffers) │
│ • Stream: MARKET_DATA (fresh quotes for simulation) ⚠️ CRITICAL    │
│   └─ Subjects: market.swap_route.>, market.price.>                 │
│   └─ Events: SwapRouteEvent, PriceUpdateEvent (FlatBuffers)        │
│ • Stream: SYSTEM (for lifecycle events) ⚠️ CRITICAL                │
│   └─ Subjects: system.killswitch.>, system.lifecycle.shutdown.*    │
│                                                                     │
│ Processing (50-100ms):                                             │
│ • Fetch fresh quotes from MARKET_DATA (if Scanner's quotes stale)  │
│ • RPC simulation with current pool state (expensive but necessary) │
│ • Deep profit validation                                           │
│ • Risk scoring                                                     │
│ • Choose execution method (Jito/TPU/RPC)                           │
│ • Confidence: 0.9+ (high accuracy after simulation)                │
│ • Handle KillSwitch: Stop planning + reject all pending            │
│ • Handle Shutdown: Finish current validation, graceful exit        │
│                                                                     │
│ Publishes to NATS:                                                 │
│ • Stream: PLANNED                                                   │
│   └─ Subject: execution.planned.<opportunityId>                    │
│   └─ Event: ExecutionPlanEvent (FlatBuffers)                       │
│ • Stream: PLANNED (rejections)                                      │
│   └─ Subject: execution.rejected.<opportunityId>.<reason>          │
│   └─ Event: ExecutionRejectedEvent (FlatBuffers)                   │
│ • Stream: METRICS                                                  │
│   └─ Subject: metrics.latency.planner.*                            │
│   └─ Event: LatencyMetricEvent (FlatBuffers)                       │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘
                            │
                            │ NATS: execution.planned.*
                            ↓
┌─────────────────────────────────────────────────────────────────────┐
│ STAGE 3: EXECUTOR (Dumb Submission / Executor Framework)           │
│ ─────────────────────────────────────────────────────────────────── │
│ Subscribes to NATS:                                                │
│ • Stream: PLANNED                                                   │
│   └─ Subjects: execution.planned.>                                 │
│   └─ Events: ExecutionPlanEvent (FlatBuffers)                      │
│ • Stream: SYSTEM (for lifecycle events) ⚠️ CRITICAL                │
│   └─ Subjects: system.killswitch.>, system.lifecycle.shutdown.*    │
│                                                                     │
│ Processing (<20ms):                                                │
│ • Build transaction from pre-computed path                         │
│ • Sign with wallet                                                 │
│ • Submit via Jito/TPU/RPC (as specified in plan)                   │
│ • NO validation, NO simulation (Planner already did this)          │
│ • Handle KillSwitch: Stop execution + cancel pending transactions  │
│ • Handle Shutdown: Finish in-flight txs, graceful exit             │
│                                                                     │
│ Publishes to NATS:                                                 │
│ • Stream: EXECUTED                                                 │
│   └─ Subject: executed.started.<opportunityId>                     │
│   └─ Event: ExecutionStartedEvent (FlatBuffers)                    │
│ • Stream: EXECUTED                                                 │
│   └─ Subject: executed.completed.<opportunityId>.<status>          │
│   └─ Event: ExecutionResultEvent (FlatBuffers)                     │
│ • Stream: EXECUTED                                                 │
│   └─ Subject: executed.failed.<opportunityId>.<error>              │
│   └─ Event: ExecutionFailedEvent (FlatBuffers)                     │
│ • Stream: METRICS                                                  │
│   └─ Subject: metrics.latency.executor.*, metrics.pnl.*            │
│   └─ Events: LatencyMetricEvent, PnLMetricEvent (FlatBuffers)      │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘
                            │
                            │ NATS: executed.completed.*
                            ↓
                   PnL Service, Monitor, Analytics

Responsibility Matrix

Service	Publishes To	Subjects	Events	Purpose
Quote-Service	MARKET_DATA	market.swap_route., market.price., market.pool.*	SwapRouteEvent, PriceUpdateEvent, PoolStateEvent	Real-time market data (quotes, prices, pool updates)
Scanner	OPPORTUNITIES	opportunity.two_hop., opportunity.triangular.	TwoHopArbitrageEvent, TriangularArbitrageEvent	Detected opportunities (pre-validation)
Planner	PLANNED	execution.planned., execution.rejected.	ExecutionPlanEvent, ExecutionRejectedEvent	Validated plans (ready to execute)
Executor	EXECUTED	executed.started., executed.completed., executed.failed.*	ExecutionStartedEvent, ExecutionResultEvent, ExecutionFailedEvent	Execution results (for PnL, monitoring)

Consumption Matrix

Service	Consumes From	Subjects	Events	Purpose
Scanner	MARKET_DATA (optional)	market.swap_route.>	SwapRouteEvent	Alternative to gRPC streaming
Scanner	SYSTEM	system.killswitch.>, system.lifecycle.shutdown.*	KillSwitchEvent, SystemShutdownEvent	Stop scanning on kill switch or shutdown
Planner	OPPORTUNITIES + MARKET_DATA	opportunity.>, market.swap_route.>, market.price.>	TwoHopArbitrageEvent + SwapRouteEvent, PriceUpdateEvent	Validate opportunities with fresh market data
Planner	SYSTEM	system.killswitch.>, system.lifecycle.shutdown.*	KillSwitchEvent, SystemShutdownEvent	Stop planning + reject pending on kill switch
Executor	PLANNED	execution.planned.>	ExecutionPlanEvent	Execute validated plans
Executor	SYSTEM	system.killswitch.>, system.lifecycle.shutdown.*	KillSwitchEvent, SystemShutdownEvent	Cancel pending txs on kill switch
PnL Service	EXECUTED	executed.completed.>	ExecutionResultEvent	Calculate profit/loss from signatures
Monitor	EXECUTED + SYSTEM	executed.>, system.health.>	All execution + health events	Alert on failures, track success rate
Analytics	EXECUTED + METRICS	executed.>, metrics.>	All execution + metric events	Historical analysis, strategy performance

Notes:

ALL frameworks (Scanner, Planner, Executor) MUST subscribe to SYSTEM stream for kill switch and graceful shutdown
Scanner typically uses gRPC streaming from quote-service for lowest latency (<1ms), but can alternatively consume from NATS MARKET_DATA stream (2-5ms latency) for replay/testing scenarios
Planner (Strategy Framework) subscribes to BOTH OPPORTUNITIES and MARKET_DATA streams to validate opportunities with fresh quotes
Executor Framework subscribes to PLANNED stream for execution plans and SYSTEM for safety controls

Distributed Tracing Flow

TraceId: 550e8400-e29b-41d4-a716-446655440000

Stage 1: quote-service (Go)
├─ Span: quote_received (0ms)
└─ Publishes: SwapRouteEvent (traceId propagated)

Stage 2: scanner-service (TS)
├─ Span: arbitrage_detected (8ms)
├─ Parent: quote_received
└─ Publishes: TwoHopArbitrageEvent (traceId propagated)

Stage 3: planner-service (TS)
├─ Span: arbitrage_validated (85ms)
├─ Parent: arbitrage_detected
└─ Publishes: ExecutionPlanEvent (traceId propagated)

Stage 4: executor-service (TS)
├─ Span: arbitrage_executed (18ms)
├─ Parent: arbitrage_validated
└─ Publishes: ExecutionResultEvent (traceId propagated)

TOTAL: 111ms (quote → profit in wallet)

TwoHopArbitrageEvent Design

Event Structure (Go)

// go/pkg/events/events.go

type TwoHopArbitrageEvent struct {
	Type       string `json:"type"`
	TraceId    string `json:"traceId"`    // UUID for distributed tracing
	Timestamp  int64  `json:"timestamp"`
	Slot       uint64 `json:"slot"`

	// Opportunity identification
	OpportunityId      string `json:"opportunityId"` // Unique ID for deduplication

	// Tokens involved
	TokenStart         string `json:"tokenStart"`        // Starting token (e.g., SOL)
	TokenIntermediate  string `json:"tokenIntermediate"` // Intermediate token (e.g., mSOL, USDC)

	// Execution path (critical for performance)
	Path               []SwapHop `json:"path"` // [A→B, B→A] with full execution details

	// Profit analysis
	AmountIn           string  `json:"amountIn"`           // Input amount (as string for u64)
	ExpectedAmountOut  string  `json:"expectedAmountOut"`  // Expected output after round-trip
	EstimatedProfitUsd float64 `json:"estimatedProfitUsd"` // Estimated profit in USD
	EstimatedProfitBps int32   `json:"estimatedProfitBps"` // Estimated profit in basis points
	NetProfitUsd       float64 `json:"netProfitUsd"`       // Profit after fees

	// Risk metrics
	TotalFees          string  `json:"totalFees"`          // Total fees (all hops)
	PriceImpactBps     int32   `json:"priceImpactBps"`     // Total price impact
	RequiredCapitalUsd float64 `json:"requiredCapitalUsd"` // Capital needed (for flash loan sizing)
	Confidence         float64 `json:"confidence"`         // 0.0 - 1.0 (scanner's confidence)

	// Liquidity context
	Hop1LiquidityUsd   float64 `json:"hop1LiquidityUsd"`   // First hop pool liquidity
	Hop2LiquidityUsd   float64 `json:"hop2LiquidityUsd"`   // Second hop pool liquidity

	// Timing
	ExpiresAt          int64   `json:"expiresAt"`          // Estimated expiration timestamp
	DetectedAtSlot     uint64  `json:"detectedAtSlot"`     // Slot when detected

	// Scanner context (for strategy optimization)
	ScannerName        string                 `json:"scannerName"`        // Which scanner detected this
	ScannerMetadata    map[string]interface{} `json:"scannerMetadata"`    // Scanner-specific metadata
}

type SwapHop struct {
	AmmKey     string `json:"ammKey"`     // Pool/AMM address
	Label      string `json:"label"`      // DEX name ("Raydium", "Orca", etc.)
	InputMint  string `json:"inputMint"`  // Input token mint address
	OutputMint string `json:"outputMint"` // Output token mint address
	InAmount   string `json:"inAmount"`   // Input amount as string
	OutAmount  string `json:"outAmount"`  // Output amount as string
	FeeAmount  string `json:"feeAmount"`  // Fee amount as string
	FeeMint    string `json:"feeMint"`    // Fee token mint address
}

Example Event: SOL → mSOL → SOL

{
  "type": "TwoHopArbitrage",
  "traceId": "550e8400-e29b-41d4-a716-446655440000",
  "opportunityId": "2hop_SOL_mSOL_12345678",
  "tokenStart": "So11111111111111111111111111111111111111112",
  "tokenIntermediate": "mSoLzYCxHdYgdzU16g5QSh3i5K3z3KZK7ytfqcJm7So",
  "path": [
    {
      "ammKey": "6a1CsrpeZubDjEJE9s1CMVheB6HWM5d7m1cj2jkhyXhj",
      "label": "raydium_amm",
      "inputMint": "So11111111111111111111111111111111111111112",
      "outputMint": "mSoLzYCxHdYgdzU16g5QSh3i5K3z3KZK7ytfqcJm7So",
      "inAmount": "1000000000",
      "outAmount": "950000000",
      "feeAmount": "2500",
      "feeMint": "So11111111111111111111111111111111111111112"
    },
    {
      "ammKey": "9tzZzEHsKnwFL1A3DyFJwj36KnZj3gZ7g4srWp9YTEoh",
      "label": "orca_whirlpool",
      "inputMint": "mSoLzYCxHdYgdzU16g5QSh3i5K3z3KZK7ytfqcJm7So",
      "outputMint": "So11111111111111111111111111111111111111112",
      "inAmount": "950000000",
      "outAmount": "1005000000",
      "feeAmount": "950000",
      "feeMint": "mSoLzYCxHdYgdzU16g5QSh3i5K3z3KZK7ytfqcJm7So"
    }
  ],
  "amountIn": "1000000000",
  "expectedAmountOut": "1005000000",
  "estimatedProfitUsd": 0.25,
  "estimatedProfitBps": 50,
  "netProfitUsd": 0.22,
  "totalFees": "3450",
  "priceImpactBps": 15,
  "requiredCapitalUsd": 50.0,
  "confidence": 0.75,
  "hop1LiquidityUsd": 150000.0,
  "hop2LiquidityUsd": 200000.0,
  "expiresAt": 1734512350000,
  "detectedAtSlot": 12345678,
  "scannerName": "arbitrage-quote-scanner",
  "scannerMetadata": {
    "source": "gRPC_quote_stream",
    "filterType": "two_hop_round_trip",
    "quoteCacheSize": 1247
  }
}

Scanner Implementation

ArbitrageQuoteScanner Architecture

// ts/apps/scanner-service/src/scanners/arbitrage-quote-scanner.ts

export class ArbitrageQuoteScanner extends SubscriptionScanner {
  private quoteCache: Map<string, QuoteStreamResponse[]> = new Map();
  private readonly CACHE_TTL_MS = 5000; // 5 second cache
  private readonly MIN_PROFIT_BPS = 30; // 0.3% minimum for pre-filter

  protected async process(quote: QuoteStreamResponse): Promise<MarketEvent[]> {
    const tracer = trace.getTracer('scanner-service');

    // Extract parent trace context from quote
    const parentContext = quote.traceId
      ? this.extractTraceContext(quote.traceId)
      : context.active();

    return await tracer.startActiveSpan(
      'arbitrage_detection',
      { kind: SpanKind.INTERNAL },
      parentContext,
      async (span) => {
        try {
          // STAGE 1: Update cache
          this.updateQuoteCache(quote);

          // STAGE 2: Fast pre-filter
          const candidates = await this.detectArbitrage(quote);

          span.setAttribute('candidates.found', candidates.length);

          if (candidates.length === 0) {
            span.setStatus({ code: SpanStatusCode.OK, message: 'No opportunities' });
            return [];
          }

          // STAGE 3: Convert to TwoHopArbitrageEvent
          const events = candidates.map(candidate =>
            this.toTwoHopArbitrageEvent(candidate, span.spanContext().traceId)
          );

          span.setAttribute('events.published', events.length);
          span.setStatus({ code: SpanStatusCode.OK });

          return events;
        } catch (error) {
          span.recordException(error as Error);
          span.setStatus({ code: SpanStatusCode.ERROR, message: (error as Error).message });
          return [];
        } finally {
          span.end();
        }
      }
    );
  }
}

Fast Pre-Filter Logic

/**
 * FAST PRE-FILTER: Detect potential arbitrage opportunities
 *
 * CONSTRAINTS:
 * - No RPC calls (fast)
 * - Use cached data only
 * - Simple math only
 * - High false positive rate is OK (strategy validates)
 */
private async detectArbitrage(quote: QuoteStreamResponse): Promise<ArbitrageCandidate[]> {
  const candidates: ArbitrageCandidate[] = [];

  // Get cached reverse quotes: outputMint → inputMint
  const reverseQuotes = this.getCachedReverseQuotes(
    quote.outputMint,
    quote.inputMint
  );

  if (reverseQuotes.length === 0) return [];

  for (const reverseQuote of reverseQuotes) {
    // Check freshness
    if (Date.now() - reverseQuote.timestamp > this.CACHE_TTL_MS) {
      continue;
    }

    // Calculate round-trip profit
    const amountIn = BigInt(quote.inAmount);
    const finalAmount = BigInt(reverseQuote.outAmount);

    if (finalAmount <= amountIn) continue;

    // Profit in basis points
    const profitBps = Number((finalAmount - amountIn) * 10000n / amountIn);

    // Pre-filter threshold
    if (profitBps < this.MIN_PROFIT_BPS) continue;

    // Calculate rough confidence (no simulation)
    const confidence = this.calculatePreFilterConfidence(
      quote,
      reverseQuote,
      profitBps
    );

    candidates.push({
      tokenStart: quote.inputMint,
      tokenIntermediate: quote.outputMint,
      forwardQuote: quote,
      reverseQuote: reverseQuote,
      profitBps,
      confidence,
    });
  }

  // Sort by profit, return top 5
  return candidates.sort((a, b) => b.profitBps - a.profitBps).slice(0, 5);
}

Pre-Filter Confidence Calculation

/**
 * Calculate pre-filter confidence (no RPC simulation)
 *
 * FACTORS:
 * - Profit magnitude (higher = better)
 * - Pool liquidity (higher = better)
 * - Price impact (lower = better)
 * - Quote freshness (newer = better)
 */
private calculatePreFilterConfidence(
  forwardQuote: QuoteStreamResponse,
  reverseQuote: QuoteStreamResponse,
  profitBps: number
): number {
  let confidence = 0.4; // Base confidence (conservative)

  // Factor 1: Profit magnitude
  if (profitBps > 50) confidence += 0.1;   // >0.5%
  if (profitBps > 100) confidence += 0.1;  // >1.0%
  if (profitBps > 200) confidence += 0.1;  // >2.0%

  // Factor 2: Liquidity
  const minLiquidity = Math.min(
    forwardQuote.liquidityUsd || 0,
    reverseQuote.liquidityUsd || 0
  );
  if (minLiquidity > 50000) confidence += 0.05;   // >$50k
  if (minLiquidity > 100000) confidence += 0.1;   // >$100k
  if (minLiquidity > 500000) confidence += 0.1;   // >$500k

  // Factor 3: Price impact
  const totalSlippage = forwardQuote.slippageBps + reverseQuote.slippageBps;
  if (totalSlippage < 50) confidence += 0.1;   // <0.5%
  if (totalSlippage < 20) confidence += 0.05;  // <0.2%

  // Factor 4: Freshness
  const maxAge = Math.max(
    Date.now() - forwardQuote.timestamp,
    Date.now() - reverseQuote.timestamp
  );
  if (maxAge < 1000) confidence += 0.05;  // <1s old

  return Math.min(confidence, 1.0);
}

Quote Caching

/**
 * Update quote cache for reverse lookup
 */
private updateQuoteCache(quote: QuoteStreamResponse): void {
  const key = `${quote.inputMint}:${quote.outputMint}`;

  if (!this.quoteCache.has(key)) {
    this.quoteCache.set(key, []);
  }

  const quotes = this.quoteCache.get(key)!;
  quotes.push(quote);

  // Keep only recent quotes
  const cutoff = Date.now() - this.CACHE_TTL_MS;
  this.quoteCache.set(
    key,
    quotes.filter(q => q.timestamp > cutoff)
  );

  // Cleanup old cache entries (1% chance per quote)
  if (Math.random() < 0.01) {
    this.cleanupCache();
  }
}

/**
 * Get cached reverse quotes: outputMint → inputMint
 */
private getCachedReverseQuotes(
  outputMint: string,
  inputMint: string
): QuoteStreamResponse[] {
  const key = `${outputMint}:${inputMint}`;
  return this.quoteCache.get(key) || [];
}

Planner Implementation (Future)

Why Planner Needs MARKET_DATA Access

Problem: Scanner uses 5-second cached quotes for fast pre-filtering. By the time Planner validates an opportunity (50-100ms later), those quotes may be stale.

Solution: Planner subscribes to MARKET_DATA stream for fresh quotes during RPC simulation.

// Planner validation flow
async validateOpportunity(arb: TwoHopArbitrageEvent): Promise<ExecutionPlanEvent | null> {
  // STEP 1: Check if Scanner's quotes are still fresh
  const quoteAge = Date.now() - arb.timestamp;

  if (quoteAge > 2000) {
    // STEP 2: Quotes are stale (>2s old), fetch fresh quotes from MARKET_DATA
    const freshQuotes = await this.fetchFreshQuotesFromMarketData(
      arb.tokenStart,
      arb.tokenIntermediate
    );

    // STEP 3: Recalculate profit with fresh quotes
    const updatedProfit = this.calculateProfit(freshQuotes);

    if (updatedProfit < this.MIN_PROFIT_THRESHOLD) {
      return null; // Opportunity expired
    }
  }

  // STEP 4: RPC simulation with current pool state
  const simulation = await this.simulateArbitrage(arb);

  // STEP 5: Create execution plan if profitable
  if (simulation.success && simulation.netProfit > 0.01) {
    return this.createExecutionPlan(arb, simulation);
  }

  return null;
}

Benefits:

✅ Accuracy: Planner validates with fresh data, not stale Scanner cache
✅ Flexibility: Can re-quote specific pairs without waiting for Scanner
✅ Performance: Only fetches fresh quotes when needed (if stale)
✅ Reliability: Reduces false positives from price movement between detection and execution

Trade-off: Planner has slightly higher latency (50-100ms) but much higher accuracy (90%+ vs Scanner’s 65%)

ExecutionPlanEvent Structure

// ts/packages/market-events/src/events.ts

export interface ExecutionPlanEvent {
  type: 'ExecutionPlan';
  traceId: string; // Propagated from TwoHopArbitrageEvent
  timestamp: number;
  slot: number;

  // Reference to source opportunity
  opportunityId: string;
  sourceEvent: 'TwoHopArbitrage' | 'TriangularArbitrage';

  // Execution details
  executionMethod: 'jito_bundle' | 'tpu_direct' | 'rpc_fallback' | 'parallel_racing';
  path: SwapHop[]; // May be modified by strategy

  // Validation results
  simulationResult: {
    success: boolean;
    netProfit: number;
    gasUsed: number;
    logs: string[];
  };

  // Execution parameters
  jitoTip?: string;        // If using Jito
  computeBudget: number;   // Compute units
  priorityFee: string;     // Priority fee (lamports)

  // Risk assessment (after simulation)
  confidence: number;      // Updated confidence after simulation
  riskScore: number;       // 0.0 - 1.0 (lower is safer)

  // Strategy context
  strategyName: string;
  strategyMetadata: Record<string, unknown>;

  // Timing
  validUntil: number;      // Deadline for execution
}

Planner Logic (Conceptual)

// ts/apps/planner-service/src/strategies/two-hop-arbitrage-strategy.ts

export class TwoHopArbitrageStrategy implements TradingStrategy {
  async onMarketEvent(event: MarketEvent): Promise<ExecutionPlanEvent[]> {
    if (event.type !== 'TwoHopArbitrage') return [];

    const arb = event as TwoHopArbitrageEvent;

    // STAGE 1: Pre-validation
    if (arb.confidence < 0.5) return []; // Scanner wasn't confident
    if (arb.estimatedProfitBps < 50) return []; // <0.5% profit

    // STAGE 2: RPC Simulation (expensive!)
    const simulation = await this.simulateArbitrage(arb);
    if (!simulation.success) return [];
    if (simulation.netProfit < 0.01) return []; // <0.01 SOL profit

    // STAGE 3: Choose execution method
    const executionMethod = this.chooseExecutionMethod(arb, simulation);

    // STAGE 4: Create execution plan
    return [this.createExecutionPlan(arb, simulation, executionMethod)];
  }

  private chooseExecutionMethod(
    arb: TwoHopArbitrageEvent,
    simulation: SimulationResult
  ): ExecutionMethod {
    // High-value: Use Jito for MEV protection
    if (simulation.netProfit > 0.1) return 'jito_bundle';

    // Medium-value: Try TPU direct (faster, no tip)
    if (simulation.netProfit > 0.03) return 'tpu_direct';

    // Low-value: Use RPC (cheapest)
    return 'rpc_fallback';
  }
}

Executor Implementation (Future)

ExecutionResultEvent Structure

export interface ExecutionResultEvent {
  type: 'ExecutionResult';
  traceId: string;
  opportunityId: string;
  signature: string;        // On-chain transaction signature
  actualProfit: number;     // Real profit from on-chain data
  actualProfitUsd: number;
  gasUsed: number;
  blockTime: number;
  executionMethod: string;
  status: 'success' | 'partial_fill' | 'failed';
  timestamp: number;
}

Executor Logic (Conceptual)

// ts/apps/executor-service/src/executor.ts

export class JitoExecutor {
  async execute(plan: ExecutionPlanEvent): Promise<ExecutionResultEvent> {
    // STAGE 1: Build transaction from pre-computed path
    const tx = await this.buildTransaction(plan.path);

    // STAGE 2: Sign with wallet
    tx.sign([this.wallet]);

    // STAGE 3: Submit via Jito
    const signature = await this.submitViaJito(tx, plan.jitoTip);

    // STAGE 4: Wait for confirmation
    await this.connection.confirmTransaction(signature);

    // STAGE 5: Calculate actual profit from on-chain data
    const txData = await this.connection.getTransaction(signature);
    const actualProfit = this.calculateProfitFromTx(txData);

    return {
      type: 'ExecutionResult',
      traceId: plan.traceId,
      opportunityId: plan.opportunityId,
      signature,
      actualProfit,
      status: 'success',
      timestamp: Date.now(),
    };
  }
}

Deployment & Configuration

Docker Compose Setup

# deployment/docker/docker-compose.yml

services:
  nats:
    image: nats:2.10-alpine
    ports:
      - "4222:4222"   # Client connections
      - "8222:8222"   # HTTP monitoring
      - "6222:6222"   # Cluster routing
    command:
      - "--jetstream"
      - "--store_dir=/data"
      - "--max_file_store=10GB"
      - "--max_mem_store=2GB"
      - "--http_port=8222"
    volumes:
      - nats-data:/data
    healthcheck:
      test: ["CMD", "nats", "server", "check", "jetstream"]
      interval: 10s
      timeout: 5s
      retries: 3

  nats-setup:
    image: natsio/nats-box:latest
    depends_on:
      nats:
        condition: service_healthy
    volumes:
      - ./nats-init.sh:/init.sh
    command: ["/init.sh"]

volumes:
  nats-data:

NATS Initialization Script

#!/bin/bash
# deployment/docker/nats-init.sh

set -e

echo "Creating MARKET_DATA stream..."
nats stream add MARKET_DATA \
  --subjects "market.>" \
  --retention limits \
  --max-age 1h \
  --max-msgs 100000 \
  --max-bytes 1GB \
  --storage memory \
  --replicas 1 \
  --discard old \
  --dupe-window 5s

echo "Creating OPPORTUNITIES stream..."
nats stream add OPPORTUNITIES \
  --subjects "opportunity.>" \
  --retention limits \
  --max-age 24h \
  --max-msgs 10000 \
  --max-bytes 100MB \
  --storage file \
  --replicas 1 \
  --discard old \
  --dupe-window 10s

echo "Creating PLANNED stream..."
nats stream add PLANNED \
  --subjects "execution.>" \
  --retention limits \
  --max-age 1h \
  --max-msgs 1000 \
  --max-bytes 10MB \
  --storage file \
  --replicas 1 \
  --discard old \
  --dupe-window 10s

echo "Creating EXECUTED stream..."
nats stream add EXECUTED \
  --subjects "executed.>" \
  --retention limits \
  --max-age 7d \
  --max-msgs -1 \
  --max-bytes 1GB \
  --storage file \
  --replicas 1 \
  --discard old \
  --dupe-window 60s

echo "Creating METRICS stream..."
nats stream add METRICS \
  --subjects "metrics.>" \
  --retention limits \
  --max-age 1h \
  --max-msgs 50000 \
  --max-bytes 100MB \
  --storage memory \
  --replicas 1 \
  --discard old \
  --dupe-window 5s

echo "Creating SYSTEM stream..."
nats stream add SYSTEM \
  --subjects "system.>" \
  --retention limits \
  --max-age 30d \
  --max-msgs 10000 \
  --max-bytes 50MB \
  --storage file \
  --replicas 1 \
  --discard old \
  --dupe-window 60s

echo "JetStream setup complete! Created 6 streams."
nats stream list

Performance Targets

Latency Breakdown

Stage	Target	Critical Path	Notes
Scanner	<10ms	✅ Yes	Fast pre-filter only
NATS (OPPORTUNITIES)	2-5ms	✅ Yes	File storage latency
Planner	50-100ms	✅ Yes	RPC simulation (unavoidable)
NATS (PLANNED)	2-5ms	✅ Yes	File storage latency
Executor	<20ms	✅ Yes	Sign + submit
NATS (EXECUTED)	5-10ms	❌ No	After trade, not critical
TOTAL	<200ms	-	Scanner → Executor

Throughput Targets

Stream	Events/sec	Peak	Buffer Size
MARKET_DATA	10,000	20,000	100k messages
OPPORTUNITIES	500	1,000	10k messages
PLANNED	50	100	1k messages
EXECUTED	50	100	10k messages
METRICS	1,000-5,000	10,000	50k messages
SYSTEM	1-10	50	10k messages

Success Metrics

Scanner:
├─ False positive rate: <35% (acceptable)
├─ Latency: <10ms (critical)
└─ Throughput: 500 opportunities/sec

Planner:
├─ Filtering efficiency: >80% (reject bad opportunities)
├─ Simulation accuracy: >90% (profit estimate ± 10%)
└─ Latency: 50-100ms (RPC-dependent)

Executor:
├─ Success rate: >80% (with proper validation)
├─ Jito bundle landing rate: >95%
└─ Latency: <20ms (sign + submit only)

End-to-End:
├─ Total latency: <200ms (quote → profit)
├─ Profitable trades: >60% (after all filtering)
└─ Average profit: >0.05 SOL per trade

Framework SYSTEM Stream Integration

Critical Safety Requirement: All trading components (Scanner, Planner, Executor) MUST subscribe to the SYSTEM stream for:

Kill Switch Events: Immediately stop all trading activity when triggered
Graceful Shutdown: Clean up resources and finish in-flight operations
System Health Monitoring: React to slot drift, connection failures, stalledcomponents

Framework Responsibilities

Scanner Framework (go/pkg/scanner)

MUST Subscribe To:

system.killswitch.> - Stop scanning immediately on any kill switch trigger
system.lifecycle.shutdown.* - Graceful shutdown on system stop

MUST Implement:

func (s *Scanner) handleKillSwitch(event *KillSwitchEvent) {
    s.logger.Error("Kill switch triggered", "trigger", event.Trigger)
    s.stopScanning()  // Stop immediately
    s.publishMetric("scanner.stopped", "killswitch")
}

func (s *Scanner) handleShutdown(event *SystemShutdownEvent) {
    s.logger.Info("Graceful shutdown initiated")
    s.stopScanning()  // Stop gracefully
    s.cleanup()       // Clean up resources
}

Strategy Framework (Planner) (ts/packages/strategy-framework)

MUST Subscribe To:

system.killswitch.> - Stop planning + reject all pending opportunities
system.lifecycle.shutdown.* - Finish current validation, then graceful exit
market.swap_route.>, market.price.> - Fresh quotes for simulation ⚠️ CRITICAL

MUST Implement:

async handleKillSwitch(event: KillSwitchEvent): Promise<void> {
  this.logger.error('Kill switch triggered', { trigger: event.trigger });
  this.stopPlanning();  // Stop immediately
  await this.rejectPendingOpportunities();  // Reject all buffered
  await this.publishMetric('planner.stopped', 'killswitch');
}

async handleShutdown(event: SystemShutdownEvent): Promise<void> {
  this.logger.info('Graceful shutdown initiated');
  await this.finishCurrentValidation();  // Finish in-flight
  this.stopPlanning();
  await this.cleanup();
}

Executor Framework (ts/packages/executor-framework)

MUST Subscribe To:

system.killswitch.> - Cancel pending transactions immediately
system.lifecycle.shutdown.* - Finish in-flight txs, then graceful exit

MUST Implement:

async handleKillSwitch(event: KillSwitchEvent): Promise<void> {
  this.logger.error('Kill switch triggered', { trigger: event.trigger });
  await this.cancelPendingTransactions();  // Cancel all pending
  this.stopExecution();  // Stop immediately
  await this.publishMetric('executor.stopped', 'killswitch');
}

async handleShutdown(event: SystemShutdownEvent): Promise<void> {
  this.logger.info('Graceful shutdown initiated');
  await this.finishInFlightTransactions();  // Wait for pending txs
  this.stopExecution();
  await this.cleanup();
}

SYSTEM Stream Event Flow

KILL SWITCH TRIGGERED:
┌─────────────────────────────────────────────────────────┐
│ Monitor detects critical condition (excessive loss)     │
│   ↓ Publishes: system.killswitch.excessive_loss        │
├─────────────────────────────────────────────────────────┤
│ Scanner receives KillSwitchEvent                        │
│   → Stop scanning immediately                           │
│   → No new opportunities published                      │
├─────────────────────────────────────────────────────────┤
│ Planner receives KillSwitchEvent                        │
│   → Stop planning immediately                           │
│   → Reject all buffered opportunities                   │
│   → Publish ExecutionRejectedEvent (reason: killswitch) │
├─────────────────────────────────────────────────────────┤
│ Executor receives KillSwitchEvent                       │
│   → Cancel all pending transactions                     │
│   → Stop execution immediately                          │
│   → Publish ExecutionFailedEvent (error: killswitch)    │
└─────────────────────────────────────────────────────────┘
Result: System stops trading within <100ms

GRACEFUL SHUTDOWN:
┌─────────────────────────────────────────────────────────┐
│ User triggers shutdown (SIGTERM / manual)               │
│   ↓ Publishes: system.lifecycle.shutdown.manual        │
├─────────────────────────────────────────────────────────┤
│ Scanner receives SystemShutdownEvent                    │
│   → Finish current detection cycle                      │
│   → Stop scanning gracefully                            │
│   → Publish final metrics                               │
├─────────────────────────────────────────────────────────┤
│ Planner receives SystemShutdownEvent                    │
│   → Finish validating current opportunity               │
│   → Stop planning gracefully                            │
│   → Publish final execution plan or rejection           │
├─────────────────────────────────────────────────────────┤
│ Executor receives SystemShutdownEvent                   │
│   → Wait for in-flight transactions (timeout: 30s)      │
│   → Stop execution gracefully                           │
│   → Publish final execution results                     │
└─────────────────────────────────────────────────────────┘
Result: System stops trading cleanly within 30-60s

Migration Checklist

Phase 1: FlatBuffers Setup (Week 1, Day 1-2)

Install flatc compiler on all dev machines
Run flatbuf/scripts/generate-all.ps1 to generate code
Verify generated code in flatbuf/generated/{go,typescript,rust}/
Add FlatBuffers dependencies to Go/TypeScript/Rust projects
Test round-trip serialization/deserialization

Phase 2: NATS Infrastructure (Week 1, Day 2-3)

Update docker-compose.yml with 6-stream NATS config (METRICS + SYSTEM)
Create nats-init.sh script with all 6 streams
Test NATS setup: docker-compose up -d nats
Verify all 6 streams created: nats stream list
Test publishing/consuming FlatBuffers events from each stream

Phase 3: Framework SYSTEM Integration (Week 1, Day 3-4)

Scanner: Add SYSTEM stream subscription (killswitch, shutdown)
Scanner: Implement handleKillSwitch() and handleShutdown()
Planner: Add SYSTEM stream subscription
Planner: Implement handleKillSwitch() with rejectPendingOpportunities()
Executor: Add SYSTEM stream subscription
Executor: Implement handleKillSwitch() with cancelPendingTransactions()
Test kill switch propagation (all frameworks stop within 100ms)
Test graceful shutdown (all frameworks cleanup within 30-60s)

Phase 4: Scanner Migration to FlatBuffers (Week 1, Day 4-5)

Update ArbitrageQuoteScanner to publish FlatBuffers TwoHopArbitrageEvent
Implement FlatBuffers serialization in detectArbitrage()
Add OpenTelemetry tracing to scanner
Add scanner metadata to events
Update NATS publishing to OPPORTUNITIES stream (FlatBuffers)
Publish LatencyMetricEvent to METRICS stream
Add unit tests for FlatBuffers serialization

Phase 5: Planner Migration to FlatBuffers (Week 2, Day 1-3)

Update TradingStrategy to consume FlatBuffers TwoHopArbitrageEvent
Subscribe to MARKET_DATA stream for fresh quotes (FlatBuffers)
Implement FlatBuffers deserialization in strategy validation
Publish FlatBuffers ExecutionPlanEvent to PLANNED stream
Publish FlatBuffers ExecutionRejectedEvent for rejections
Publish LatencyMetricEvent to METRICS stream
Test with FlatBuffers OPPORTUNITIES events

Phase 6: Executor Migration to FlatBuffers (Week 2, Day 4-5)

Update Executor to consume FlatBuffers ExecutionPlanEvent
Implement FlatBuffers deserialization in transaction building
Publish FlatBuffers ExecutionResultEvent to EXECUTED stream
Publish FlatBuffers ExecutionFailedEvent for failures
Publish PnLMetricEvent to METRICS stream
Test with FlatBuffers PLANNED events

Phase 7: End-to-End Testing (Week 3, Day 1-2)

Integration test: Quote → FlatBuffers events → Execution
Load test: 1000 events/sec throughput (all FlatBuffers)
Verify trace propagation end-to-end (FlatBuffers preserves traceId)
Measure latency reduction (JSON vs FlatBuffers)
Test kill switch under load (system stops < 100ms)
Test graceful shutdown under load
Validate FlatBuffers event data completeness

Phase 8: Production Deployment (Week 3, Day 3-5)

Deploy Scanner with FlatBuffers + SYSTEM integration
Monitor OPPORTUNITIES stream volume (FlatBuffers)
Deploy Planner with FlatBuffers + MARKET_DATA + SYSTEM
Monitor PLANNED stream volume (FlatBuffers)
Deploy Executor with FlatBuffers + SYSTEM
Monitor EXECUTED + METRICS streams
Measure end-to-end latency (<200ms target)
Verify FlatBuffers performance gains (10-20ms reduction)
Tune thresholds based on real data

Conclusion

Key Architectural Decisions

✅ 6 Separate JetStreams - Clear separation of concerns, different lifecycles

MARKET_DATA: High-throughput market data (10k events/sec)
OPPORTUNITIES: Pre-filtered opportunities (500 events/sec)
PLANNED: Validated execution plans (50 events/sec)
EXECUTED: Execution results (50 events/sec, 7-day retention)
METRICS: Performance metrics (1-5k events/sec, 1-hour retention)
SYSTEM: Lifecycle & health events (1-10 events/sec, 30-day retention)

✅ FlatBuffers for All Events - Zero-copy serialization

20-150x faster deserialization (0.1-0.5μs vs 8-15μs)
30% smaller message size (300-400 bytes vs 450-600 bytes)
Expected latency reduction: 10-20ms per event (5-10% of 200ms budget)
Minimal memory allocations (reduces GC pressure)

✅ TwoHopArbitrageEvent with Path - Complete execution data, no re-quoting needed

✅ Scanner = Fast Pre-Filter - <10ms, high false positive rate OK

✅ Planner = Deep Validation - 50-100ms, RPC simulation for accuracy

Subscribes to MARKET_DATA for fresh quotes during validation
Subscribes to SYSTEM for kill switch and graceful shutdown

✅ Executor = Dumb Submission - <20ms, trusts Planner’s validation

Subscribes to SYSTEM for kill switch and transaction cancellation

✅ Distributed Tracing - TraceId propagation in FlatBuffers for end-to-end visibility

✅ Kill Switch Safety - All frameworks subscribe to SYSTEM stream

System stops trading within <100ms on kill switch
Graceful shutdown within 30-60s with proper cleanup

Performance Expectations

Scanner:  8ms   (quote → TwoHopArbitrageEvent FlatBuffers)
NATS:     2ms   (OPPORTUNITIES stream latency)
Planner:  85ms  (TwoHopArbitrageEvent → ExecutionPlan FlatBuffers)
NATS:     2ms   (PLANNED stream latency)
Executor: 18ms  (ExecutionPlan → Transaction)
────────────────
TOTAL:    115ms (quote → profit in wallet)

With FlatBuffers optimization: -20ms (10ms serialization + 10ms deserialization) Final target: 95ms end-to-end (well under 200ms target) ✅

FlatBuffers Performance Impact

Operation	JSON (baseline)	FlatBuffers	Improvement
Scanner publish	10ms	2ms	-8ms
Planner consume	8ms	0.5ms	-7.5ms
Planner publish	10ms	2ms	-8ms
Executor consume	8ms	0.5ms	-7.5ms
Total saved	36ms	5ms	-31ms

SYSTEM Stream Safety Benefits

Scenario	Without SYSTEM	With SYSTEM	Improvement
Excessive loss	Manual intervention (minutes)	Auto kill switch (<100ms)	100x faster
Connection failure	Trades continue blindly	Auto pause + alert	Prevents losses
Slot drift	Unknown until too late	Real-time detection	Early warning
Graceful shutdown	Forced kill (lost state)	Clean exit (preserved state)	Data integrity

Next Steps

Week 1: FlatBuffers setup + NATS 6-stream deployment + SYSTEM integration
Week 2: Migrate Scanner/Planner/Executor to FlatBuffers
Week 3: End-to-end testing + production deployment
Result: <100ms end-to-end execution with full safety controls

Your HFT system is architecturally sound, performance-optimized (FlatBuffers), and production-safe (SYSTEM stream) - ready for implementation! 🚀

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James Shen

HFT Pipeline Architecture: Complete Guide

Table of Contents

Overview

Four-Stage Pipeline

Performance Goals

NATS 6-Stream Architecture (FlatBuffers)

Stream Overview

FlatBuffers Performance Benefits

Why 6 Separate Streams?

1. Different Throughput Rates

2. Different Retention Policies

3. Independent Replay

4. Complete Fault Isolation

Stream Configurations

Stream 1: MARKET_DATA

Stream 2: OPPORTUNITIES

Stream 3: PLANNED

Stream 4: EXECUTED

Stream 5: METRICS

Stream 6: SYSTEM

Subject Hierarchy

Event Flow: Quote-Service → Scanner → Planner → Executor

Complete Pipeline Diagram

Responsibility Matrix

Consumption Matrix

Distributed Tracing Flow

TwoHopArbitrageEvent Design

Event Structure (Go)

Example Event: SOL → mSOL → SOL

Scanner Implementation

ArbitrageQuoteScanner Architecture

Fast Pre-Filter Logic

Pre-Filter Confidence Calculation

Quote Caching

Planner Implementation (Future)

Why Planner Needs MARKET_DATA Access

ExecutionPlanEvent Structure

Planner Logic (Conceptual)

Executor Implementation (Future)

ExecutionResultEvent Structure

Executor Logic (Conceptual)

Deployment & Configuration

Docker Compose Setup

NATS Initialization Script

Performance Targets

Latency Breakdown

Throughput Targets

Success Metrics

Framework SYSTEM Stream Integration

Why ALL Frameworks Must Subscribe to SYSTEM

Framework Responsibilities

Scanner Framework (go/pkg/scanner)

Strategy Framework (Planner) (ts/packages/strategy-framework)

Executor Framework (ts/packages/executor-framework)

SYSTEM Stream Event Flow

Migration Checklist

Phase 1: FlatBuffers Setup (Week 1, Day 1-2)

Phase 2: NATS Infrastructure (Week 1, Day 2-3)

Phase 3: Framework SYSTEM Integration (Week 1, Day 3-4)

Phase 4: Scanner Migration to FlatBuffers (Week 1, Day 4-5)

Phase 5: Planner Migration to FlatBuffers (Week 2, Day 1-3)

Phase 6: Executor Migration to FlatBuffers (Week 2, Day 4-5)

Phase 7: End-to-End Testing (Week 3, Day 1-2)

Phase 8: Production Deployment (Week 3, Day 3-5)

Conclusion

Key Architectural Decisions

Performance Expectations

FlatBuffers Performance Impact

SYSTEM Stream Safety Benefits

Next Steps

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