System Architecture

Explore the sophisticated technical architecture that powers GRID Token's high-performance automated trading system, built with Rust for maximum efficiency and reliability.

Overview

Design Principles

GRID Token's architecture follows these core principles:

⚑

Performance

Sub-millisecond latency for critical operations

πŸ”’

Security

Zero-trust architecture with isolated components

πŸ”„

Reliability

99.99% uptime through redundancy and self-healing

πŸ“¦

Scalability

Horizontal scaling for unlimited growth

Technology Stack

Core Technologies

Language

Rust

Performance & safety

Framework

Tokio

Async runtime

Blockchain

Solana

High throughput

Database

PostgreSQL

Persistent storage

Core Components

System Architecture Diagram

Grid Trading EngineDelta Hedge EngineRisk ManagerActor SystemSniper ActorCentral ActorCoverage ActorSafe ActorBlockchain LayerData StorageExternal APIs

Component Descriptions

1. Grid Trading Engine

Responsibilities

  • β€’ Position range calculation based on volatility
  • β€’ Liquidity provision on Orca Whirlpools
  • β€’ Fee collection and reinvestment
  • β€’ Rebalancing coordination

Key Features

Transaction Speed

< 100ms

Concurrent Positions

Unlimited

2. Delta Hedge Engine

Responsibilities

  • β€’ Real-time delta calculation
  • β€’ Perpetual futures management on Drift
  • β€’ Hedge position optimization
  • β€’ Funding rate arbitrage

Performance Metrics

Delta Precision

Β± 0.5%

Update Frequency

5 seconds

3. Risk Manager

Responsibilities

  • β€’ Portfolio risk assessment
  • β€’ Position size limits
  • β€’ Drawdown protection
  • β€’ Emergency shutdown triggers

Safety Limits

Max Position Size

10% of AUM

Daily Rebalance Limit

6 times

Actor System Design

Actor Model Benefits

GRID uses an actor-based architecture for superior concurrency and fault isolation:

Concurrency

Each position runs as an independent actor, enabling true parallelism

  • β€’ No shared state between actors
  • β€’ Lock-free message passing
  • β€’ Automatic work distribution

Fault Isolation

Actor failures don't affect other positions or system components

  • β€’ Supervisor hierarchy
  • β€’ Automatic restart policies
  • β€’ Error boundary enforcement

Actor Implementation

pub struct PositionActor {
    position_id: String,
    strategy: PositionStrategy,
    whirlpool: WhirlpoolClient,
    state: PositionState,
}

impl Actor for PositionActor {
    type Context = Context<Self>;
    
    fn started(&mut self, ctx: &mut Self::Context) {
        // Schedule periodic tasks
        ctx.run_interval(Duration::from_secs(30), |act, _ctx| {
            act.check_position_health();
        });
    }
}

impl Handler<RebalanceMessage> for PositionActor {
    type Result = Result<RebalanceResult, Error>;
    
    fn handle(&mut self, msg: RebalanceMessage, _ctx: &mut Context<Self>) -> Self::Result {
        // Rebalance logic
        self.close_position()?;
        self.calculate_new_range(msg.volatility)?;
        self.open_position()?;
        Ok(RebalanceResult::Success)
    }
}

Message Flow

Actor Communication Pattern

RiskManager→PositionActor: CheckHealth
PositionActor→RiskManager: HealthStatus
Volatility→PositionActor: RebalanceSignal

Data Flow

Real-Time Data Pipeline

πŸ“‘ Price Data Ingestion

Pyth Network Oracle

400ms updates β†’ Price aggregator β†’ Volatility calculator

πŸ“Š Position Monitoring

Blockchain State

WebSocket subscriptions β†’ Position parser β†’ Delta calculator

🎯 Decision Engine

Strategy Processor

Market data + Risk limits β†’ Action decisions β†’ Order execution

Data Storage Architecture

Data TypeStorageRetentionPurpose
Position StatePostgreSQL + WALForeverRecovery & audit
Price TicksRedis (cache)24 hoursVolatility calc
Performance MetricsTimescaleDB90 daysAnalytics
Transaction LogsS3 + PostgreSQL7 yearsCompliance

Fault Tolerance

Self-Healing Mechanisms

Position Recovery

Automatic detection and recovery of failed positions

1. Detect position failure via heartbeat timeout 2. Attempt graceful shutdown and state save 3. Restart actor with last known good state 4. Verify position consistency on-chain 5. Resume normal operations

Network Resilience

Multi-RPC failover with automatic health checks

  • β€’ Primary: QuickNode (< 50ms latency)
  • β€’ Secondary: Helius (< 75ms latency)
  • β€’ Tertiary: Public RPC (emergency)

Monitoring & Alerting

System Health Monitoring

100%

API Uptime

< 1ms

P99 Latency

0

Failed Txns

16/16

Active Actors

Alert Thresholds

  • Critical: System downtime, position failures, delta deviation > 2%
  • Warning: High latency, rebalance failures, low SOL balance
  • Info: Successful rebalances, daily summaries, maintenance events

Performance Optimization

Optimization Techniques

Transaction Batching

Multiple operations combined into single transaction

Efficiency Gain

75% fee reduction

Compute Unit Optimization

Precise compute unit allocation for each operation

Success Rate

99.9%

Security Architecture

Key Management

  • Hot Wallet: Limited funds for operations (< 5% of AUM)
  • Multisig Treasury: Main fund storage (3/5 signatures)
  • Hardware Security Modules: Key generation and signing
  • Rotation Policy: Monthly key rotation for hot wallets

Access Control

// Simplified permission system
enum Permission {
    ReadOnly,
    Trading,
    Rebalancing,
    EmergencyShutdown,
    Admin,
}

impl Authorization {
    fn check_permission(&self, action: Action) -> Result<(), Error> {
        match (self.role, action) {
            (Role::Bot, Action::Trade) => Ok(()),
            (Role::Bot, Action::Withdraw) => Err(Error::Forbidden),
            (Role::Admin, _) => Ok(()),
            _ => Err(Error::Unauthorized),
        }
    }
}

Future Enhancements

Planned Improvements

  • Machine Learning Integration: Predictive volatility models
  • Cross-Chain Expansion: Support for multiple blockchains
  • Advanced Order Types: Iceberg orders, TWAP execution
  • Decentralized Governance: On-chain parameter updates

Infrastructure Details

Security Measures

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