Arbitrum One Gas Optimization: Technical Reference

Configuration Requirements

Gas Model Fundamentals

Arbitrum charges for 5 distinct resource dimensions (not generic "gas"):

1. Computation - CPU work (cheapest component, 20-30% of total cost)
2. State reads - Storage slot access (expensive, costs more during congestion)
3. State writes - New storage creation (most expensive, 60-70% of total cost)
4. Event logs - L1 data posting cost (varies with ETH gas prices)
5. Calldata - Input data L1 posting cost (5-15% of total)

Production Cost Thresholds

• Normal periods: $0.20-0.80 per transaction
• Congestion periods: $3-12 per transaction (user abandonment threshold)
• Network degradation: Occurs around 15 TPS, sometimes earlier
• State operation cost multiplier: 10x increase during high congestion
• Critical failure point: Creating new storage slots can cost $5+ during congestion

Resource Requirements

Development Prerequisites

• Monitoring tools: Tenderly (transaction debugging), Blockscout (block explorer)
• Testing requirements: Must test during actual network congestion, not just normal conditions
• Gas estimation buffer: 50-100% safety margin required
• Batch operation limits: Maximum 25-50 operations per batch to prevent failures

Time Investment Estimates

• State packing implementation: Medium complexity, high impact (cuts costs by ~50%)
• Event optimization: Low complexity, 10-25% savings depending on ETH gas
• Assembly optimization: Very high complexity, minimal impact (5-15% savings max)
• Event-driven state reconstruction: Very high complexity, 30-60% savings (expert-only)

Critical Implementation Warnings

State Storage Failure Modes

• Single biggest cost factor: New storage slot creation during congestion
• Hidden cost: Multiple state reads within single function (each read costs $0.50+ during busy periods)
• Breaking point: Contracts creating >3 state operations per transaction become prohibitively expensive
• Failure scenario: "Optimized" mainnet contracts fail on Arbitrum due to different gas model

Gas Estimation Critical Flaw

• Primary failure cause: estimateGas() provides minimum gas for perfect conditions
• Real failure rate: 30-40% transaction failure during congestion without buffers
• Required mitigation: Always multiply estimates by 1.5-2x minimum
• Impact severity: Users lose gas fees on failed transactions, causing abandonment

Batch Operation Breaking Points

• Gas limit failures: Occur randomly during network congestion
• Circuit breaker requirement: Must check gasleft() < originalGas / 10 inside loops
• Maximum safe batch size: 50 operations maximum, 25 recommended
• Failure consequence: Complete transaction reversion with gas fee loss

Proven Implementation Patterns

State Storage Optimization (Required)

// CRITICAL: Pack data into single storage slots
struct PackedPosition {
    uint128 amount;      // Sufficient precision for most cases
    uint64 timestamp;    // Unix timestamp fits in 64 bits  
    bool active;         // Packed with timestamp
}

// Cache reads within functions - each state read is expensive
function updatePosition(address user, uint128 newAmount) external {
    PackedPosition storage pos = positions[user]; // Single read
    require(pos.active, "Position inactive");
    pos.amount = newAmount; // Single write
}

Gas Buffer Strategy (Critical)

// REQUIRED: Buffer gas estimates to prevent failures
const baseEstimate = await contract.estimateGas.complexFunction(params);
const gasLimit = baseEstimate.mul(150).div(100); // Minimum 50% buffer
const tx = await contract.complexFunction(params, { gasLimit });

Safe Batching Pattern

function safeBatch(address[] memory users, uint256[] memory amounts) external {
    require(users.length <= 50, "Batch too large"); // Hard limit
    
    uint gasStart = gasleft();
    for (uint i = 0; i < users.length; i++) {
        if (gasleft() < gasStart / 10) { // Reserve 10% gas
            revert("Gas limit approaching");
        }
        updateUserBalance(users[i], amounts[i]);
    }
}

Cost-Benefit Analysis

Optimization	Real Savings	Implementation Complexity	Production Stability	Recommendation
Pack Storage Slots	50%+ cost reduction	Medium	High	✅ Always implement
Cache State Reads	15-30% reduction	Low	High	✅ Standard practice
Batch Operations	20-50% reduction	Low-High	Medium	⚠️ Requires circuit breakers
Minimize Events	10-25% reduction	Low	High	✅ Usually beneficial
Gas Buffers	0% savings, prevents failures	Low	High	✅ Critical for reliability
Assembly Optimization	5-15% reduction	Very High	Low	❌ Not cost-effective

Monitoring Requirements

Essential Metrics to Track

• State operation costs vs total gas consumption
• Transaction failure rates (target <5%)
• Gas estimation accuracy during different network conditions
• Event count per transaction (warn if >10 events)
• Batch operation success rates

Alert Thresholds

• High cost warning: Transactions >400k gas likely indicate excessive state operations
• Network congestion indicator: Simple transactions costing >$2
• Batch failure indicator: >5% batch operations failing with gas errors
• Gas buffer inadequacy: >5% transactions failing with "out of gas"

Integration Considerations

Bridge Reality

• Withdrawal time: 7 days (unchangeable due to optimistic rollup design)
• Fast exit options: Across, Hop (0.1-0.3% fees)
• Sequencer centralization: Single point of failure (historical 4-hour outage in 2022)

Current Limitations

• Dynamic pricing: Not implemented despite documentation (as of September 2025)
• Gas estimation reliability: Fundamentally unreliable during congestion
• State cost predictability: Varies significantly with network conditions

Decision Framework

When to Use Arbitrum

• Suitable for: DeFi applications with predictable transaction patterns
• Avoid if: Requiring fixed gas costs or frequent batch operations >50 items
• Alternative consideration: Base for simple applications, avoid zkSync Era due to compatibility issues

Optimization Priority Order

1. State storage packing - Highest impact, required for production
2. Gas buffer implementation - Prevents user transaction failures
3. State read caching - Easy wins with reliable savings
4. Event minimization - Beneficial during high ETH gas periods
5. Batch circuit breakers - Essential if implementing batch operations

Failure Prevention Checklist

Before production deployment:

• New storage slots are packed efficiently (target: <3 slots per user)
• State reads are cached within functions
• Batch operations have gas circuit breakers
• Events are minimal and necessary (<10 per transaction)
• Gas estimates include 50-100% safety buffers
• Tested during actual network congestion periods
• Monitoring alerts configured for cost spikes and failure rates

Success Metrics

Production Benchmarks

• Target cost range: $0.20-0.80 normal periods, <$3 during congestion
• Acceptable failure rate: <5% transactions failing due to gas issues
• User retention threshold: Transactions consistently >$3 cause abandonment
• Network resilience: Contract functions remain usable during 15+ TPS periods

This technical reference prioritizes operational intelligence over theoretical optimization, focusing on patterns proven to work in production environments with thousands of daily transactions.