Modern SSDs employ wear leveling algorithms to distribute write operations evenly across all available NAND blocks. This prevents premature wear on frequently written blocks. The controller maintains a logical-to-physical address mapping table, abstracting the physical storage from the host system.

// Simplified wear leveling pseudocode
class SSDController {
    constructor(totalBlocks) {
        this.blockWearCount = new Array(totalBlocks).fill(0);
        this.addressMap = new Map();
    }

    writeLogicalBlock(logicalAddr, data) {
        // Find least worn physical block
        let physicalBlock = this.findMinWearBlock();
        
        // Update mapping and wear count
        this.addressMap.set(logicalAddr, physicalBlock);
        this.blockWearCount[physicalBlock]++;
        
        // Actual write to NAND
        nandProgram(physicalBlock, data);
    }
    
    findMinWearBlock() {
        return this.blockWearCount.indexOf(Math.min(...this.blockWearCount));
    }
}

Larger SSDs inherently provide more NAND blocks for wear leveling to utilize. For the same write workload:

• A 500GB SSD with 50% utilization has 250GB spare for wear leveling
• A 1TB SSD with 25% utilization has 750GB spare for wear leveling

The Terabytes Written (TBW) rating typically scales nearly linearly with capacity:

When designing storage-intensive applications:

// Bad practice: Constant small writes to same location
function logEvent(event) {
    fs.appendFileSync('/ssd/logs/app.log', event);
}

// Better practice: Buffer writes and rotate files
const writeBuffer = [];
let fileCounter = 0;

function bufferedWrite(event) {
    writeBuffer.push(event);
    if (writeBuffer.length >= 1000) {
        fs.writeFileSync(/ssd/logs/app-${fileCounter++}.log, writeBuffer.join('\n'));
        writeBuffer.length = 0;
    }
}

Linux developers can check SSD wear using smartctl:

#!/bin/bash
# Check SSD wear level
WEAR=$(sudo smartctl -a /dev/nvme0n1 | grep "Percentage Used" | awk '{print $4}')
echo "SSD wear: ${WEAR}%"

# Alternative using Node.js
const { execSync } = require('child_process');
const output = execSync('sudo smartctl -a /dev/nvme0n1');
const wearMatch = output.toString().match(/Percentage Used.*?(\d+)%/);
console.log(SSD wear: ${wearMatch ? wearMatch[1] : 'N/A'}%);

For Windows developers, PowerShell provides similar functionality:

Get-PhysicalDisk | Where-Object MediaType -eq "SSD" | 
Select-Object DeviceID, FriendlyName, @{Name="TotalBytes";Expression={$_.Size}}, 
@{Name="BytesWritten";Expression={(Get-Counter "\PhysicalDisk($($_.DeviceId)) Disk Write Bytes/sec").CounterSamples.CookedValue}}

Benchmark results showing performance degradation based on capacity utilization:

# FIO benchmark comparing different utilization levels
fio --name=test --filename=/ssd/testfile --size=10G --rw=randwrite \
    --ioengine=libaio --direct=1 --bs=4k --numjobs=16 --runtime=60 \
    --group_reporting --time_based

Typical results show:

• Empty drive: 50,000 IOPS
• 50% full: 45,000 IOPS
• 75% full: 35,000 IOPS
• 90% full: 20,000 IOPS

Modern SSDs implement wear leveling algorithms to distribute write operations evenly across all available NAND blocks. This prevents specific cells from wearing out prematurely. The controller maintains a logical-to-physical address mapping table (FTL - Flash Translation Layer) that dynamically rotates write locations.

Larger SSDs inherently have lower write amplification factors (WAF) because:

• More free blocks for garbage collection
• Reduced probability of write collisions
• Better parallelism across NAND die

Here's a simplified WAF calculation example:

def calculate_waf(ssd_capacity, op_size):
    # Theoretical model - actual implementation varies by controller
    overprovisioning = 0.07  # 7% standard OP
    usable_blocks = ssd_capacity * (1 - overprovisioning) 
    waf = 1 + (op_size / usable_blocks)
    return waf

# Compare 512GB vs 1TB SSD
print(f"512GB WAF: {calculate_waf(512, 4):.4f}")  # Typical 4KB operation
print(f"1TB WAF: {calculate_waf(1024, 4):.4f}")

Data from TechReport's 2015 SSD endurance experiment shows:

The larger drives lasted approximately proportional to their increased capacity.

Not all wear leveling implementations are equal. Enterprise SSDs (like Intel D7-P5510) use more sophisticated algorithms than consumer models. This C++ snippet demonstrates a basic wear-leveling simulation:

class WearLeveler {
public:
    WearLeveler(int blocks) : total_blocks(blocks) {
        wear_count.resize(blocks, 0);
    }
    
    int writeBlock(int logical_addr) {
        // Simple round-robin wear leveling
        static int current_block = 0;
        wear_count[current_block]++;
        current_block = (current_block + 1) % total_blocks;
        return current_block;
    }

private:
    int total_blocks;
    std::vector wear_count;
};

• For write-intensive workloads, choose SSDs with at least 25-30% free space
• NVMe drives typically handle wear leveling more efficiently than SATA
• Monitor SMART attributes (like Media_Wearout_Indicator) programmatically:

# Python example using smartmontools
import subprocess

def check_ssd_health(device):
    result = subprocess.run(['smartctl', '-A', device], capture_output=True)
    return parse_smart_attributes(result.stdout)

# Typical output includes:
# Wear_Leveling_Count    0x0032   100   100   000    Old_age   Always   -       123