LSI's CacheCade Pro 2.0 implements a hybrid caching architecture where SSDs supplement rather than replace the controller's NVRAM. The onboard NVRAM still plays critical roles:

// Pseudo-configuration showing cache hierarchy
RAID_Controller {
    NVRAM: 2GB (Battery-backed)
    Functions:
        - Write journaling
        - Transaction consistency
        - Emergency write buffer
    CacheCade_SSD: 400GB Intel S3700
    Functions:
        - Read cache (adaptive)
        - Write cache (optional)
        - Hot data tiering
}

While LSI allows consumer SSDs, enterprise workloads demand careful consideration:

# SSD endurance calculator for CacheCade
def calculate_endurance(ssd_tbw, daily_writes):
    days_to_wearout = ssd_tbw * 1000 / (daily_writes * 365)
    return days_to_wearout

# Example with 1TB DWPD drive:
print(calculate_endurance(10, 5))  # 5.48 years at 5TB/day
print(calculate_endurance(3, 10)) # 0.82 years at 10TB/day

The write path follows this sequence for data protection:

1. Host write → Controller NVRAM (immediate ack)
2. NVRAM → CacheCade SSD (async, 1-5 sec)
3. SSD → HDD array (background)

CacheCade uses a modified LRU algorithm with these enhancements:

// Simplified algorithm representation
class CacheCadeAlgorithm {
    constructor() {
        this.hotBlocks = new Map();
        this.candidateBlocks = new Set();
    }
    
    trackAccess(lba) {
        if (this.hotBlocks.has(lba)) {
            // Promote to MRU position
            this.hotBlocks.delete(lba);
            this.hotBlocks.set(lba, Date.now());
        } else if (++accessCount[lba] > THRESHOLD) {
            this.candidateBlocks.add(lba);
        }
    }
    
    promoteCandidates() {
        this.candidateBlocks.forEach(lba => {
            if (this.hotBlocks.size < MAX_CACHE_SIZE) {
                this.hotBlocks.set(lba, Date.now());
            }
        });
    }
}

Key metrics accessible via MegaRAID CLI:

# Sample monitoring commands
$ storcli /c0 show all | grep -i cache
CacheCade Hits: 2345678 (78.2%)
CacheCade Misses: 654321
SSD Wear Indicator: 15%

$ storcli /c0/v0 show ccstats
Read Acceleration: Enabled (92% hit rate)
Write Acceleration: Enabled (64% hit rate)
Dirty Cache Blocks: 1245

Optimal configuration for MySQL workloads:

# Recommended CacheCade 2.0 setup
RAID_Level = 10
SSD_Config = {
    "Model": "Intel DC S3700",
    "Capacity": "800GB",
    "RAID1_Mirror": True,
    "Read_Policy": "Adaptive",
    "Write_Policy": "WriteThrough",
    "SSD_Reserve": "15%"  # For overprovisioning
}

# Tuning parameters
echo "256" > /sys/block/cciss/c0d0/queue/nr_requests
echo "1024" > /sys/block/cciss/c0d0/queue/max_sectors_kb

Feature	CacheCade 2.0	ZFS L2ARC	HP SmartCache
Write Caching	Yes (optional)	No	Yes
Metadata Efficiency	8KB granularity	128KB default	64KB block
Endurance Mgmt	Basic wear-leveling	None	Advanced
Cache Coherency	Controller-managed	ZFS-managed	Battery-backed

For enterprise deployments, supplement CacheCade with these monitoring tools:

# Nagios plugin for CacheCade health
define command {
    command_name check_cachecade
    command_line /usr/lib64/nagios/plugins/check_storcli -C $ARG1$ -W $ARG2$ -c $ARG3$
}

---

LSI's CacheCade Pro 2.0 technology fundamentally transforms how SSDs interact with traditional RAID arrays. The system creates a two-layer caching architecture:

// Simplified architectural overview
SSD Cache Layer (CacheCade) → RAID Controller Cache (NVRAM) → HDD RAID Array

While CacheCade SSDs handle bulk caching operations, the controller's NVRAM serves critical functions:

• Power-loss protection for in-flight writes
• Ultra-low latency metadata operations
• Write coalescing before SSD commitment

Testing shows consumer SSDs can perform surprisingly well in CacheCade deployments:

// Sample write endurance calculation
const ssdCapacity = 480; // GB
const writeEndurance = 3000; // P/E cycles
const dailyWrites = 5; // Drive writes per day

const lifespanYears = (ssdCapacity * writeEndurance) / (ssdCapacity * dailyWrites * 365);
// Returns ~1.64 years for this configuration

CacheCade employs adaptive algorithms that differ from ZFS ARC/L2ARC:

• Frequency-based promotion (hot data tracking)
• Sequential read bypass (avoids cache pollution)
• Write-back with periodic destaging

The MegaCLI utility provides critical performance metrics:

# Check cache hit ratio
megacli -LDInfo -Lall -aALL | grep "Cache Hit Ratio"

# View SSD wear indicators
megacli -PDList -aALL | grep -E "Media Error|Predictive Failure"

# Force cache flush (benchmarking)
megacli -CacheCade -Flush -L0 -a0

This Python snippet simulates cache behavior analysis:

import pandas as pd
import numpy as np

def analyze_cache_patterns(log_file):
    data = pd.read_csv(log_file)
    read_hits = data['cache_hits'].sum()
    total_reads = data['total_ops'].sum()
    hit_ratio = (read_hits / total_reads) * 100
    
    # Identify working set size
    working_set = data['block_size'].unique().size * 512 / (1024**2) # MB
    return {'hit_ratio': hit_ratio, 'working_set_mb': working_set}

Testing shows significant improvements in specific workloads:

Workload	HDD Only	CacheCade	Improvement
Random 4K Read	1,200 IOPS	28,000 IOPS	23x
OLTP Pattern	450 IOPS	9,800 IOPS	21x
Sequential 1M	210 MB/s	225 MB/s	7%

Optimal CacheCade settings vary by workload:

# For database workloads (70% read / 30% write)
megacli -CacheCade -Modify -L0 -Imprint 70 -a0

# For write-heavy applications
megacli -CacheCade -Modify -L0 -WB -Imprint 30 -a0

# View current policy
megacli -CacheCade -GetPolicy -L0 -a0

CacheCade maintains data integrity through:

• Atomic write operations
• Background mirror rebuilding
• Automatic failback to HDD array