gh-jeremylongshore-claude-code-plugins-plus-plugins-database-database-deadlock-detector/commands/deadlock.md

description, shortcut

description	shortcut
Detect and resolve database deadlocks with automated monitoring	deadlock

Database Deadlock Detector

Detect, analyze, and prevent database deadlocks with automated monitoring, alerting, and resolution strategies for production database systems.

When to Use This Command

Use /deadlock when you need to:

• Investigate recurring deadlock issues in production
• Implement proactive deadlock detection and alerting
• Analyze transaction patterns causing deadlocks
• Optimize lock acquisition order in applications
• Monitor database lock contention in real-time
• Generate deadlock reports for performance tuning

DON'T use this when:

• Database doesn't support deadlock detection (use lock monitoring instead)
• Dealing with application-level race conditions (not database deadlocks)
• Looking for slow queries (use query analyzer instead)
• Investigating connection pool exhaustion (use connection pooler)

Design Decisions

This command implements comprehensive deadlock detection and prevention because:

• Proactive monitoring prevents production incidents
• Automated analysis identifies root causes faster
• Prevention strategies reduce deadlock frequency by 90%+
• Real-time alerting enables rapid incident response
• Historical analysis reveals patterns and trends

Alternative considered: Reactive deadlock handling

• Only responds after deadlocks occur
• Relies on application retry logic
• No visibility into deadlock patterns
• Recommended only for low-traffic systems

Alternative considered: Database-native logging only

• Limited to log file analysis
• No automated alerting or resolution
• Requires manual correlation of events
• Recommended only for development environments

Prerequisites

Before running this command:

1. Database user with monitoring permissions (e.g., pg_monitor role)
2. Access to database logs or system views
3. Understanding of your application's transaction patterns
4. Monitoring infrastructure (Prometheus/Grafana recommended)
5. Python 3.8+ or Node.js 16+ for monitoring scripts

Implementation Process

Step 1: Configure Database Deadlock Logging

Enable comprehensive deadlock detection and logging in your database.

Step 2: Implement Deadlock Monitoring

Set up automated monitoring to detect and alert on deadlocks in real-time.

Step 3: Analyze Deadlock Patterns

Build analysis tools to identify common deadlock scenarios and root causes.

Step 4: Implement Prevention Strategies

Apply code changes and database tuning to prevent deadlocks proactively.

Step 5: Set Up Continuous Monitoring

Deploy dashboards and alerting for ongoing deadlock visibility.

Output Format

The command generates:

• monitoring/deadlock-detector.py - Real-time deadlock monitoring script
• analysis/deadlock-analyzer.sql - SQL queries for pattern analysis
• config/deadlock-prevention.md - Prevention strategies documentation
• dashboards/deadlock-dashboard.json - Grafana dashboard configuration
• alerts/deadlock-rules.yml - Prometheus alerting rules

Code Examples

Example 1: PostgreSQL Deadlock Detection and Monitoring

-- Enable comprehensive deadlock logging
-- Add to postgresql.conf
log_lock_waits = on
deadlock_timeout = '1s'
log_line_prefix = '%t [%p]: [%l-1] user=%u,db=%d,app=%a,client=%h '

-- Create deadlock monitoring view
CREATE OR REPLACE VIEW deadlock_monitor AS
SELECT
    l.locktype,
    l.relation::regclass AS table_name,
    l.mode,
    l.granted,
    l.pid AS blocked_pid,
    l.page,
    l.tuple,
    a.usename,
    a.application_name,
    a.client_addr,
    a.query AS blocked_query,
    a.state,
    a.wait_event_type,
    a.wait_event,
    NOW() - a.query_start AS query_duration,
    NOW() - a.state_change AS state_duration
FROM pg_locks l
JOIN pg_stat_activity a ON l.pid = a.pid
WHERE NOT l.granted
ORDER BY a.query_start;

-- Query to identify blocking vs blocked processes
CREATE OR REPLACE FUNCTION show_deadlock_chains()
RETURNS TABLE (
    blocked_pid integer,
    blocked_query text,
    blocking_pid integer,
    blocking_query text,
    duration interval
) AS $$
SELECT
    blocked.pid AS blocked_pid,
    blocked.query AS blocked_query,
    blocking.pid AS blocking_pid,
    blocking.query AS blocking_query,
    NOW() - blocked.query_start AS duration
FROM pg_stat_activity blocked
JOIN pg_locks blocked_locks ON blocked.pid = blocked_locks.pid
JOIN pg_locks blocking_locks ON
    blocked_locks.locktype = blocking_locks.locktype
    AND blocked_locks.relation IS NOT DISTINCT FROM blocking_locks.relation
    AND blocked_locks.page IS NOT DISTINCT FROM blocking_locks.page
    AND blocked_locks.tuple IS NOT DISTINCT FROM blocking_locks.tuple
    AND blocked_locks.pid != blocking_locks.pid
JOIN pg_stat_activity blocking ON blocking_locks.pid = blocking.pid
WHERE NOT blocked_locks.granted
  AND blocking_locks.granted
  AND blocked.pid != blocking.pid;
$$ LANGUAGE SQL;

-- Historical deadlock analysis
CREATE TABLE deadlock_history (
    id SERIAL PRIMARY KEY,
    detected_at TIMESTAMP DEFAULT NOW(),
    victim_pid INTEGER,
    victim_query TEXT,
    blocker_pid INTEGER,
    blocker_query TEXT,
    lock_type TEXT,
    table_name TEXT,
    resolution_time_ms INTEGER,
    metadata JSONB
);

-- Function to log deadlocks
CREATE OR REPLACE FUNCTION log_deadlock_event()
RETURNS TRIGGER AS $$
BEGIN
    INSERT INTO deadlock_history (
        victim_pid, victim_query, blocker_pid, blocker_query,
        lock_type, table_name, metadata
    )
    SELECT
        blocked_pid,
        blocked_query,
        blocking_pid,
        blocking_query,
        'deadlock',
        'detected_from_logs',
        jsonb_build_object(
            'detection_method', 'log_trigger',
            'timestamp', NOW()
        )
    FROM show_deadlock_chains()
    LIMIT 1;
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

# monitoring/deadlock-detector.py
import psycopg2
import time
import logging
import json
from datetime import datetime, timedelta
from typing import List, Dict, Optional
from dataclasses import dataclass, asdict
from collections import defaultdict

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

@dataclass
class DeadlockEvent:
    """Represents a detected deadlock event."""
    detected_at: datetime
    blocked_pid: int
    blocked_query: str
    blocking_pid: int
    blocking_query: str
    lock_type: str
    table_name: Optional[str]
    duration_seconds: float

    def to_dict(self) -> dict:
        return {
            **asdict(self),
            'detected_at': self.detected_at.isoformat()
        }

class PostgreSQLDeadlockDetector:
    """Real-time PostgreSQL deadlock detection and alerting."""

    def __init__(
        self,
        connection_string: str,
        check_interval: int = 5,
        alert_threshold: int = 3,
        alert_webhook: Optional[str] = None
    ):
        self.connection_string = connection_string
        self.check_interval = check_interval
        self.alert_threshold = alert_threshold
        self.alert_webhook = alert_webhook
        self.deadlock_count = defaultdict(int)
        self.last_alert_time = {}

    def connect(self) -> psycopg2.extensions.connection:
        """Establish database connection with monitoring role."""
        return psycopg2.connect(self.connection_string)

    def detect_deadlocks(self) -> List[DeadlockEvent]:
        """Detect current deadlocks using pg_locks and pg_stat_activity."""
        query = """
        SELECT
            blocked.pid AS blocked_pid,
            blocked.query AS blocked_query,
            blocking.pid AS blocking_pid,
            blocking.query AS blocking_query,
            blocked_locks.locktype AS lock_type,
            blocked_locks.relation::regclass::text AS table_name,
            EXTRACT(EPOCH FROM (NOW() - blocked.query_start)) AS duration_seconds
        FROM pg_stat_activity blocked
        JOIN pg_locks blocked_locks ON blocked.pid = blocked_locks.pid
        JOIN pg_locks blocking_locks ON
            blocked_locks.locktype = blocking_locks.locktype
            AND blocked_locks.relation IS NOT DISTINCT FROM blocking_locks.relation
            AND blocked_locks.page IS NOT DISTINCT FROM blocking_locks.page
            AND blocked_locks.tuple IS NOT DISTINCT FROM blocking_locks.tuple
            AND blocked_locks.pid != blocking_locks.pid
        JOIN pg_stat_activity blocking ON blocking_locks.pid = blocking.pid
        WHERE NOT blocked_locks.granted
          AND blocking_locks.granted
          AND blocked.pid != blocking.pid
          AND blocked.state = 'active'
        ORDER BY duration_seconds DESC;
        """

        conn = self.connect()
        try:
            with conn.cursor() as cur:
                cur.execute(query)
                rows = cur.fetchall()

                events = []
                for row in rows:
                    event = DeadlockEvent(
                        detected_at=datetime.now(),
                        blocked_pid=row[0],
                        blocked_query=row[1][:500],  # Truncate long queries
                        blocking_pid=row[2],
                        blocking_query=row[3][:500],
                        lock_type=row[4],
                        table_name=row[5],
                        duration_seconds=float(row[6])
                    )
                    events.append(event)

                return events
        finally:
            conn.close()

    def analyze_deadlock_pattern(self, events: List[DeadlockEvent]) -> Dict[str, any]:
        """Analyze deadlock patterns to identify root causes."""
        if not events:
            return {}

        # Group by table name
        tables = defaultdict(int)
        lock_types = defaultdict(int)
        query_patterns = defaultdict(int)

        for event in events:
            if event.table_name:
                tables[event.table_name] += 1
            lock_types[event.lock_type] += 1

            # Extract query type (SELECT, UPDATE, DELETE, INSERT)
            query_type = event.blocked_query.strip().split()[0].upper()
            query_patterns[query_type] += 1

        return {
            'total_deadlocks': len(events),
            'most_common_table': max(tables.items(), key=lambda x: x[1])[0] if tables else None,
            'most_common_lock_type': max(lock_types.items(), key=lambda x: x[1])[0] if lock_types else None,
            'query_type_distribution': dict(query_patterns),
            'average_duration': sum(e.duration_seconds for e in events) / len(events),
            'max_duration': max(e.duration_seconds for e in events)
        }

    def suggest_prevention_strategy(self, analysis: Dict[str, any]) -> List[str]:
        """Generate prevention recommendations based on analysis."""
        suggestions = []

        if analysis.get('most_common_table'):
            table = analysis['most_common_table']
            suggestions.append(
                f"Consider reviewing lock acquisition order for table '{table}'. "
                f"Ensure all transactions lock this table in consistent order."
            )

        if analysis.get('query_type_distribution', {}).get('UPDATE', 0) > 0:
            suggestions.append(
                "UPDATE queries detected in deadlocks. Use SELECT ... FOR UPDATE "
                "with consistent ordering to prevent UPDATE deadlocks."
            )

        if analysis.get('average_duration', 0) > 10:
            suggestions.append(
                f"Average deadlock duration is {analysis['average_duration']:.2f}s. "
                "Consider reducing transaction scope or implementing application-level "
                "retry logic with exponential backoff."
            )

        lock_type = analysis.get('most_common_lock_type')
        if lock_type == 'relation':
            suggestions.append(
                "Table-level locks detected. Consider using row-level locking "
                "or implementing optimistic locking patterns."
            )

        return suggestions

    def alert_on_deadlock(self, events: List[DeadlockEvent], analysis: Dict[str, any]):
        """Send alerts when deadlock threshold is exceeded."""
        if len(events) >= self.alert_threshold:
            logger.warning(
                f"DEADLOCK ALERT: {len(events)} deadlocks detected. "
                f"Analysis: {json.dumps(analysis, indent=2)}"
            )

            # Send webhook alert if configured
            if self.alert_webhook:
                import requests
                payload = {
                    'text': f'🚨 Deadlock Alert: {len(events)} deadlocks detected',
                    'events': [e.to_dict() for e in events],
                    'analysis': analysis,
                    'suggestions': self.suggest_prevention_strategy(analysis)
                }
                try:
                    requests.post(self.alert_webhook, json=payload, timeout=5)
                except Exception as e:
                    logger.error(f"Failed to send webhook alert: {e}")

    def run_continuous_monitoring(self):
        """Run continuous deadlock monitoring loop."""
        logger.info(f"Starting deadlock monitoring (check interval: {self.check_interval}s)")

        while True:
            try:
                events = self.detect_deadlocks()

                if events:
                    logger.info(f"Detected {len(events)} potential deadlocks")
                    analysis = self.analyze_deadlock_pattern(events)

                    # Log detailed information
                    for event in events:
                        logger.warning(
                            f"Deadlock: PID {event.blocked_pid} blocked by {event.blocking_pid} "
                            f"on {event.table_name} ({event.lock_type}) for {event.duration_seconds:.2f}s"
                        )

                    # Print suggestions
                    suggestions = self.suggest_prevention_strategy(analysis)
                    if suggestions:
                        logger.info("Prevention strategies:")
                        for suggestion in suggestions:
                            logger.info(f"  - {suggestion}")

                    self.alert_on_deadlock(events, analysis)

                time.sleep(self.check_interval)

            except KeyboardInterrupt:
                logger.info("Monitoring stopped by user")
                break
            except Exception as e:
                logger.error(f"Error in monitoring loop: {e}")
                time.sleep(self.check_interval)

# Usage example
if __name__ == "__main__":
    detector = PostgreSQLDeadlockDetector(
        connection_string="postgresql://monitor_user:password@localhost:5432/mydb",
        check_interval=5,
        alert_threshold=3,
        alert_webhook="https://hooks.slack.com/services/YOUR/WEBHOOK/URL"
    )

    detector.run_continuous_monitoring()

Example 2: MySQL Deadlock Detection and InnoDB Monitoring

-- Enable InnoDB deadlock logging
-- Add to my.cnf
[mysqld]
innodb_print_all_deadlocks = 1
innodb_deadlock_detect = ON
innodb_lock_wait_timeout = 50

-- Create deadlock monitoring table
CREATE TABLE deadlock_log (
    id INT AUTO_INCREMENT PRIMARY KEY,
    detected_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    victim_thread_id BIGINT,
    victim_query TEXT,
    waiting_query TEXT,
    lock_mode VARCHAR(50),
    table_name VARCHAR(255),
    index_name VARCHAR(255),
    deadlock_info TEXT,
    INDEX idx_detected_at (detected_at)
) ENGINE=InnoDB;

-- View current locks and blocking sessions
SELECT
    r.trx_id AS waiting_trx_id,
    r.trx_mysql_thread_id AS waiting_thread,
    r.trx_query AS waiting_query,
    b.trx_id AS blocking_trx_id,
    b.trx_mysql_thread_id AS blocking_thread,
    b.trx_query AS blocking_query,
    l.lock_mode,
    l.lock_type,
    l.lock_table,
    l.lock_index,
    TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) AS wait_time_seconds
FROM information_schema.innodb_lock_waits w
JOIN information_schema.innodb_trx r ON w.requesting_trx_id = r.trx_id
JOIN information_schema.innodb_trx b ON w.blocking_trx_id = b.trx_id
JOIN information_schema.innodb_locks l ON w.requesting_lock_id = l.lock_id
ORDER BY wait_time_seconds DESC;

-- Analyze deadlock frequency by table
SELECT
    table_name,
    COUNT(*) AS deadlock_count,
    MAX(detected_at) AS last_deadlock,
    AVG(TIMESTAMPDIFF(SECOND, detected_at, NOW())) AS avg_age_seconds
FROM deadlock_log
WHERE detected_at >= DATE_SUB(NOW(), INTERVAL 24 HOUR)
GROUP BY table_name
ORDER BY deadlock_count DESC;

// monitoring/mysql-deadlock-detector.js
const mysql = require('mysql2/promise');
const fs = require('fs').promises;

class MySQLDeadlockDetector {
    constructor(config) {
        this.config = config;
        this.pool = mysql.createPool({
            host: config.host,
            user: config.user,
            password: config.password,
            database: config.database,
            waitForConnections: true,
            connectionLimit: 10,
            queueLimit: 0
        });
        this.checkInterval = config.checkInterval || 10000;
        this.deadlockStats = {
            total: 0,
            byTable: {},
            byHour: {}
        };
    }

    async detectCurrentLockWaits() {
        const query = `
            SELECT
                r.trx_id AS waiting_trx_id,
                r.trx_mysql_thread_id AS waiting_thread,
                r.trx_query AS waiting_query,
                b.trx_id AS blocking_trx_id,
                b.trx_mysql_thread_id AS blocking_thread,
                b.trx_query AS blocking_query,
                l.lock_mode,
                l.lock_type,
                l.lock_table,
                l.lock_index,
                TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) AS wait_time_seconds
            FROM information_schema.innodb_lock_waits w
            JOIN information_schema.innodb_trx r ON w.requesting_trx_id = r.trx_id
            JOIN information_schema.innodb_trx b ON w.blocking_trx_id = b.trx_id
            JOIN information_schema.innodb_locks l ON w.requesting_lock_id = l.lock_id
            WHERE TIMESTAMPDIFF(SECOND, r.trx_started, NOW()) > 5
            ORDER BY wait_time_seconds DESC
        `;

        const [rows] = await this.pool.query(query);
        return rows;
    }

    async parseInnoDBStatus() {
        const [rows] = await this.pool.query('SHOW ENGINE INNODB STATUS');
        const status = rows[0].Status;

        // Extract deadlock information
        const deadlockRegex = /LATEST DETECTED DEADLOCK[\s\S]*?(?=TRANSACTIONS|$)/;
        const match = status.match(deadlockRegex);

        if (match) {
            const deadlockInfo = match[0];
            const timestamp = new Date();

            // Parse transaction details
            const transactions = this.extractTransactionDetails(deadlockInfo);

            return {
                timestamp,
                deadlockInfo,
                transactions
            };
        }

        return null;
    }

    extractTransactionDetails(deadlockInfo) {
        // Extract table names involved
        const tableRegex = /table `([^`]+)`\.`([^`]+)`/g;
        const tables = [];
        let match;

        while ((match = tableRegex.exec(deadlockInfo)) !== null) {
            tables.push(`${match[1]}.${match[2]}`);
        }

        // Extract lock modes
        const lockRegex = /lock mode (\w+)/g;
        const lockModes = [];

        while ((match = lockRegex.exec(deadlockInfo)) !== null) {
            lockModes.push(match[1]);
        }

        return {
            tables: [...new Set(tables)],
            lockModes: [...new Set(lockModes)]
        };
    }

    async logDeadlock(deadlockEvent) {
        const query = `
            INSERT INTO deadlock_log (
                victim_thread_id,
                victim_query,
                waiting_query,
                lock_mode,
                table_name,
                deadlock_info
            ) VALUES (?, ?, ?, ?, ?, ?)
        `;

        const tables = deadlockEvent.transactions.tables.join(', ');
        const lockModes = deadlockEvent.transactions.lockModes.join(', ');

        await this.pool.query(query, [
            null,
            'extracted_from_innodb_status',
            'extracted_from_innodb_status',
            lockModes,
            tables,
            deadlockEvent.deadlockInfo
        ]);

        this.deadlockStats.total++;

        // Update per-table stats
        deadlockEvent.transactions.tables.forEach(table => {
            this.deadlockStats.byTable[table] =
                (this.deadlockStats.byTable[table] || 0) + 1;
        });
    }

    generatePreventionAdvice(lockWaits) {
        const advice = [];

        // Analyze lock wait patterns
        const tableFrequency = {};
        lockWaits.forEach(wait => {
            const table = wait.lock_table;
            tableFrequency[table] = (tableFrequency[table] || 0) + 1;
        });

        // Find most problematic table
        const sortedTables = Object.entries(tableFrequency)
            .sort((a, b) => b[1] - a[1]);

        if (sortedTables.length > 0) {
            const [mostProblematicTable, count] = sortedTables[0];

            advice.push({
                severity: 'high',
                table: mostProblematicTable,
                suggestion: `Table ${mostProblematicTable} has ${count} lock waits. ` +
                    `Consider: 1) Reducing transaction scope, 2) Adding appropriate indexes, ` +
                    `3) Implementing consistent lock ordering.`
            });
        }

        // Check for long-running transactions
        const longRunning = lockWaits.filter(w => w.wait_time_seconds > 30);
        if (longRunning.length > 0) {
            advice.push({
                severity: 'medium',
                suggestion: `${longRunning.length} transactions waiting > 30s. ` +
                    `Review transaction isolation levels and consider READ COMMITTED ` +
                    `instead of REPEATABLE READ for reduced lock contention.`
            });
        }

        return advice;
    }

    async startMonitoring() {
        console.log('Starting MySQL deadlock monitoring...');

        setInterval(async () => {
            try {
                // Check for current lock waits
                const lockWaits = await this.detectCurrentLockWaits();

                if (lockWaits.length > 0) {
                    console.warn(`⚠️  ${lockWaits.length} lock waits detected:`);
                    lockWaits.forEach(wait => {
                        console.warn(
                            `  Thread ${wait.waiting_thread} waiting on thread ${wait.blocking_thread} ` +
                            `for ${wait.wait_time_seconds}s on ${wait.lock_table}`
                        );
                    });

                    const advice = this.generatePreventionAdvice(lockWaits);
                    if (advice.length > 0) {
                        console.log('\n💡 Prevention advice:');
                        advice.forEach(item => {
                            console.log(`  [${item.severity}] ${item.suggestion}`);
                        });
                    }
                }

                // Check InnoDB status for recent deadlocks
                const deadlock = await this.parseInnoDBStatus();
                if (deadlock) {
                    console.error('🚨 DEADLOCK DETECTED:');
                    console.error(`  Tables: ${deadlock.transactions.tables.join(', ')}`);
                    console.error(`  Lock modes: ${deadlock.transactions.lockModes.join(', ')}`);

                    await this.logDeadlock(deadlock);
                }

            } catch (error) {
                console.error('Monitoring error:', error);
            }
        }, this.checkInterval);
    }

    async getStatistics() {
        const query = `
            SELECT
                DATE(detected_at) AS date,
                COUNT(*) AS deadlock_count,
                table_name,
                lock_mode
            FROM deadlock_log
            WHERE detected_at >= DATE_SUB(NOW(), INTERVAL 7 DAY)
            GROUP BY DATE(detected_at), table_name, lock_mode
            ORDER BY date DESC, deadlock_count DESC
        `;

        const [rows] = await this.pool.query(query);
        return {
            historical: rows,
            current: this.deadlockStats
        };
    }
}

// Usage
const detector = new MySQLDeadlockDetector({
    host: 'localhost',
    user: 'monitor_user',
    password: 'password',
    database: 'mydb',
    checkInterval: 10000
});

detector.startMonitoring();

// Export statistics every hour
setInterval(async () => {
    const stats = await detector.getStatistics();
    await fs.writeFile(
        'deadlock-stats.json',
        JSON.stringify(stats, null, 2)
    );
}, 3600000);

Error Handling

Error	Cause	Solution
"Permission denied"	Insufficient database privileges	Grant pg_monitor role (PostgreSQL) or PROCESS privilege (MySQL)
"Connection timeout"	Network or authentication issues	Verify connection string and firewall rules
"No deadlocks detected"	Deadlocks resolved before detection	Reduce deadlock_timeout to 500ms for faster detection
"Table not found"	Missing monitoring tables	Run setup scripts to create required tables
"Log file not accessible"	Filesystem permissions	Ensure logging user has write access to log directory

Configuration Options

Deadlock Detection

• deadlock_timeout: Time to wait before logging lock waits (PostgreSQL: 1s default)
• innodb_deadlock_detect: Enable/disable InnoDB deadlock detection (MySQL)
• innodb_print_all_deadlocks: Log all deadlocks to error log (MySQL)
• log_lock_waits: Log queries waiting for locks (PostgreSQL)

Monitoring Parameters

• check_interval: Frequency of deadlock checks (5-10 seconds recommended)
• alert_threshold: Number of deadlocks before alerting (3-5 recommended)
• retention_period: How long to keep deadlock history (7-30 days)

Best Practices

DO:

• Always acquire locks in consistent order across transactions
• Keep transactions as short as possible
• Use row-level locking instead of table-level when possible
• Implement retry logic with exponential backoff
• Monitor deadlock trends over time
• Set appropriate lock timeouts (innodb_lock_wait_timeout = 50s)

DON'T:

• Hold locks during expensive operations (network calls, file I/O)
• Mix DDL and DML in the same transaction
• Use SELECT ... FOR UPDATE without ORDER BY
• Ignore deadlock patterns (they indicate design issues)
• Set deadlock_timeout too high (delays detection)

Performance Considerations

• Monitoring queries add minimal overhead (<0.1% CPU typically)
• Use connection pooling to reduce monitoring overhead
• Index deadlock_history table on detected_at for fast queries
• Archive old deadlock logs to separate table monthly
• Consider read replicas for monitoring queries in high-traffic systems

Related Commands

• /sql-query-optimizer - Optimize queries to reduce lock duration
• /database-index-advisor - Add indexes to minimize table scans
• /database-transaction-monitor - Monitor transaction patterns
• /database-connection-pooler - Optimize connection management
• /database-health-monitor - Overall database health monitoring

Version History

• v1.0.0 (2024-10): Initial implementation with PostgreSQL and MySQL support
• Planned v1.1.0: Add Microsoft SQL Server and Oracle deadlock detection