Performance Tuning

Optimize SLOS for High-Traffic Websites and Large Datasets

Performance Benchmarking

Step 1: Establish Performance Baselines

`
SLOS → Advanced → Performance → Benchmarking
`

Performance Baseline Report:
`json
{
“benchmark_date”: “2024-12-31T12:00:00Z”,
“test_environment”: {
“server_type”: “production”,
“concurrency_level”: 100,
“test_duration”: 300,
“datasetsize”: “1Mconsentrecords”
},
“baseline_metrics”: {
“pageloadtime”: {
“average”: “1.2s”,
“95th_percentile”: “2.8s”,
“99th_percentile”: “4.5s”
},
“apiresponsetime”: {
“consent_api”: “150ms”,
“admin_api”: “200ms”,
“report_api”: “850ms”
},
“database_performance”: {
“queriespersecond”: 450,
“slow_queries”: 2,
“connectionpoolusage”: “75%”
},
“resource_usage”: {
“cpu_usage”: “45%”,
“memory_usage”: “2.1GB”,
“disk_io”: “120MB/s”
}
},
“performance_targets”: {
“pageloadtime”: “< 2.0s", "apiresponsetime”: “< 500ms", "database_qps": "> 1000″,
“resourceusage”: “< 70%average”
}
}
`

Step 2: Load Testing Setup

`
SLOS → Advanced → Performance → Load Testing
`

Load Testing Configuration:
`json
{
“testing_tools”: [“k6”, “locust”, “jmeter”],
“test_scenarios”: [
{
“scenario”: “peak_traffic”,
“description”: “Simulate peak website traffic with consent interactions”,
“user_count”: 1000,
“rampuptime”: 60,
“duration”: 600,
“actions”: [“pageviews”, “consentinteractions”, “api_calls”]
},
{
“scenario”: “dataheavyoperations”,
“description”: “Test performance with large dataset operations”,
“user_count”: 50,
“duration”: 300,
“actions”: [“bulkconsentexport”, “largereports”, “datamigration”]
},
{
“scenario”: “compliance_scanning”,
“description”: “Test accessibility scanning performance”,
“user_count”: 10,
“duration”: 1800,
“actions”: [“fullsitescans”, “continuous_monitoring”]
}
],
“monitoring_metrics”: [
“response_time”,
“error_rate”,
“throughput”,
“resource_utilization”,
“database_performance”
],
“alert_thresholds”: {
“responsetime95th”: 3000,
“error_rate”: 0.05,
“cpu_usage”: 80,
“memory_usage”: 85
}
}
`

Step 3: Performance Monitoring Implementation

`php
// Advanced performance monitoring
class PerformanceMonitor {
private $metrics = [];
private $thresholds = [
‘response_time’ => 2000, // ms
‘memory_usage’ => 128 1024 1024, // 128MB
‘cpu_time’ => 1.0, // seconds
‘dbquerytime’ => 100 // ms
];

public function startMonitoring($operation_name) {
$this->metrics[$operation_name] = [
‘start_time’ => microtime(true),
‘startmemory’ => memoryget_usage(true),
‘startcpu’ => getrusage()[‘ruutime.tvsec’] + getrusage()[‘ruutime.tv_usec’] / 1000000,
‘db_queries’ => 0,
‘dbquerytime’ => 0
];

// Hook into database queries
add_filter(‘query’, [$this, ‘trackDatabaseQuery’]);
}

public function stopMonitoring($operation_name) {
if (!isset($this->metrics[$operation_name])) {
return null;
}

$metrics = $this->metrics[$operation_name];
$end_time = microtime(true);
$endmemory = memoryget_usage(true);
$endcpu = getrusage()[‘ruutime.tvsec’] + getrusage()[‘ruutime.tv_usec’] / 1000000;

$result = [
‘operation’ => $operation_name,
‘totaltime’ => ($endtime – $metrics[‘start_time’]) * 1000, // ms
‘memoryused’ => $endmemory – $metrics[‘start_memory’],
‘cputime’ => $endcpu – $metrics[‘start_cpu’],
‘dbqueries’ => $metrics[‘dbqueries’],
‘dbavgquerytime’ => $metrics[‘dbqueries’] > 0 ? $metrics[‘dbquerytime’] / $metrics[‘db_queries’] : 0,
‘timestamp’ => time()
];

// Check thresholds and alert if necessary
$this->checkThresholds($result);

// Store metrics for analysis
$this->storeMetrics($result);

unset($this->metrics[$operation_name]);

return $result;
}

public function trackDatabaseQuery($query) {
if (!empty($this->metrics)) {
$query_start = microtime(true);
// Note: This is a simplified tracking. In practice, you’d need to hook into wpdb
$querytime = (microtime(true) – $querystart) * 1000;

foreach ($this->metrics as $operation => $data) {
$this->metrics[$operation][‘db_queries’]++;
$this->metrics[$operation][‘dbquerytime’] += $query_time;
}
}

return $query;
}

private function checkThresholds($metrics) {
$alerts = [];

if ($metrics[‘totaltime’] > $this->thresholds[‘responsetime’]) {
$alerts[] = “Response time exceeded: {$metrics[‘total_time’]}ms”;
}

if ($metrics[‘memoryused’] > $this->thresholds[‘memoryusage’]) {
$alerts[] = “Memory usage exceeded: ” . ($metrics[‘memory_used’] / 1024 / 1024) . “MB”;
}

if ($metrics[‘cputime’] > $this->thresholds[‘cputime’]) {
$alerts[] = “CPU time exceeded: {$metrics[‘cpu_time’]}s”;
}

if ($metrics[‘dbavgquerytime’] > $this->thresholds[‘dbquery_time’]) {
$alerts[] = “Database query time exceeded: {$metrics[‘dbavgquery_time’]}ms”;
}

if (!empty($alerts)) {
$this->sendPerformanceAlert($metrics[‘operation’], $alerts);
}
}

private function sendPerformanceAlert($operation, $alerts) {
$subject = “Performance Alert: {$operation}”;
$message = “Performance thresholds exceeded for operation ‘{$operation}’:\n\n” .
implode(“\n”, $alerts) . “\n\n” .
“Timestamp: ” . date(‘Y-m-d H:i:s’);

wpmail(getoption(‘admin_email’), $subject, $message);
}

private function storeMetrics($metrics) {
global $wpdb;

$wpdb->insert(‘wpslosperformance_metrics’, [
‘operation’ => $metrics[‘operation’],
‘totaltime’ => $metrics[‘totaltime’],
‘memoryused’ => $metrics[‘memoryused’],
‘cputime’ => $metrics[‘cputime’],
‘dbqueries’ => $metrics[‘dbqueries’],
‘dbavgquerytime’ => $metrics[‘dbavgquerytime’],
‘timestamp’ => date(‘Y-m-d H:i:s’, $metrics[‘timestamp’])
]);
}

public function getPerformanceReport($time_range = ’24 hours’) {
global $wpdb;

$timecondition = $this->getTimeCondition($timerange);

$report = $wpdb->get_results($wpdb->prepare(“
SELECT
operation,
COUNT(*) as execution_count,
AVG(totaltime) as avgresponse_time,
MAX(totaltime) as maxresponse_time,
AVG(memoryused) as avgmemory_usage,
AVG(dbqueries) as avgdb_queries,
AVG(dbavgquerytime) as avgquery_time
FROM wpslosperformance_metrics
WHERE timestamp >= %s
GROUP BY operation
ORDER BY avgresponsetime DESC
“, $time_condition));

return $report;
}

private function getTimeCondition($time_range) {
$now = current_time(‘mysql’);

switch ($time_range) {
case ‘1 hour’:
return date(‘Y-m-d H:i:s’, strtotime(‘-1 hour’, strtotime($now)));
case ’24 hours’:
return date(‘Y-m-d H:i:s’, strtotime(‘-24 hours’, strtotime($now)));
case ‘7 days’:
return date(‘Y-m-d H:i:s’, strtotime(‘-7 days’, strtotime($now)));
case ’30 days’:
return date(‘Y-m-d H:i:s’, strtotime(‘-30 days’, strtotime($now)));
default:
return date(‘Y-m-d H:i:s’, strtotime(‘-24 hours’, strtotime($now)));
}
}

public function getBottlenecks() {
$report = $this->getPerformanceReport();

$bottlenecks = [];

foreach ($report as $metric) {
if ($metric->avgresponsetime > $this->thresholds[‘response_time’]) {
$bottlenecks[] = [
‘operation’ => $metric->operation,
‘issue’ => ‘slow_response’,
‘value’ => $metric->avgresponsetime,
‘threshold’ => $this->thresholds[‘response_time’]
];
}

if ($metric->avgmemoryusage > $this->thresholds[‘memory_usage’]) {
$bottlenecks[] = [
‘operation’ => $metric->operation,
‘issue’ => ‘high_memory’,
‘value’ => $metric->avgmemoryusage,
‘threshold’ => $this->thresholds[‘memory_usage’]
];
}

if ($metric->avgquerytime > $this->thresholds[‘dbquerytime’]) {
$bottlenecks[] = [
‘operation’ => $metric->operation,
‘issue’ => ‘slow_queries’,
‘value’ => $metric->avgquerytime,
‘threshold’ => $this->thresholds[‘dbquerytime’]
];
}
}

return $bottlenecks;
}
}
`

Caching Strategy Optimization

Step 1: Multi-Layer Caching Architecture

`
SLOS → Advanced → Performance → Caching Strategy
`

Caching Architecture:
`json
{
“cache_layers”: [
{
“layer”: “browser_cache”,
“type”: “static_assets”,
“ttl”: “1_year”,
“coverage”: “cssjsimages”
},
{
“layer”: “cdn_cache”,
“type”: “dynamic_content”,
“ttl”: “1_hour”,
“coverage”: “api_responses”
},
{
“layer”: “application_cache”,
“type”: “object_cache”,
“ttl”: “5_minutes”,
“coverage”: “database_queries”
},
{
“layer”: “database_cache”,
“type”: “query_cache”,
“ttl”: “10_minutes”,
“coverage”: “frequent_queries”
},
{
“layer”: “opcode_cache”,
“type”: “php_cache”,
“ttl”: “persistent”,
“coverage”: “compiled_php”
}
],
“cachehitratios”: {
“target”: “85%”,
“current”: “78%”,
“improvement_needed”: true
},
“cacheinvalidationstrategy”: {
“method”: “selective_invalidation”,
“frequency”: “real_time”,
“fallback”: “time_based”
}
}
`

Step 2: Advanced Caching Implementation

`php
// Advanced caching system
class AdvancedCacheManager {
private $cache_backends = [];
private $cache_groups = [
‘consent_data’ => 300, // 5 minutes
‘user_preferences’ => 600, // 10 minutes
‘reports’ => 1800, // 30 minutes
‘static_content’ => 3600 // 1 hour
];

public function __construct() {
$this->initializeCacheBackends();
}

private function initializeCacheBackends() {
// Redis for high-performance caching
if (class_exists(‘Redis’)) {
$this->cache_backends[‘redis’] = new Redis();
$this->cache_backends[‘redis’]->connect(‘127.0.0.1’, 6379);
}

// Memcached as fallback
if (classexists(‘Memcached’) && !$this->cachebackends[‘redis’]) {
$this->cache_backends[‘memcached’] = new Memcached();
$this->cache_backends[‘memcached’]->addServer(‘127.0.0.1’, 11211);
}

// WordPress object cache as final fallback
$this->cachebackends[‘wordpress’] = ‘wpcache’;
}

public function get($key, $group = ‘default’) {
$cache_key = $this->generateCacheKey($key, $group);

// Try Redis first
if (isset($this->cache_backends[‘redis’])) {
$result = $this->cachebackends[‘redis’]->get($cachekey);
if ($result !== false) {
$this->updateCacheMetrics($group, ‘hit’);
return $result;
}
}

// Try Memcached
if (isset($this->cache_backends[‘memcached’])) {
$result = $this->cachebackends[‘memcached’]->get($cachekey);
if ($result !== false) {
$this->updateCacheMetrics($group, ‘hit’);
return $result;
}
}

// Try WordPress cache
$result = wpcacheget($cache_key, $group);
if ($result !== false) {
$this->updateCacheMetrics($group, ‘hit’);
return $result;
}

$this->updateCacheMetrics($group, ‘miss’);
return false;
}

public function set($key, $data, $group = ‘default’, $expiration = null) {
$cache_key = $this->generateCacheKey($key, $group);
$expiration = $expiration ?: ($this->cache_groups[$group] ?? 300);

$success = false;

// Set in Redis
if (isset($this->cache_backends[‘redis’])) {
$success = $this->cachebackends[‘redis’]->setex($cachekey, $expiration, serialize($data));
}

// Set in Memcached
if (isset($this->cache_backends[‘memcached’])) {
$success = $success || $this->cachebackends[‘memcached’]->set($cachekey, $data, $expiration);
}

// Set in WordPress cache
$success = $success || wpcacheset($cache_key, $data, $group, $expiration);

if ($success) {
$this->updateCacheMetrics($group, ‘set’);
}

return $success;
}

public function delete($key, $group = ‘default’) {
$cache_key = $this->generateCacheKey($key, $group);

// Delete from all backends
$deleted = false;

if (isset($this->cache_backends[‘redis’])) {
$deleted = $this->cachebackends[‘redis’]->del($cachekey) || $deleted;
}

if (isset($this->cache_backends[‘memcached’])) {
$deleted = $this->cachebackends[‘memcached’]->delete($cachekey) || $deleted;
}

$deleted = wpcachedelete($cache_key, $group) || $deleted;

return $deleted;
}

public function invalidateGroup($group) {
// For Redis, we can use pattern deletion
if (isset($this->cache_backends[‘redis’])) {
$pattern = $this->generateCacheKey(‘*’, $group);
$keys = $this->cache_backends[‘redis’]->keys($pattern);
if (!empty($keys)) {
$this->cache_backends[‘redis’]->del($keys);
}
}

// For Memcached, we need to track keys or use a different approach
if (isset($this->cache_backends[‘memcached’])) {
// This is more complex – would need key tracking
$this->cache_backends[‘memcached’]->flush();
}

// WordPress cache group invalidation
wpcacheflush_group($group);
}

public function warmCache($group = null) {
$groupstowarm = $group ? [$group] : arraykeys($this->cachegroups);

foreach ($groupstowarm as $cache_group) {
$this->warmCacheGroup($cache_group);
}
}

private function warmCacheGroup($group) {
switch ($group) {
case ‘consent_data’:
$this->warmConsentDataCache();
break;
case ‘user_preferences’:
$this->warmUserPreferencesCache();
break;
case ‘reports’:
$this->warmReportsCache();
break;
}
}

private function warmConsentDataCache() {
global $wpdb;

// Preload frequently accessed consent data
$frequentconsents = $wpdb->getresults(“
SELECT userid, consentcategories, COUNT(*) as frequency
FROM wpslosconsent_log
WHERE consenttimestamp >= DATESUB(NOW(), INTERVAL 30 DAY)
GROUP BY userid, consentcategories
HAVING frequency > 5
ORDER BY frequency DESC
LIMIT 100
“);

foreach ($frequent_consents as $consent) {
$cachekey = “consent{$consent->user_id}”;
$this->set($cachekey, $consent, ‘consentdata’);
}
}

private function warmUserPreferencesCache() {
// Similar implementation for user preferences
}

private function warmReportsCache() {
// Pre-calculate and cache common reports
}

private function generateCacheKey($key, $group) {
return “slos:{$group}:{$key}”;
}

private function updateCacheMetrics($group, $action) {
$metricskey = “cachemetrics_{$group}”;
$metrics = wpcacheget($metricskey, ‘slosmetrics’) ?: [
‘hits’ => 0,
‘misses’ => 0,
‘sets’ => 0
];

$metrics[$action]++;
wpcacheset($metricskey, $metrics, ‘slosmetrics’, 3600);
}

public function getCacheMetrics($group = null) {
if ($group) {
$metrics = wpcacheget(“cachemetrics{$group}”, ‘slos_metrics’) ?: [‘hits’ => 0, ‘misses’ => 0, ‘sets’ => 0];
$total_requests = $metrics[‘hits’] + $metrics[‘misses’];
$hitratio = $totalrequests > 0 ? ($metrics[‘hits’] / $total_requests) * 100 : 0;

return array_merge($metrics, [
‘hitratio’ => round($hitratio, 2) . ‘%’,
‘totalrequests’ => $totalrequests
]);
}

// Return metrics for all groups
$all_metrics = [];
foreach (arraykeys($this->cachegroups) as $cache_group) {
$allmetrics[$cachegroup] = $this->getCacheMetrics($cache_group);
}

return $all_metrics;
}

public function optimizeCacheSettings() {
$metrics = $this->getCacheMetrics();

$recommendations = [];

foreach ($metrics as $group => $metric) {
if ($metric[‘hit_ratio’] < 70) { $recommendations[] = [ 'group' => $group,
‘issue’ => ‘lowhitratio’,
‘currentratio’ => $metric[‘hitratio’],
‘recommendation’ => ‘increasettlorpreloaddata’
];
}

if ($metric[‘misses’] > $metric[‘hits’] * 2) {
$recommendations[] = [
‘group’ => $group,
‘issue’ => ‘highmissrate’,
‘misstohit_ratio’ => $metric[‘misses’] / max($metric[‘hits’], 1),
‘recommendation’ => ‘reviewcachestrategy’
];
}
}

return $recommendations;
}
}
`

Step 3: Cache Invalidation Strategy

`php
// Intelligent cache invalidation
class CacheInvalidationManager {
private $invalidation_rules = [];
private $deferred_invalidations = [];

public function __construct() {
$this->setupInvalidationRules();
}

private function setupInvalidationRules() {
$this->invalidation_rules = [
‘consent_updated’ => [
‘invalidate’ => [‘consentdata’, ‘userpreferences’],
‘pattern’ => ‘consent{userid}’
],
‘userprofilechanged’ => [
‘invalidate’ => [‘user_preferences’],
‘pattern’ => ‘user{userid}’
],
‘settings_changed’ => [
‘invalidate’ => [‘static_content’],
‘pattern’ => ‘settings_*’
],
‘content_updated’ => [
‘invalidate’ => [‘reports’],
‘pattern’ => ‘report_*’
]
];
}

public function invalidateOnEvent($event, $params = []) {
if (!isset($this->invalidation_rules[$event])) {
return;
}

$rule = $this->invalidation_rules[$event];

// Immediate invalidation for critical updates
if ($this->isCriticalEvent($event)) {
$this->performInvalidation($rule, $params);
} else {
// Defer non-critical invalidations
$this->deferInvalidation($rule, $params);
}
}

private function isCriticalEvent($event) {
$criticalevents = [‘consentupdated’, ‘userprofilechanged’];
return inarray($event, $criticalevents);
}

private function performInvalidation($rule, $params) {
$cache_manager = new AdvancedCacheManager();

foreach ($rule[‘invalidate’] as $group) {
if (isset($rule[‘pattern’])) {
// Invalidate specific pattern
$pattern = $this->replacePatternPlaceholders($rule[‘pattern’], $params);
$this->invalidatePattern($group, $pattern);
} else {
// Invalidate entire group
$cache_manager->invalidateGroup($group);
}
}
}

private function deferInvalidation($rule, $params) {
$this->deferred_invalidations[] = [
‘rule’ => $rule,
‘params’ => $params,
‘timestamp’ => time()
];

// Schedule deferred invalidation
if (!wpnextscheduled(‘slosdeferredcache_invalidation’)) {
wpschedulesingleevent(time() + 300, ‘slosdeferredcacheinvalidation’);
}
}

public function processDeferredInvalidations() {
foreach ($this->deferred_invalidations as $key => $invalidation) {
// Only process if it’s been more than 5 minutes
if (time() – $invalidation[‘timestamp’] > 300) {
$this->performInvalidation($invalidation[‘rule’], $invalidation[‘params’]);
unset($this->deferred_invalidations[$key]);
}
}
}

private function replacePatternPlaceholders($pattern, $params) {
foreach ($params as $key => $value) {
$pattern = str_replace(“{{$key}}”, $value, $pattern);
}
return $pattern;
}

private function invalidatePattern($group, $pattern) {
$cache_manager = new AdvancedCacheManager();

// For Redis, we can use pattern-based invalidation
if (isset($cachemanager->cachebackends[‘redis’])) {
$redis = $cachemanager->cachebackends[‘redis’];
$keys = $redis->keys(“slos:{$group}:{$pattern}”);

if (!empty($keys)) {
$redis->del($keys);
}
} else {
// For other backends, we need to track keys or use group invalidation
$cache_manager->invalidateGroup($group);
}
}

public function predictiveInvalidation($datatype, $changetype, $params = []) {
// Predict what cache entries might be affected by a change
$predictions = $this->predictInvalidations($datatype, $changetype, $params);

foreach ($predictions as $prediction) {
$this->invalidateOnEvent($prediction[‘event’], $prediction[‘params’]);
}
}

private function predictInvalidations($datatype, $changetype, $params) {
$predictions = [];

switch ($data_type) {
case ‘consent’:
if ($change_type === ‘update’) {
$predictions[] = [
‘event’ => ‘consent_updated’,
‘params’ => [‘userid’ => $params[‘userid’]]
];
}
break;

case ‘user’:
if ($changetype === ‘profileupdate’) {
$predictions[] = [
‘event’ => ‘userprofilechanged’,
‘params’ => [‘userid’ => $params[‘userid’]]
];
}
break;

case ‘settings’:
$predictions[] = [
‘event’ => ‘settings_changed’,
‘params’ => []
];
break;
}

return $predictions;
}

public function batchInvalidate($invalidations) {
// Group invalidations to minimize cache operations
$grouped = [];

foreach ($invalidations as $invalidation) {
$key = $invalidation[‘group’] . ‘:’ . ($invalidation[‘pattern’] ?? ‘all’);
if (!isset($grouped[$key])) {
$grouped[$key] = [
‘group’ => $invalidation[‘group’],
‘pattern’ => $invalidation[‘pattern’] ?? null,
‘count’ => 0
];
}
$grouped[$key][‘count’]++;
}

$cache_manager = new AdvancedCacheManager();

foreach ($grouped as $groupkey => $groupdata) {
if ($group_data[‘count’] > 10) {
// If many keys in a group are being invalidated, invalidate the whole group
$cachemanager->invalidateGroup($groupdata[‘group’]);
} else {
// Otherwise, invalidate specific patterns
foreach ($invalidations as $invalidation) {
if ($invalidation[‘group’] === $group_data[‘group’]) {
if (isset($invalidation[‘pattern’])) {
$this->invalidatePattern($invalidation[‘group’], $invalidation[‘pattern’]);
}
}
}
}
}
}
}
`

Database Query Optimization

Step 1: Query Analysis and Optimization

`
SLOS → Advanced → Performance → Query Optimization
`

Query Optimization Analysis:
`json
{
“query_analysis”: {
“totalqueriesanalyzed”: 1250,
“optimization_opportunities”: 45,
“performanceimprovementpotential”: “35%”,
“query_patterns”: [
{
“pattern”: “consenthistorylookup”,
“frequency”: “high”,
“currentavgtime”: “450ms”,
“optimized_time”: “45ms”,
“improvement”: “90%”
},
{
“pattern”: “bulkconsentexport”,
“frequency”: “medium”,
“currentavgtime”: “8500ms”,
“optimized_time”: “1200ms”,
“improvement”: “86%”
},
{
“pattern”: “compliance_reporting”,
“frequency”: “low”,
“currentavgtime”: “2500ms”,
“optimized_time”: “800ms”,
“improvement”: “68%”
}
]
},
“index_recommendations”: [
{
“table”: “wpslosconsent_log”,
“recommendedindex”: “idxuserconsenttimestamp”,
“columns”: [“userid”, “consenttimestamp”],
“benefit”: “Improves user consent history queries by 80%”
},
{
“table”: “wpslosaudit_log”,
“recommendedindex”: “idxaction_timestamp”,
“columns”: [“action”, “created_at”],
“benefit”: “Speeds up audit log filtering by 65%”
}
]
}
`

Step 2: Advanced Query Optimization

`php
// Advanced query optimization engine
class QueryOptimizationEngine {
private $query_patterns = [];
private $optimization_rules = [];

public function __construct() {
$this->initializeQueryPatterns();
$this->initializeOptimizationRules();
}

private function initializeQueryPatterns() {
$this->query_patterns = [
‘consent_history’ => [
‘pattern’ => ‘/SELECT.FROM.wpslosconsentlog.WHERE.userid.ORDER BY.consent_timestamp/i’,
‘optimization’ => ‘useindexedlookup’
],
‘bulk_export’ => [
‘pattern’ => ‘/SELECT.FROM.wpslosconsentlog.WHERE.consenttimestamp.*BETWEEN/i’,
‘optimization’ => ‘usepartitionedscan’
],
‘compliance_report’ => [
‘pattern’ => ‘/SELECT.COUNT.FROM.wpslosconsentlog.GROUP BY.*consentcategories/i’,
‘optimization’ => ‘useaggregatedcache’
],
‘user_search’ => [
‘pattern’ => ‘/SELECT.FROM.wpslosconsentlog.WHERE.ipaddress.*LIKE/i’,
‘optimization’ => ‘usegeospatialindex’
]
];
}

private function initializeOptimizationRules() {
$this->optimization_rules = [
‘useindexedlookup’ => [$this, ‘optimizeIndexedLookup’],
‘usepartitionedscan’ => [$this, ‘optimizePartitionedScan’],
‘useaggregatedcache’ => [$this, ‘optimizeAggregatedCache’],
‘usegeospatialindex’ => [$this, ‘optimizeGeospatialQuery’]
];
}

public function optimizeQuery($query, $params = []) {
$query_type = $this->identifyQueryType($query);

if ($querytype && isset($this->optimizationrules[$query_type])) {
return calluserfunc($this->optimizationrules[$querytype], $query, $params);
}

return $query; // Return original query if no optimization available
}

private function identifyQueryType($query) {
foreach ($this->querypatterns as $type => $patterninfo) {
if (pregmatch($patterninfo[‘pattern’], $query)) {
return $pattern_info[‘optimization’];
}
}

return null;
}

private function optimizeIndexedLookup($query, $params) {
// Ensure the query uses the most efficient index
$optimized_query = $query;

// Add FORCE INDEX hint if needed
if (strpos($query, ‘FORCE INDEX’) === false) {
$optimizedquery = pregreplace(
‘/FROM\s+wpslosconsent_log\s+/i’,
‘FROM wpslosconsentlog FORCE INDEX(idxuser_timestamp) ‘,
$query
);
}

// Add LIMIT if not present for user history queries
if (strpos($query, ‘LIMIT’) === false && strpos($query, ‘user_id’) !== false) {
$optimized_query .= ‘ LIMIT 50’;
}

return $optimized_query;
}

private function optimizePartitionedScan($query, $params) {
// For date-range queries, ensure partition pruning
$optimized_query = $query;

// Add partition hint for date ranges
if (pregmatch(‘/consenttimestamp\s+BETWEEN\s+\'”\'”]\s+AND\s+[\'”[\'”]/i’, $query, $matches)) {
$start_date = $matches[1];
$end_date = $matches[2];

// Calculate which partitions to scan
$partitions = $this->calculatePartitionsForRange($startdate, $enddate);

if (!empty($partitions)) {
$partition_list = implode(‘, ‘, $partitions);
$optimizedquery = pregreplace(
‘/FROM\s+wpslosconsent_log\s+/i’,
“FROM wpslosconsentlog PARTITION ({$partitionlist}) “,
$query
);
}
}

return $optimized_query;
}

private function optimizeAggregatedCache($query, $params) {
// For aggregation queries, check if we have cached results
$cachekey = ‘agg‘ . md5($query . serialize($params));
$cache_manager = new AdvancedCacheManager();

$cachedresult = $cachemanager->get($cache_key, ‘reports’);
if ($cached_result !== false) {
// Return a query that will use cached data instead
return “SELECT ” . jsonencode($cachedresult) . ” as cached_result”;
}

// Cache the result after execution
addaction(‘queryresultcached’, function($result) use ($cachekey) {
$cache_manager = new AdvancedCacheManager();
$cachemanager->set($cachekey, $result, ‘reports’, 1800); // 30 minutes
});

return $query;
}

private function optimizeGeospatialQuery($query, $params) {
// For IP-based queries, optimize with geospatial indexing
$optimized_query = $query;

// Convert IP addresses to numeric for faster comparison
if (pregmatch(‘/ipaddress\s=\s\'”[\'”]/i’, $query, $matches)) {
$ip = $matches[1];
$ip_numeric = ip2long($ip);

$optimizedquery = strreplace(
“ip_address = ‘{$ip}'”,
“ipaddressnumeric = {$ip_numeric}”,
$query
);
}

return $optimized_query;
}

private function calculatePartitionsForRange($startdate, $enddate) {
$partitions = [];
$startyear = date(‘Y’, strtotime($startdate));
$endyear = date(‘Y’, strtotime($enddate));

for ($year = $startyear; $year <= $endyear; $year++) {
$partitions[] = “p{$year}”;
}

return $partitions;
}

public function analyzeQueryPerformance($query, $executiontime, $resultcount) {
$analysis = [
‘query_type’ => $this->identifyQueryType($query),
‘executiontime’ => $executiontime,
‘resultcount’ => $resultcount,
‘efficiencyscore’ => $this->calculateEfficiencyScore($executiontime, $result_count),
‘recommendations’ => []
];

// Analyze execution time
if ($execution_time > 1000) { // Over 1 second
$analysis[‘recommendations’][] = ‘Consider adding database indexes’;
}

if ($execution_time > 5000) { // Over 5 seconds
$analysis[‘recommendations’][] = ‘Consider query optimization or caching’;
}

// Analyze result efficiency
if ($resultcount > 1000 && $executiontime > 100) {
$analysis[‘recommendations’][] = ‘Consider pagination for large result sets’;
}

// Store analysis for future optimization
$this->storeQueryAnalysis($analysis);

return $analysis;
}

private function calculateEfficiencyScore($executiontime, $resultcount) {
// Simple efficiency scoring algorithm
$base_score = 100;

// Penalize slow queries
if ($execution_time > 100) {
$basescore -= min(50, $executiontime / 20);
}

// Penalize queries returning too many results
if ($result_count > 100) {
$basescore -= min(30, $resultcount / 100);
}

return max(0, $base_score);
}

private function storeQueryAnalysis($analysis) {
global $wpdb;

$wpdb->insert(‘wpslosquery_analysis’, [
‘querytype’ => $analysis[‘querytype’],
‘executiontime’ => $analysis[‘executiontime’],
‘resultcount’ => $analysis[‘resultcount’],
‘efficiencyscore’ => $analysis[‘efficiencyscore’],
‘recommendations’ => json_encode($analysis[‘recommendations’]),
‘analyzedat’ => currenttime(‘mysql’)
]);
}

public function getOptimizationRecommendations() {
global $wpdb;

$recommendations = $wpdb->get_results(“
SELECT
query_type,
AVG(executiontime) as avgtime,
AVG(efficiencyscore) as avgscore,
COUNT(*) as occurrence_count,
GROUPCONCAT(DISTINCT recommendations) as allrecommendations
FROM wpslosquery_analysis
WHERE analyzedat >= DATESUB(NOW(), INTERVAL 7 DAY)
GROUP BY query_type
HAVING avg_score < 70 ORDER BY avg_time DESC ");return $recommendations; } } `

Resource Scaling and Load Balancing

Step 1: Auto-Scaling Configuration

`
SLOS → Advanced → Performance → Auto-Scaling
`

Auto-Scaling Configuration:
`json
{
“scaling_triggers”: [
{
“metric”: “cpu_usage”,
“threshold”: 70,
“scale_direction”: “up”,
“cooldown_period”: 300
},
{
“metric”: “memory_usage”,
“threshold”: 80,
“scale_direction”: “up”,
“cooldown_period”: 300
},
{
“metric”: “response_time”,
“threshold”: 2000,
“scale_direction”: “up”,
“cooldown_period”: 600
},
{
“metric”: “active_connections”,
“threshold”: 1000,
“scale_direction”: “up”,
“cooldown_period”: 300
}
],
“scaling_limits”: {
“min_instances”: 2,
“max_instances”: 10,
“scaleupincrement”: 1,
“scaledownincrement”: 1
},
“resource_allocation”: {
“web_servers”: “auto”,
“database_servers”: “auto”,
“cache_servers”: “auto”,
“load_balancers”: “auto”
}
}
`

Step 2: Load Balancing Strategy

`php
// Advanced load balancing for SLOS
class LoadBalancingManager {
private $backend_servers = [];
private $load_distribution = [];
private $health_checks = [];

public function __construct() {
$this->initializeBackendServers();
$this->setupHealthChecks();
}

private function initializeBackendServers() {
// Define backend servers with capabilities
$this->backend_servers = [
‘web1’ => [
‘host’ => ‘web1.example.com’,
‘weight’ => 100,
‘capabilities’ => [‘consentapi’, ‘admindashboard’, ‘reporting’],
‘status’ => ‘healthy’
],
‘web2’ => [
‘host’ => ‘web2.example.com’,
‘weight’ => 100,
‘capabilities’ => [‘consentapi’, ‘admindashboard’],
‘status’ => ‘healthy’
],
‘web3’ => [
‘host’ => ‘web3.example.com’,
‘weight’ => 50,
‘capabilities’ => [‘consent_api’],
‘status’ => ‘healthy’
]
];
}

private function setupHealthChecks() {
// Schedule health checks
if (!wpnextscheduled(‘sloshealthcheck’)) {
wpscheduleevent(time(), ’60’, ‘sloshealthcheck’);
}
}

public function performHealthChecks() {
foreach ($this->backendservers as $serverid => &$server) {
$health = $this->checkServerHealth($server[‘host’]);

$server[‘status’] = $health[‘status’];
$server[‘responsetime’] = $health[‘responsetime’];
$server[‘last_check’] = time();

// Adjust weight based on health
if ($health[‘status’] === ‘unhealthy’) {
$server[‘weight’] = 0;
} elseif ($health[‘response_time’] > 1000) {
$server[‘weight’] = max(10, $server[‘weight’] – 20);
}
}
}

private function checkServerHealth($host) {
$start_time = microtime(true);

// Perform multiple health checks
$checks = [
‘http_response’ => $this->checkHttpResponse($host),
‘database_connectivity’ => $this->checkDatabaseConnectivity($host),
‘cache_availability’ => $this->checkCacheAvailability($host),
‘load_average’ => $this->checkLoadAverage($host)
];

$responsetime = (microtime(true) – $starttime) * 1000;

$healthychecks = arrayfilter($checks, function($check) {
return $check === true;
});

$status = count($healthy_checks) >= 3 ? ‘healthy’ : ‘unhealthy’;

return [
‘status’ => $status,
‘responsetime’ => $responsetime,
‘checks’ => $checks
];
}

private function checkHttpResponse($host) {
$url = “http://{$host}/wp-json/slos/v1/health”;
$response = wpremoteget($url, [‘timeout’ => 5]);

return !iswperror($response) && wpremoteretrieveresponsecode($response) === 200;
}

private function checkDatabaseConnectivity($host) {
// This would require server-specific implementation
// For now, return true as placeholder
return true;
}

private function checkCacheAvailability($host) {
// Check if Redis/Memcached is available
return true;
}

private function checkLoadAverage($host) {
// Check server load average
return true;
}

public function routeRequest($request_type, $params = []) {
$availableservers = $this->getAvailableServers($requesttype);

if (empty($available_servers)) {
throw new Exception(‘No available servers for request type: ‘ . $request_type);
}

$selectedserver = $this->selectServer($availableservers, $params);

return $this->proxyRequest($selectedserver, $requesttype, $params);
}

private function getAvailableServers($request_type) {
return arrayfilter($this->backendservers, function($server) use ($request_type) {
return $server[‘status’] === ‘healthy’ &&
inarray($requesttype, $server[‘capabilities’]) &&
$server[‘weight’] > 0;
});
}

private function selectServer($available_servers, $params) {
// Weighted random selection with load balancing
$totalweight = arraysum(arraycolumn($availableservers, ‘weight’));

if ($total_weight === 0) {
return arraykeyfirst($available_servers);
}

$random = mtrand(1, $totalweight);

foreach ($availableservers as $serverid => $server) {
$random -= $server[‘weight’];
if ($random <= 0) { return $server_id; } }return arraykeyfirst($available_servers);
}

private function proxyRequest($serverid, $requesttype, $params) {
$server = $this->backendservers[$serverid];

// Record load distribution
if (!isset($this->loaddistribution[$serverid])) {
$this->loaddistribution[$serverid] = 0;
}
$this->loaddistribution[$serverid]++;

// In a real implementation, this would proxy the request to the selected server
// For now, we’ll simulate the response
return [
‘server’ => $server_id,
‘response’ => ‘Request routed successfully’,
‘processingtime’ => mtrand(100, 500)
];
}

public function getLoadDistribution() {
$totalrequests = arraysum($this->load_distribution);

$distribution = [];
foreach ($this->loaddistribution as $serverid => $requests) {
$distribution[$server_id] = [
‘requests’ => $requests,
‘percentage’ => $totalrequests > 0 ? ($requests / $totalrequests) * 100 : 0,
‘weight’ => $this->backendservers[$serverid][‘weight’]
];
}

return $distribution;
}

public function optimizeLoadDistribution() {
$distribution = $this->getLoadDistribution();

foreach ($distribution as $server_id => $stats) {
$server = &$this->backendservers[$serverid];

// Adjust weights based on load distribution
if ($stats[‘percentage’] > 40) {
// Server is overloaded, reduce weight
$server[‘weight’] = max(10, $server[‘weight’] – 10);
} elseif ($stats[‘percentage’] < 20) { // Server is underutilized, increase weight $server['weight'] = min(200, $server['weight'] + 10); } } }public function failoverHandling($failed_server) { // Mark server as unhealthy if (isset($this->backendservers[$failedserver])) {
$this->backendservers[$failedserver][‘status’] = ‘unhealthy’;
$this->backendservers[$failedserver][‘weight’] = 0;
}

// Redistribute load to remaining servers
$healthyservers = arrayfilter($this->backend_servers, function($server) {
return $server[‘status’] === ‘healthy’;
});

if (!empty($healthy_servers)) {
$additionalweight = 50 / count($healthyservers);

foreach ($healthyservers as $serverid => &$server) {
$server[‘weight’] += $additional_weight;
}
}

// Log failover event
$this->logFailoverEvent($failed_server);
}

private function logFailoverEvent($failed_server) {
global $wpdb;

$wpdb->insert(‘wpslosfailover_events’, [
‘failedserver’ => $failedserver,
‘failovertime’ => currenttime(‘mysql’),
‘activeservers’ => jsonencode(arraykeys(arrayfilter($this->backend_servers, function($s) {
return $s[‘status’] === ‘healthy’;
}))),
‘loaddistribution’ => jsonencode($this->getLoadDistribution())
]);
}
}
`

Support Resources

Documentation

1. Performance Monitoring Guide
2. Caching Best Practices
3. Load Testing Procedures

Help


4. Performance optimization specialists
5. Database tuning experts
6. Load balancing consultants
7. Infrastructure scaling advisors