When you configure multiple Memcached servers in your PHP application, the client library doesn't write to all servers simultaneously. Instead, it uses consistent hashing to determine which server should store each key-value pair. This is fundamentally different from replication.

// Example PHP configuration for multiple Memcached servers
$memcached = new Memcached();
$servers = [
    ['web1.example.com', 11211],
    ['web2.example.com', 11211],
    // ... up to web5
];
$memcached->addServers($servers);

The PHP client (using libmemcached) applies a hash function to each key to determine its target server. This creates a distributed hash table where:

• Keys are consistently mapped to the same server (unless server list changes)
• No data is duplicated across servers by default
• Each server stores a portion of the total cache

Tools like repcached solve a different problem - they provide redundancy by copying data between servers. This is useful when:

// Without replication, if a server goes down:
$memcached->get('user_123'); // Returns false if server is unavailable
// With replication, another server has the data

Your current setup with 5 load-balanced servers running Memcached is actually optimal for:

• Distributing memory usage across multiple machines
• Increasing total available cache size (aggregate of all servers)
• Maintaining performance during individual server failures

Here's how to verify which server stores your keys:

function getServerForKey($memcached, $key) {
    $servers = $memcached->getServerList();
    $serverIndex = $memcached->getServerByKey($key);
    return $servers[$serverIndex]['host'];
}

// Usage:
echo 'Key "session_123" is stored on: ' . getServerForKey($memcached, 'session_123');

You might consider localhost-only caching when:

• Each web server has enough RAM for its cache needs
• Network latency to other Memcached servers is high
• You want to minimize cross-server dependencies

When working with Memcache across multiple web servers, the distribution behavior is often misunderstood. The PHP client doesn't write to all servers in the pool - instead, it uses a consistent hashing algorithm to determine which server should store each key/value pair. Here's how it works:

// Example PHP memcache connection setup
$memcache = new Memcache;
$memcache->addServer('web1.example.com', 11211);
$memcache->addServer('web2.example.com', 11211);
// ... add all 5 servers

// The client automatically selects the server based on key hash
$memcache->set('user_12345', $userData); // Goes to exactly one server
$data = $memcache->get('user_12345');    // Retrieves from the same server

The PHP memcache client (both Memcache and Memcached extensions) uses the following logic:

• When you perform a set() operation, the client hashes the key
• This hash determines which server in your pool will store the data
• Subsequent get() operations will use the same hash to locate the server

Tools like repcached serve an important purpose despite this distribution mechanism:

1. High Availability: If a server fails, its data becomes inaccessible
2. Read Scaling: Multiple copies allow spreading read load
3. Data Locality: When servers are geographically distributed

In your load-balanced environment with 5 servers running memcached locally, consider these approaches:

// Option 1: Let the client distribute automatically (default)
$memcache = new Memcache;
foreach ($servers as $server) {
    $memcache->addServer($server, 11211);
}

// Option 2: Force localhost-only with fallback
$memcache = new Memcache;
$memcache->addServer('localhost', 11211, true); // 'true' makes it preferred
foreach ($other_servers as $server) {
    $memcache->addServer($server, 11211, false); // 'false' makes them fallbacks
}

Testing across different configurations reveals important patterns:

Based on production experience with similar setups:

• For most balanced workloads, use full distribution
• If network latency between servers is high, prefer local with fallback
• Monitor cache hit rates when changing configurations
• Consider sharding patterns for very large datasets