Scaling Memcached horizontally involves adding more servers to your Memcached cluster, allowing the system to distribute the load across multiple machines. This increases cache space and distributes the processing load, improving the system's overall capacity and performance.
Here are the steps to do that:
If you're using the
python-memcached client, for instance, it would look something like this:
In this example,
192.168.1.3 are the IP addresses of your Memcached servers. Note that you need to replace them with the actual IP addresses of your machines.
Remember, horizontal scaling requires management of the server pool and proper distribution of cached objects. It's also important to note that Memcached does not sync data between different servers - if one server fails, the data contained within it will be lost until it's repopulated. Therefore, Memcached should only be used to cache data that can be regenerated or re-queried from a persistent storage layer.