Load Balancing | Load Balancer | Consistent hashing


The concept of taking N servers to handle requests and trying to balance evenly in all of them is called Load Balancing.

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Video Take away: * Load balancing distributes requests across servers.
* You can use `hash(r_id) % n_servers` to get the server index for a request `r_id`. -> Drawback: if you add an extra server `n_servers` changes and `r_id` will end up on a different server. This is bad because often we want to map requests with the same ids consistently to the same servers (there could e.g. be cached data there that we want to reuse). * "Consistent hashing" hashes with a constant denominator `M`, e.g. `hash(r_id) % M`, and then maps the resulting integer onto a server index. Each server has a range of integers that map to their index.



Load Balancing is a key concept to system design. One of the popular ways to balance load in a system is to use the concept of consistent hashing. Consistent Hashing allows requests to be mapped into hash buckets while allowing the system to add and remove nodes flexibly so as to maintain a good load factor on each machine. The standard way to hash objects is to map them to a search space, and then transfer the load to the mapped computer. A system using this policy is likely to suffer when new nodes are added or removed from it. Consistent Hashing maps servers to the key space and assigns requests(mapped to relevant buckets, called load) to the next clockwise server. Servers can then store relevant request data in them while allowing the system flexibility and scalability. Some terms you would here in system design interviews are Fault Tolerance, in which case a machine crashes. And Scalability, in which case machines need to be added to process more requests. These two principles are allowed by Consistent Hashing, and hence it is an important building block to a system design architect's toolbox. Another term used often is request allocation. This means assigning a request to a server. Consistent hashing assigns requests to the servers in a way that the load is balanced are remains close to equal.

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