Scalability

CS75 Lecture 9: Scalability

Vertical Scaling

Get more RAM, processors, disks for one machine, but you will exhaust the financial resources/state.

Horizontal Scaling

Plural number of machines, use multiple servers to build the topology.

Cache

.html

Requires a lot of work when want to update/redesign the page.

MySQL Query Cache

query_cache_type = 1

Memcached

Store whatever you want in RAM.
Garbage Collection: expire objects based on when they are put in.

Load Balancing

Implementation

Dedicated servers for images, videos… for different host HTTP header.
Round Robin. The load balancer can be a DNS setup which returns the IP address of server 1 when the first time someone asks for a URL, then return the IP address of server 2 when the second time someone asks for the same url, then server 3, server 4… eventually wrapping up.
- Downside: one server may get a really computational heavy user.
Based on the load on a server.
Have a server specifically for storing sessions. But what if that machine breaks down. Lacks redundancy, can add RAID (Redundant Array of Independent Disks).

Load Balancers

Replication

Master-Slave

Master: the main database that you write/read data to/from.
Slave: anytime a query is executed on the master that same query is copied down to one or more slaves and they do the exact same thing.

Advantage

If the master is down, promote one of the slaves and do some configuration. (redundancy)
If there are a lot queries, you could just load balance across database servers.
For read heavy websites, any select can go to all four databases, while any insert/update/delete has to go to server master.

Master-Master

You could write to either server one or two and if you happen to write to server 1 that query gets replicated on server 2 and vice versa, so now you could keep it simple.