production grade logging

Logging to sockets is better than logging to files. It allows for more flexibility in terms of log rotation and data integrity. I started looking around for examples of this but everything these days when it comes to logging is built for the enterprise. The actual skeleton of what all those enterprise systems are doing is quite simple. In fact it is so simple that you can do it in less than 30 lines of code in most high level languages. Here’s the skeleton for a logging server in Ruby: Continue reading

simple in-memory store with consistent reads

Problem Statement

Suppose you want to write a simple in-memory JSON store with an equally simple socket based protocol. You want this in-memory store to support parallel and consistent reads. By “parallel reads” what I mean is if 10 clients request to read data from the store then no client should be blocking any other client. By “consistent reads” what I mean is when a client requests some data from the store there is absolutely no way that client gets half of the data before a write and half of it after a write and there is also some kind of ordering for reads and writes. In other words, if we have an array “[1,2,3,4]” that corresponds to the key “ints” in our JSON store then the following sequence of events is impossible: Continue reading