The revolt against SQL continues at a steady but considerably slower pace. Bespoke database software seems to crop up daily in the name of performance or functionality. This talk will examine the ever growing field of monitoring systems and their respective databases, and look in depth as to how Postgres can be used in a number of these places. Systems of this nature are typically tasked with collecting and storing metrics from your infrastructure, drawing pretty graphs, and nagging you when things break.
Forms of data stored by these systems are nothing to be afraid of - they often include: - Time series metrics - the history of a measurement over time, e.g. temperatures - Logs - unstructured text emitted by applications, operating systems and hardware - Events - schema-less but well structured notifications
An assertion of this talk is that for a majority of use cases, Postgres is more than capable of storing all of this data. We will attempt to replace numerous well known pieces of software with just one Postgres database. Of course we are told to use the right tool for the job, but having to learn and operate a single tool is a huge operational advantage.
We’ll get quite technical in this talk, take a look the data models and access patterns required, and how this can be fitted into the general purpose environment of Postgres. Additionally, it is always constructive to look at what can be problematic, and not just focus on the positives, and why many turn to other bespoke solutions.