When most people think of job scheduling, they think of all different sorts of things. Container orchestration, serverless allocation, batch job running… all of these things qualify. In highly concurrent systems, it is important that you can schedule work to be done and be able to collect those results upon completion. In the world of high-performance, low-latency systems software, those jobs take on a whole different flavor.

Whether or not you’re familiar with time-series data, it has a significant impact on your life – and your business. If you aren’t using it, you’re missing out. If you are using it, you may not be getting the most out of it. First things first, let’s define time-series data. Simply stated, it’s any series of data points recorded with accompanying time stamps, usually as a sequence recorded at equally spaced intervals.

What happens when cloud-based application infrastructure slows down? Twelve years ago, I attended a meetup at the San Francisco Perl Mongers group where an engineer from Amazon introduced the Elastic Compute Cloud service (EC2). At the time, anyone involved with computing infrastructure either racked their own servers or used managed hosting where someone else took care of the pipes, power, and ping.