Almost all new software businesses these days are helpers. They offer software to help you use other software or help you make other software. Compared to 20 years ago, it’s much harder to build something as fundamentally seismic to humanity as a Google or a Facebook. On the other hand, it’s much easier to make something that makes a selected group of people happy, thanks to open source culture. The wealth of resources and education available for free means that with a little talent, you can create little earthquakes at a very low cost. Software monitoring is one of these rivers in the ocean of software business.

Software monitoring to software is just like the dashboard to your car. Your car dashboard tells you if you have enough gas or if something is wrong with your engine. Software monitoring tools tell you if something is wrong with your software and the things you use to run it. Monitoring had existed since software existed, but offering a set of integrated tools as a comprehensive service is a relatively new practice. In the past, developers would often patch together several tools and keep them in-house. More recently, some companies have begun to offer a full suite of monitoring tools, integrating them with cloud computing services, and topping up the package with advanced features in analytics. They offer this as a subscription, removing the need to host and maintain locally, and they have managed to make it look sexy.

The main perk is efficiency: it frees up local resources to focus on gaining insights from data. Incorporating nifty visualizations and statistical techniques allows you to feel like you are doing a data scientist’s work rather than a system administrator’s. “Data scientist” is definitely sexier than “Sysadmin,” which is why companies market monitoring from a data science angle. What used to be a dreaded chore becomes appealing, and this is a side effect that is not to be overlooked. Having a reputation of installing ping pong tables in the office, making things fun is a staple allure of the software business.

The old model of monitoring is like having a horse carriage. You buy some horses (monitoring tools), a stable (servers) and a full staff to maintain the health of the horses. The new model is more like having a self-driving Iron Man suit with a supercharged assistant like Jarvis. He is more than a helper; he is a sentinel. He is an artificial intelligence that can auto-adjust your power mode according to flight conditions, verbally alert you to engine problems while cracking jokes, and make you green juice in the morning.

A fairly popular general model of software monitoring is Gartner’s Application Performance Management, which is an apt description, but I’ve already started yawning. Words, names, and imagery do matter, a lot (sometimes even, or especially, punctuation). Data scientists used to be called statisticians or analysts. When someone thought of calling the job a different name, granted that the field became associated with artificial intelligence, the same job evolved into the sexiest job of the century. There has to be a more imaginative name to software monitoring as data science is to statistics. Like Sentinel. Software Sentinel. Cloud Sentinel. Cloud Computing. Data Science. Cloud Sentinel. Got a nice ring to it, doesn’t it? A bit strange at first, but remember, cloud computing used to be a headscratcher not long ago, and now it’s become a beloved buzzword in Techspeak.