Machine learning (ML) has quickly become integral to many businesses. Its rapid adoption across almost every industry is because it is a force multiplier: new data can be learned from and understood as it arrives, while historical data can be revisited with new tools and practices.

Part 1 of the series of posts which talk about engineering design decisions to make high cardinality work in time-series databases.

We’ve all seen it: a company experiencing a major incident and going radio silent, leaving their customers to wonder “Are they doing something about this?!”. If you’ve ever been on the inside of something like this, you know the answer is most likely yes, there are people working hard to put out the fire as quickly as possible. But when it comes to incidents, perception is reality for customers.

What is Graphite? Simply put, Graphite is an open-source enterprise-ready time-series database. So what is a time-series database? Well, a time series is a series of data points indexed (or listed or graphed) in time order. Time Series databases have excellent benefits over traditional databases in terms of high performance, higher writes, improved scalability, better reliability, and many more.