Operations | Monitoring | ITSM | DevOps | Cloud

Let's say you log into your amazon or eBay account and start searching for a gift clothing. First you would filter out gender-specific collections, then you might fix a particular color or even a set of colors of your choice, and following that, you can fix a price range. When you apply these filters one by one, you can see the aggregate products displayed each time varies (their total number changing according to the availability of aggregates). This is exactly what aggregations do.

Data is kind of like Newton’s first law of motion. Data is just that unless acted upon by something else. Time series data, therefore, is something you derive from data. We generally derive time series data to record historical observations about a physical or virtual system (for example, think of sensors and servers, respectively). However, not all time series data is the same. There are different use cases for time series data, and each has its own workload needs.