Community Highlight: How Supralog Built an Online Incremental Machine Learning Pipeline with InfluxDB OSS for Capacity Planning

This article was written by Gregory Scafarto, Data Scientist intern at Supralog, in collaboration with InfluxData’s DevRel Anais Dotis-Georgiou.

At InfluxData, we pride ourselves on our awesome InfluxDB Community. We’re grateful for all of your contributions and feedback. Whether it’s Telegraf plugins, community templates, awesome InfluxDB projects, or Third Party Flux Packages, your contributions continue to both impress and humble us. Today, let’s shine a spotlight on Gregory Scafarto from Supralog.

Gregory Scafarto built and maintains an online capacity planning pipeline with Kapacitor, Python, and InfluxDB. Gregory Scafarto is based in France and is finishing the last year of his Masters Degree in Computer Systems Networking and Telecommunication at ENSEIRB-MATMECA. He’s also working as a Data Scientist intern at Supralog on research for predictive maintenance and capacity planning solutions.

How Supralog uses Kapacitor for capacity planning

Capacity planning is one of the most important types of analysis in time series monitoring. Capacity planning tools help evaluate the production capacity required by an organization. Specifically in IT, capacity planning involves estimating the storage, business demand, and cost estimates to deliver the agreed service level targets.