It’s easy to see the value of sensor data that enables acting in time. Just picture driving as the scene of a massive traffic accident unfolds and ambulances race to the rescue…what a difference a few seconds can make. What if past traffic patterns could help city operators predict and manage traffic flow at critical times?

As the world is now forced into remote working due to COVID-19, I believe it’s important to make some things explicit that have been implicit for many a remote worker over the past few years with the rise of Slack in the distributed office. These tips are designed to be simple and actionable, with the goal of improving your remote working experience.

So you’re using InfluxDB and Telegraf. Perhaps you’re writing over a million metrics points per second. Perhaps you’ve used Flux to do some data exploration. However, you now find yourself in a little bit of a pickle. You need to process and analyze this large amount of data, and you’d prefer to do that work in your favorite language with your go-to libraries.

At InfluxData, we love the community! Our amazing open source members are an integral part of InfluxData and have been since its founding. They’ve helped us build amazing products for time series data. This is a quick update to give you some insight into how we track metrics about our community and ensure we are building products and features that our users want to see.