When the stakes are high, every decision is only as good as the information behind it. With the right information, enterprises and vital sectors can confidently make informed decisions. Data becomes a foundation for action — and a source of differentiation. But how do you store the relentless influx of data — especially since data storage costs, amplified by the risk of data loss, are among the top hurdles facing organizations today?

Recently InfluxAce Jorge de la Cruz presented on “Modern vSphere Monitoring and Dashboards Using InfluxDB, Telegraf and Grafana”. Jorge is a Systems Engineer at Veeam Software and has been using InfluxDB for years. In case you missed attending the live session, we have shared the recording and the slides for everyone to review and watch at your leisure.

As InfluxDB continues to grow and improve, more and more developers are using it as the platform of choice for their own solutions. Most of these solutions range from filling niche internal needs to solving common problems faced by entire industries, but some of them are extraordinary for their impact, innovation, or how much they push the boundaries of what is possible with the technology. In order to recognize those, we are launching the InfluxDB Inventors program.

Are you currently using Flux with InfluxDB? Have you written a great Flux function that would be useful to the community? If the answers to these questions are “Yes!”, then I encourage you to contribute your awesome work to Flux, so that others can appreciate you and your work. Today, we’re sharing how you can contribute a custom Flux function in a Third Party Flux Package.

Energy storage and sustainability are big issues in Hawaii, where oil tankers are shipped in everyday, just to keep the lights on. Resiliency in the energy grid, due to threat of natural disaster, is critical. Energy storage is needed to manage how much solar energy is coming into the market or into the grid. Properly managing the power entering the grid is vital for grid stability since Hawaii has intermittent energy that floods the grid.

Data ingestion and data analysis are the yin and yang of a time series platform. There are many resources to help you ingest data. Typical ingestions are agent-based, imports via CSVs, using client libraries, or via third-party technologies. Once your time series data arrives, analysis completes the circle and often leads to additional data collection, and so on and so forth.

InfluxDB Cloud is now beta on Microsoft Azure and we’d like you to try it out so we can work to make sure it’s ready for general availability (GA). If you’re already familiar with InfluxDB, head over to cloud2.influxdata.com to sign up for your free account. And if you’re not, read on for how to get started.

​Have you seen this when using the Flux code editor? Pretty neat to be able to get that much help from an editor while writing code. ​Have you ever wondered how that worked? Today, I’ll take us on a bit of a deep dive on the behind-the-scenes that enable these autocompletion features in the editor.

I wanted to better understand how COVID-19 has been developing in South America. As I’ve recently started playing with InfluxDB, the open source time series database, I created a dashboard of cases and deaths using InfluxData’s platform. I usually use InfluxDB, Chronograf, Grafana, Zabbix and other similar solutions to monitor services and systems. However, until this point, I hadn’t used them to process and visualize other kinds of data.

Giraffe is the open source React-based visualization library that’s used to implement InfluxDB’s v2 UI. It employs clever algorithms to handle the challenge of visualizing the incredibly high volume of data that InfluxDB can ingest and query. We’ve just published documentation describing how developers can take advantage of this library and I’ve tried to create a companion tutorial to further illustrate the power of this library.