In a conversation with my sister last week, I was musing whether we would go back to shaking hands in the aftermath of the coronavirus and in general what the world was going to look like in the months and years ahead. She made an observation that I thought was spot on: “I don’t think we’re going back.” The world has fundamentally changed.

Percentiles are commonly used for measuring statistics, particularly when analyzing things like latency. Unfortunately, people frequently get tripped up when they want to take multiple percentiles and aggregate them. For example, let’s say we are monitoring a set of ten web servers and we want to collect latency statistics across all of them.

Today we want to talk about a welcome change to Circonus’ user interface: the addition of dark mode. Once found only in apps themselves, dark mode is now supported by all major operating systems, including MacOS, Windows 10, Android and iOS. And it’s also well-liked, with some tech sites finding that over 90% of their audience use dark mode some or all of the time.

At Circonus, we love demanding and challenging use cases. We love working with companies in industries where getting it right is mission critical. Where the ability to harness and analyze vast amounts of data in real-time is critical to success and where good enough just isn’t good enough. There is perhaps no better example than the oil and gas industry where the industrial era is entering the digital era unleashing both challenges and enormous opportunities.

Today we are excited to announce and share the significant momentum we’ve seen here at Circonus for the start of 2020, as more enterprises seek out machine data intelligence solutions that can underpin their digital transformation initiatives. At the end of 2019, we launched our machine data intelligence platform, which enables enterprises to collect, store, and analyze vast amounts of data from sensors, systems and connected devices to gain extraordinary business insight and intelligence.

We’re extremely pleased to announce today that Circonus has raised a $6.8 million Series A1 investment, which will help us continue advancing our machine data intelligence platform and accelerate our sales and marketing efforts. The round was led by Osage Venture Partners and included new investors Bull City Venture Partners and Ben Franklin Technology Partners. NewSpring, which led the Series A investment, also invested in the round.

As the number of things we want to monitor grows and sensors proliferate our world, enterprises have the opportunity to gather and analyze vast amounts of machine-generated data that provide extraordinary business insights. This is machine data intelligence. Today we released a visionary paper on machine data intelligence, the missing link to deriving business value in the current Internet of Everything economy.

Today, we’re proud to announce the launch and availability of our Circonus Platform, the first machine data intelligence platform built to provide enterprises with the ability to handle the rapidly increasing data volume and frequency seen in today’s global IT infrastructure and IoT deployments.

This post is Part 1 of a 2-part series about Monitoring Ephemeral Infrastructure. Part 2 will detail how Circonus uses these features to monitor our API services backed by ephemeral GCP infrastructure.

When most people think of job scheduling, they think of all different sorts of things. Container orchestration, serverless allocation, batch job running… all of these things qualify. In highly concurrent systems, it is important that you can schedule work to be done and be able to collect those results upon completion. In the world of high-performance, low-latency systems software, those jobs take on a whole different flavor.