Advanced Computing in the Age of AI|Thursday, July 9, 2020
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Cloud Analytics Startup Raises $52M 

via Shutterstock

As more companies are moving applications and other workloads to the cloud, the market for cloud-based data analytics appears to be gaining momentum as cloud infrastructure vendors invest in application monitoring services.

Among the emerging cloud monitoring services attracting investors is Wavefront, an analytics tool vendor that helps software-as-a-service vendors boost their DevOps functions. The three-year-old startup said Tuesday (Oct. 25) it has raised $52 million in an oversubscribed funding round led by new investor Tenaya Capital. The venture fund has previously backed Hadoop specialist Hortonworks and Palo Alto Networks.

A pair unidentified cloud infrastructure vendors also participated in the Series B funding round. The company's customers include file-sharing specialist Box (NYSE: BOX), Intuit (NASDAQ: INTU) and Microsoft (NASDAQ: MSFT). Existing investors include Sequoia Capital and Sutter Hill Ventures.

Wavefront, Palo Alto, Calif., raised $11.5 million earlier this year. The startup said it would use the latest funding to extend its hosted platform for ingesting, storing and visualizing time series data. The platform is based on a stream processing approach invented at Google (NASDAQ: GOOGL).

In between funding rounds, the company introduced "operational data science" tools designed to help enterprises keep pace with operational complexity, including intelligent alerting and expanded query functions. The goal is fewer cloud outages, noted CEO Pete Cittadini, the former CEO of analytics and reporting software company Actuate who was hired in April.

The startup attributes its early success to surpassing traditional cloud monitoring by crunching time series data in real time. Along with detecting and preventing cloud outages, the service also is touted as helping cloud operators improve capacity planning and resource allocation.

"By streaming metrics from every corner of the cloud instead, and correlating for connections, a DevOps team can investigate issues in real time without filtering their data or taking on unnecessary latency in their time-to-recovery," Wavefront CTO and co-founder Dev Nag wrote earlier this year on sister web site Datanami.

Wavefront also promotes its cloud-monitoring platform as allowing users to visualize and query performance metrics ranging from cloud computing load to application and business performance data. It is betting that the accelerating stream of performance data from servers, cloud infrastructure and applications are overwhelming developers.

As DevOps teams incorporate the operational data science model, they face a series of key challenges, Dev Nag argued. Those include scaling data collection and analytics tools, improving statistical methods and "condensing" multiple metrics into operational details, the former Google software engineer stressed.

Along with reducing application downtime, the startup also is pitching its analytics tools as a complement to current business intelligence tools as big data and cloud computing continue to merge.

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

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