YotaScale Gets Another Round of Funding

YotaScale announced another round of funding in September 2016, worth $2.4 million from Engineering Capital, Pelion Ventures, and angel investors such as Jocelyn Goldfein, Timothy Chou and Robert Dykes. This is the second round of funding for Yotascale. In January 2016, it got a funding of $1.2 million from Engineering Capital. In all, the company has raised a total funding of $3.6 million.

YotaScale – Company Profile

YotaScale is an infrastructure performance management platform for cloud computing. Founded in 2015, this company is headquartered in Menlo Park in California. It was founded by Asim Razzaq, a  former Senior Engineering Director at eBay and PayPal. During his stint at eBay, Razzaq realized that there was no dedicated service for monitoring the performance of cloud infrastructure, so he set out to fill this gap with his own company. Abbas Yousafzai is the current CTO, and Razzaq is the CEO of this company.

YotaScale collects and analyzes data collected from billions of data points on a platform. It uses machine learning algorithms to monitor factors such as load balance, performance, cost and availability of any platform. The aim of this system is to ensure that a company’s infrastructure is optimized to meet the changing business priorities of its clients. In fact, using such performance-based information, enterprises can customize platforms to align with their own priorities, so they can make the most of the underlying hardware and software of any cloud platform. In addition, it gives them unique insights about the platform, using which they can create new products and applications, and at the same time, reduce their operating costs.

Performance management for cloud computing is a hot and growing space, and there is much competition in this niche.  However, Razzaq is confident that his product will bring in more investors as the company expands.

That said, YotaScale, or for that matter, other companies in this space too, face many hurdles. Different types of cloud infrastructure data are generated at different times because not all hardware or software components run at the same time. Some information is generated hourly, while others daily, and so on. With such disparate data, it becomes difficult to combine them together to get the picture of the platform’s performance at any given time.

For example, let’s say three components run and based on it, the performance is optimal at 1:00 AM, but when data about a hardware component arrives in at 5:00 AM, it changes to sub-optimal. This way, it’s hard to know if the performance was optimal at all at 1:00 AM because the data that is needed to get a complete picture hasn’t come in until 5:00 AM.

Another problem is to define what is normal because it is highly contextual. So, what is normal for one situation may not be normal for another one.

Addressing these hurdles will be a crucial aspect for YotaScale in the near future.

About The Author
Lavanya Rathnam is a professional writer of tech and financial blogs. Creative thinker, out of the boxer, content builder and tenacious researcher who specializes in explaining complex ideas to different audiences.
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