After working at NASA, Cisco, and multiple Silicon Valley data centers, product manager and engineer Srini Sekaran saw a discussion come up time and time again — the high energy bills that these converged data centers produced.
“Everyone wants to store more and more data. As machine learning, which is basically reliant on extracting data and patterns from data, becomes more popular, everyone is going to store more and more data,” says Sekaran. “As we penetrate more into our internet and computing and energy usage, energy usage is going to skyrocket for the next five, 10 years.”
“Every company is essentially a data company now — from pest companies to public schools.”
Sekaran left Silicon Valley for Atlanta to join Georgia Tech’s Create-X student incubator and pursue a Master’s in Computer Science. He recently launched his energy analytics startup, Gavano.
“Gavano is at the middle of two very important industries — cloud computing and energy efficiency as it relates to cloud computing,” says Sekaran.
Gavano’s platform uses VMWare, machine learning and other virtualization hypervisors (the software/firmware layer that runs virtual machines in the data center) to gather 40+ metrics from the converged data center related to energy efficiency, carbon emissions and financial metrics.
Those metrics include total facility energy, inefficient devices, power demand, and data about cost trends and maintenance time.
The customer then receives a report on how to reduce operating expenses, power usage, greenhouse gas and carbon emissions, and improve overall efficiency from a management perspective. Alerts can be put in place when specific thresholds are passed, and clients can get predictions about their future usage.
Sekaran explains that established analytics solutions cater to traditional infrastructure, as opposed to Gavano’s focus on hyper-converged infrastructure. Existing tools can also take time to set up on-site. Not Gavano. “Within 30 seconds, a company can remotely plug in the URL of their center and Gavano is able to retrieve data from that.”
In terms of security, the power analytics startup offers two options. Customers that only need standard encryption can choose the SaaS model. For bigger enterprises like the federal government or NASA, where security is the number-one concern, they have the option to run the software within their data center itself, keeping it isolated internally.
Currently, the startup is in private beta with a few pilots in place. Sekaran is looking to raise a seed round to hire more engineers and scale the product further to accommodate more enterprise and federal customers.
“Right now we’ve only scratched the surface in terms of our online footprint collectively as society. As the world relies more on data centers and servers, we need more energy efficiency tools and services,” says Sekaran.
