Granulate, a startup developing a platform that optimizes computing infrastructure in real time, today announced that it raised $12 million, bringing its total raised to date to $15.6 million. The company’s products could reduce the time engineers spend fine-tuning the performance of enterprise systems, freeing them up to pursue more creative and impactful projects.
Granulate’s eponymous product comprises agents that can be installed on any Linux server in data centers or cloud environments, including virtual machines. These agents, which are underpinned by AI, adapt both to operating systems and kernels, prioritizing threads while taking into account each request’s processing stage and employing a network stack that enables high parallelism. Granulate analyzes memory usage patterns and sizes to optimize allocations and release of memory for each app, and it autonomously crafts congestion control prioritizations between connections, optimizing throughput for the current workload and network status.
“Most companies run at 35% IT infrastructure utilization or less due to strict quality of service and stability needs. Granulate solves the trade-off between quality of service and costs, providing customers improved results in both,” said Granulate cofounder and CEO Asaf Ezra, who previously did a stint at cyber research and security firm KayHut after serving four years in the Israeli Defense Forces.
Applying AI to data center operations isn’t a new idea — IDC predicts that 50% of IT assets in data centers will run autonomously using embedded AI functionality by 2022. To this end, Concertio, which recently raised $4.2 million, provides AI-powered system optimization tools for boosting hardware and software performance. Facebook has said that it employs AI internally to speed up searches for optimal server settings. And IBM offers a tool — Data Center Advisor with Watson — that calculates data center health scores and predicts potential issues or failures.
Above: Granulate’s analytics dashboard.
But according to Ezra, Granulate’s suite — which works with existing monitoring tools like Prometheus, AppDynamics, New Relic, Datadog, Dynatrace, and Elastic — is installed in dozens of production environments and tens of thousands of servers, and it’s more performant than most. It improves the throughput of machines by up to five times on average, the company claims, leading to up to a 60% compute cost savings and a 40% reduction in latency.
Startapp, a mobile data platform with over 1.5 billion monthly active users and 800,000 partner apps, reports that Granulate achieved a 30% reduction in average latency and a 25% processor utilization reduction, netting a 33% compute cost reduction. Another customer — Bigabid, an advertising technology company specializing in mobile user acquisition and re-engagement for gaming, dating, and productivity apps — says it managed to reduce compute costs by 60% within 15 minutes of deploying Granulate.
“Given the current economic slowdown, we are even more excited about helping businesses across the globe achieve dramatic cost reductions necessary to thrive amid changes in the global business environment,” Ezra added.
Granulate’s financing round (a series A) was led by Insight Partners, with participation from TLV Partners and Hetz Ventures. It brings the company’s total raised to $15.6 million shortly after its graduation from the 16-week Intel Ignite accelerator program. Ezra, who cofounded Granulate with Tal Saiag in 2018, says the capital will support the Tel Aviv-based company’s growth and expansion as it triples the size of its R&D, sales, and marketing departments. (Granulate has 14 employees, and it expects to triple its headcount to roughly 40 by 2021.)
Author: Kyle Wiggers.
Source: Venturebeat
