Edge Delta, which analyzes data using distributed stream processing and federated machine learning, announced a $15-million Series A round led by Menlo Ventures and Tim Tully, the former CTO of Splunk. Previous investors, MaC Venture Capital and Amity Ventures, are participating as well.

Tasked with the health of mission critical systems, DevOps, Security and SRE teams rely on the ability to analyze data quickly and efficiently. With data expanding exponentially, corporations face increasingly significant challenges to keep up with the volume of data analysis — resulting costs have become exorbitant, and bottlenecks frequent. The traditional, centralized cloud model can no longer be relied upon due to inherent technical and financial limitations.

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Edge Delta is changing the way that data is analyzed. Rather than pushing everything to the cloud and then beginning to analyze data, Edge Delta starts the analysis where it’s created — ie, K8s containers, AWS EC2, Azure Functions, physical machines, and network devices.

This “on-the-edge” stream processing allows corporations to analyze machine data output such as logs, metrics, events, traces, telemetry at the source, resulting in a more sophisticated and deeper real-time analysis. Edge Delta typically results in an almost 90-percent improvement in TCO compared to traditional centralized monitoring solutions.

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“Five years ago, data volumes were smaller, and it was no problem to simply forward all observability data to the cloud, index it, and then analyze it,” said Ozan Unlu, founder and CEO of Edge Delta. “But in that short time, gigabytes have turned into terabytes, and terabytes are turning into petabytes. The centralized cloud model can’t handle it in real time without massive trade offs, the traditional system is archaic.”

“Edge Delta allows enterprises to analyze all of their data without worrying about overages or crushing costs,” said Fatih Yildiz, co-founder and CTO. “Suddenly, teams get complete visibility of all of their data. It is transformative.”