Edge Delta, a Seattle-based startup that is building a modern distributed surveillance stack that competes directly with industry heavyweights like Splunk, New Relic and Datadog, today announced it has raised a round of series funding. A $ 15 million led by Menlo Ventures and Tim Tully, the former CTO of Splunk. Previous investors MaC Venture Capital and Amity Ventures also participated in this funding round, bringing the company’s total funding to $ 18 million to date.
“Our thesis is that there is no way for businesses today to continue to analyze all of their data in real time,” said Edge Delta co-founder and CEO Ozan Unlu, who works in the field of observability for about 15 years already (including at Microsoft and Sumo Logic). “The way it was traditionally done with these primitive, centralized models – there’s just too much data. It used to work 10 years ago, but gigabytes turned into terabytes and now terabytes turn into petabytes. This whole model is falling apart.
He recognizes that traditional big data warehousing works well enough for business intelligence and analytics use cases. But it’s not in real time, and it also involves moving a lot of data from where it’s generated to a centralized warehouse. Edge Delta’s promise is that it can deliver all the capabilities of this centralized model by allowing businesses to start analyzing their logs, metrics, traces, and other telemetry right at the source. This, in turn, also allows them to have visibility into all the data that is generated there, instead of most current systems, which only provide an overview of a small portion of that information.
While competing services tend to have agents running on a customer’s machine, but usually just compressing the data, encrypting it and then sending it to its final destination, the Edge Delta agent begins to analyze data directly at the local level. With this, if you want, for example, to graph the error rates of your Kubernetes cluster, you won’t have to collect all that data and send it to your data warehouse where it needs to be indexed before it can be. analyzed and graphically.
With Edge Delta, you can instead have each node draw its own graphic, which Edge Delta can then combine later. Thanks to this, according to Edge Delta, its agent is able to offer significant performance advantages, often of several orders of magnitude. It also allows businesses to run their machine learning models at the edge.
“What I saw before I left Splunk was that people were sort of selective about where to locate workloads for a variety of reasons, including cost control,” said Tim Tully of Menlo. Ventures, who joined the company just a few months ago. . “So this idea that you can move some of the compute to the edge and reduce latency and do machine learning at the edge in a distributed fashion was incredibly fascinating to me. “
Edge Delta is able to offer a significantly cheaper service, in large part because it doesn’t need to run a lot of calculations and manage huge pools of storage on its own, as much of it is. managed at the periphery. And while customers obviously still incur overhead to provide this computing power, it’s still significantly less than what they would pay for a comparable service. The company says it typically sees about a 90% improvement in total cost of ownership over traditional centralized services.
Edge Delta bills by volume and it doesn’t hesitate to compare its prices with those of Splunk and does so directly on its price calculator. Indeed, speaking to Tully and Unlu, Splunk was clearly on everyone’s mind.
“There’s kind of a concept of unbundling Splunk,” Unlu said. “You have Snowflake and the data warehouse solutions coming in on one side, and they say, ‘hey, if you don’t care about real time, use us. And then we’re the other half of the equation, which is: in fact there are a lot of real-time operational use cases and this model is actually better for those massive flow processing datasets. that you need to analyze in real time.
But despite this competition, Edge Delta can still integrate with Splunk and similar services. Users can still take their data, ingest it through Edge Delta, and then push it to solutions like Sumo Logic, Splunk, AWS S3, and others.
“If you follow Splunk’s trajectory, we had this whole idea of building this business around IoT and Splunk at the Edge – and we never really got there,” Tully said. “I think what we end up seeing collectively is that the advantage actually means something a little different. […] Advances in distributed computing and the sophistication of edge hardware make it possible to solve these types of problems at lower cost and with lower latency.
The Edge Delta team plans to use the new funding to expand their team and support any new customers who have expressed interest in the product. To do this, it is strengthening its sales and marketing teams, as well as its customer success and support teams.