LogDNA raises $50M to convey ‘full energy’ of observability knowledge to safety

LogDNA raises $50M to bring 'full power' of observability data to security

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Observability knowledge software program developer LogDNA, which at present introduced a $50 million sequence D funding spherical, mentioned it’s creating a brand new platform that may allow a extra data-driven method in key enterprise areas similar to safety administration. The corporate plans to debut the brand new platform within the second quarter of 2022, and the launch will characterize a serious growth of the seller’s efforts in cybersecurity — past its roots in aiding developer use of log knowledge, CEO Tucker Callaway informed VentureBeat.

Observability knowledge contains telemetry from programs — logs, metrics, and traces — and can be utilized to find out whether or not a system is wholesome or not. If the system is having issues, observability knowledge may also help to pinpoint an answer. The idea of observability has emerged in recent times as a extra superior successor to monitoring, with capabilities to reply completely different questions slightly than the identical questions frequently.

Arming builders

Based in 2016, LogDNA has tackled the observability knowledge alternative on behalf of builders, after discovering that builders had been sometimes spending half of their time digging by means of purposes to get essential log data, Callaway mentioned. The San Jose, California-based firm created a instrument to streamline developer workflows, focusing solely on that one use of observability knowledge, he mentioned.

Now, after rising to three,000 clients and seeing its answer used through main companions similar to IBM Cloud, LogDNA has noticed what it sees as its subsequent large alternative: creating a brand new observability knowledge platform that would open up further enterprise use circumstances, similar to safety administration.

The corporate describes the forthcoming product as an observability knowledge “pipeline” as a result of it would route ingested and processed knowledge from a central level out to no matter instrument a consumer is working with. The last word promise of the platform is to allow builders and engineers, together with safety engineers, “to harness the total energy of machine knowledge inside their workflows,” LogDNA mentioned in a information launch.

Alert overload

The chance to maneuver into cybersecurity comes as enterprises wrestle to make sense of the massive quantity of knowledge, and numerous alerts, generated by their rising cadre of safety instruments.

A latest survey from cyber vendor Pattern Micro discovered that enterprises sometimes have a mean of 29 completely different safety instruments, whereas the biggest organizations have a mean of 46. This has led to an lack of ability to successfully prioritize safety alerts, with many instruments going unused or underused, in response to the survey.

“Enterprises have dozens of safety instruments, however few selections in tips on how to leverage observability knowledge throughout them, whatever the instruments they’ve chosen,” Callaway mentioned in an e-mail to VentureBeat.

“In the meantime, safety professionals are drowning in alerts and crimson lights, and need to sift by means of knowledge to do every little thing from stopping threats to fixing poor configurations,” he mentioned. “There’s a want to get forward of safety points by shifting left with DevSecOps, to create sound safety practices proactively in enterprise and know-how operations, versus continually chasing dangerous safety postures.”

LogDNA’s forthcoming observability knowledge pipeline will enable enterprise groups to ingest all of their knowledge to a single platform, normalize it, after which route it to the suitable instruments — enabling them to take “significant motion” on their observability knowledge in actual time, Callaway mentioned.

Enhancing managed safety

The know-how can provide a bonus for safety administration because of the want to wish for simplifying knowledge assortment, processing, and routing in that house, he mentioned. “Safety is a primary instance the place we’re replicating what we’ve carried out for builders for safety engineers who want entry to the best knowledge, in the best instrument, in actual time,” Callaway mentioned.

As an illustration, LogDNA at the moment processes greater than 4 petabytes of log knowledge per thirty days for IBM Cloud throughout a dozen world datacenters, in response to Callaway. That’s now enabling IBM Cloud to stream knowledge to providers similar to IBM QRadar and Splunk for “sooner safety administration,” Callaway mentioned.

LogDNA sees managed safety service suppliers (MSSPs) and managed detection and response (MDR) suppliers as a primary wave of customers for the corporate’s observability pipeline, “with the intention to differentiate their safety capabilities to enterprises,” he mentioned. The corporate has begun bringing on MSSP design companions.

ML capabilities

The observability pipeline additionally has the potential to allow enhanced use of machine studying (ML) with safety, Callaway mentioned. Firms that condense giant quantities of knowledge for ML “have solely taken step one,” he mentioned.

“Totally different ML duties require completely different varieties of knowledge, and corporations have to form, kind, trim, redact, and course of the info for each ML mannequin with the intention to yield the very best outcomes,” Callaway mentioned. “For instance, coaching a mannequin centered on safety errors requires knowledge centered on safety errors, not every bit of knowledge the corporate has ever generated.”

Consequently, LogDNA is wanting into routing to ML applied sciences for extremely efficient studying throughout particular person fashions, he mentioned. Notably, the info pipeline method additionally differs from the “single pane of glass” method taken by different gamers within the observability knowledge house, Callaway mentioned.

“Now that open programs, cloud-native architectures, and interconnected purposes and knowledge are commonplace, a single pane of glass is much too limiting,” he mentioned. “It’s time to shift the main focus to the individuals who use the info.”

The info shopper should be capable of seize the real-time worth of knowledge that’s in movement, not simply knowledge at relaxation in storage, Callaway mentioned. And “they have to be capable of ingest and course of knowledge to a central level — the pipeline — after which route it to the instruments the place persons are really working, slightly than pressure them to interrupt their workflow to make use of a special instrument. That is the issue that LogDNA goals to unravel,” he mentioned.

Safety VC curiosity

One other indicator of LogDNA’s transfer into safety — and the potential relevance of its answer for the safety market — is that the brand new spherical of funding was led by security-focused enterprise agency NightDragon. The agency’s cofounder and managing director is Dave DeWalt, previously the CEO of distinguished cybersecurity distributors FireEye and McAfee.

DeWalt had joined the board at LogDNA in April, the place he serves as vice chair, although this spherical represents the primary funding by NightDragon into the corporate. In a weblog put up in April, DeWalt referred to as LogDNA “one of many main corporations fixing the DevSecOps problem for builders and software safety groups at present.”

Within the information launch asserting the funding at present, DeWalt mentioned that LogDNA’s know-how permits clients to make “smarter, less expensive selections” — and in the end “cut back the imply time to detection and remediation for cyberattacks.”

Two current traders, Initialized Capital and Emergence, took half within the sequence D funding spherical. LogDNA didn’t disclose any valuation particulars related to the spherical. The corporate has now raised a complete of $110 million in funding.

Fast development

LogDNA didn’t disclose income particulars for 2021, however had beforehand reported income development of 155% in 2020. The corporate was additionally lately ranked No. 112 on Deloitte’s 2021 Expertise Quick 500 of the fastest-growing private and non-private tech companies. The rating acknowledged the corporate for producing income development of 1,293% between 2017 and 2020.

On the partnership facet, the IBM Log Evaluation and IBM Cloud Exercise Tracker providers are pushed by LogDNA know-how.

Along with serving as a accomplice, IBM Cloud can be a LogDNA buyer. LogDNA’s know-how supplies centralized logging for your entire IBM Cloud system, in addition to for particular person groups similar to IBM Watson and The Climate Firm. Different LogDNA clients embrace Asics, Lime, Higher.com, and Sysdig.

The corporate employs 124. It was based by Chris Nguyen, who served as CEO from 2016 to 2020, and chief know-how officer Lee Liu. The founders had beforehand based two corporations collectively, JobLoft (acquired by OnTargetjobs) and TeamSave.

The thought for the corporate got here whereas Nguyen and Liu had been participating in Y Combinator’s winter 2015 cohort, engaged on an ecommerce advertising platform. “We constructed a strong logging system a lot of our pals wished” and “determined to pivot,” Liu wrote on Hacker Information in 2016.

Callaway, who beforehand held government roles together with at Chef and Sauce Labs, took the helm as CEO of LogDNA in mid-2020, after a stint serving as president of the corporate.

Key differentiators

Rivals embrace publicly held corporations Datadog and Sumo Logic — in addition to venture-backed corporations similar to Cribl, which raised a $200 million sequence C spherical in August, and Coralogix, which raised a $55 million sequence C in July.

In keeping with Callaway, main differentiators embrace that LogDNA is “constructed for builders” similar to software builders, website reliability engineers, and platform engineers. Wanting forward, including the observability knowledge pipeline to the corporate’s portfolio will provide additional differentiation, he informed VentureBeat.

“Most of our opponents both present a single pane of glass answer or an information pipeline,” Callaway mentioned. “In contrast to them, LogDNA brings collectively best-in-class log evaluation and an observability knowledge pipeline — in order that enterprises can get machine knowledge from any supply, at any scale, to any vacation spot, for any use case.”

This in the end empowers “any knowledge shopper” inside a company, he mentioned.

All in all, “there may be clear enterprise-driven demand to make observability knowledge work higher for all knowledge customers,” Callaway mentioned. “This funding permits us to speed up bringing our full answer to market.”


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