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Cribl, a data observability platform used by businesses such as Accenture, Domino’s and 7-Eleven, has raised $150 million in a series D round of funding.
The raise comes as remote work has become a semi-permanent way-of-life for millions of employees around the globe, and this “decentralized” workforce makes it more complex for companies to manage IT systems and data distributed across multiple locations.
“Enterprises have no streamlined way to make use of all that data, and are getting crushed by the cost of trying to,” Cribl cofounder and CEO Clint Sharp told VentureBeat.
Throw into the mix the myriad digital transformation efforts that companies are adopting, and a growing need to engage with customers through a software-powered interface, and it’s clear that companies will have to find ways to ensure minimal friction and maximum uptime.
“Today, nearly every business is a ‘software business’ — whether you’re a bank or a retailer, software applications are now a primary way businesses interact with their customers, and if businesses don’t provide a great experience on those apps, their customers are going to go elsewhere,” Sharp said.
But where, exactly, does Cribl come into all of this? Well, Cribl occupies a space known as “observability,” which is concerned with giving companies visibility into their systems, including details of specific customer interactions such as when they opened an app, what menu options they selected, and whether they encountered any errors in the process. It’s all about gleaning real-time insights into the internal state of an application by monitoring a vast array of telemetry data.
Founded out of San Francisco in 2017, Cribl has hitherto offered four core products, including AppScope; Cribl.Cloud; Cribble Edge; and the star of the show Cribl Stream, touted as an “observability pipeline” for transporting observability data between any source and destination.
The broader observability sphere includes big-name incumbents such as Splunk, Snowflake, and Elastic. But rather than compete directly with these platforms, it actually integrates with them, allowing businesses to get their logs, metrics, and traces to and from any source. According to Sharp, the most direct competitors are open-source “build-your-own” solutions such as Kafka or FluentD, while its core USP is a “vendor-agnostic” approach that helps companies move all their machine data.
“A common pain point we hear from our IT and security customers is that they’re using many tools across their functions, with data passing to and from all of them — but there’s no central point of control,” Sharp explained. “This creates more complexity and huge cost inefficiencies. Cribl’s suite of products are open and interoperable by design, meaning they can connect the disparate parts of the data ecosystem, and give customers choice and control over all the event data that flows through their corporate IT systems.”
From today, Cribl has thrown a fifth product into the mix with the announcement of Cribl Search, which enables companies to conduct “search-in-place” queries where the data is created, rather than having to ingest and centralize it all first. This has important ramifications for real-time data access, particularly for security teams that might want to “eliminate blind spots” using instant telemetry data.
This also follows a growing trend in the data infrastructure space, which has seen companies steadily embrace decentralized over centralized data platforms. However, the more disparate systems a company has in its stack, the harder it is to derive insights from the data they generate.
In terms of how a company might use Cribl search, well, the use-cases are endless. A company with thousands of Kubernetes instances powering numerous types of applications can generate multiple terabytes of telemetry data each day — the time it takes to transport all that information into a centralized repository for deeper analysis and troubleshooting can be the difference between winning and losing customers. Cribl Search takes all this spadework to the source of the data, allowing users to search against data stored in the likes of Splunk, Elasticsearch, or OpenSearch. On top of that, it also allows users to search through data as it flows through Cribl Stream, or even when that data is stored “at rest” in what Cribl refers to as an “observability lake,” which is basically a data lake for log data.
“Traditionally, if an application were to start performing poorly or encounter errors, the only way to debug that application is to forward the information and store it centrally,” Sharp said. “This creates unnecessary complexity and slows down the process of remediating the performance issue. With Cribl Search, you can troubleshoot directly on the edge, without having to move data first.”
Prior to now, Cribl had raised $252 million, and with a fresh $150 million in the bank, the company is well-financed to build out Cribl Search and ready it for public launch — the product is being made available today in private beta as part of an early-access program.
A source closed to the deal confirmed to VentureBeat that Cribl’s latest series D investment now values the company at a hefty $2.5 billion — a sharp hike on the $1 billion valuation it reported at its $200 million series C round less than a year ago.
Cribl’s series D round was led by Tiger Global Management, with participation from Sequoia, Greylock, Redpoint Ventures, IVP, and CRV.
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