LogDNA Announces Series D To Expand Observability Data
SAN FRANCISCO--(BUSINESS WIRE)--LogDNA, the leading observability data platform, today announced that cybersecurity investment and advisory firm NightDragon will lead a Series D funding round of $50 million with participation from existing investors Emergence and Initialized Capital. Today’s milestone accelerates LogDNA’s vision of enabling enterprises to maximize the value of observability data in motion.
The investment comes amidst substantial company growth. In November, LogDNA made Deloitte’s 2021 Technology Fast 500™, which highlighted the company’s 1293% revenue growth from 2017 to 2020. The company has more than tripled its team over the past few years and it continues to expand its customer base, which includes global technology brands like Lifesize and Reltio, as well as major platforms and service providers such as IBM Cloud and Armor.
With LogDNA’s cloud-first platform, some of the world’s largest companies are able to manage and take concrete action on observability data in real time and at hyperscale. The need for this type of solution is at an all-time high, and the LogDNA team sees a huge market opportunity to build on the platform’s existing capabilities. The investment will enable the company to deliver a more robust observability data pipeline solution that will empower builders — the application developers, the site reliability engineers, the platform engineers, and the teams that make sure that what’s being built is secure — to harness the full power of machine data within their workflows.
NightDragon co-founder and managing director, Dave DeWalt, who serves as vice chair for LogDNA’s Board of Directors, said he sees this as an opportunity to rethink the paradigm around data, especially for use cases like cybersecurity.
“Organizations need a comprehensive platform that ingests and normalizes massive amounts of data in the cloud and at hyperscale. With this type of platform, stakeholders from the developer to the C-Suite are empowered to make smarter, more cost-effective decisions and reduce the mean time to detection and remediation for cyberattacks,” said Dave DeWalt, Founder and Managing Director, NightDragon. “LogDNA has the right team and technology to address this challenge head on. NightDragon is proud to partner with them to accelerate their vision and help enterprises everywhere realize the true potential of data across their organizations.”
The Observability Data Opportunity
The prevailing approach in the observability market today is to manage the massive amount of data through a ‘single pane of glass’. While seemingly practical, it becomes a choke point, making data-intensive innovation and operations slower, more complicated, and prone to errors and heightened risk. They struggle to control costs and enable a wide array of people who need access to their observability data.
“Now that open systems, cloud-native architectures and interconnected applications and data are commonplace, a single pane of glass is far too limiting. It’s time to shift the focus to the people who use the data,” said Tucker Callaway, CEO, LogDNA. “The data consumer must be able to capture the real-time value of data in motion, not just data at rest in storage. They must be able to ingest and process data to a central point — the pipeline — and then route it to the tools where people are actually working, rather than forcing them to break their workflow to use a different tool. This is the problem that LogDNA aims to solve.”
The investment allows LogDNA to accelerate time to market for a new observability data pipeline solution, which will enable enterprises to ingest all of their data to a single platform, normalize it, and seamlessly route it to the appropriate teams, so they can take meaningful action quickly. The solution will be generally available in 2022. LogDNA will also continue rapidly expanding its team to support its growth and innovation, and it plans to expand its strategic partnerships to support more cloud and services providers, platforms, and technical integrations.