PagerDuty Enters Unicorn Territory With $90 Million Funding Round

PagerDuty, a startup that's built an extensive suite of intelligent IT operations management solutions for enterprises reliant on maintaining uptime of their services, said Thursday it had secured $90 million in funding, putting it in the exclusive unicorn club.

New investors T. Rowe Price and Wellington Management led PagerDuty's D round, which brought total funding to more than $173 million and a valuation of $1.3 billion. Existing investors also joined the round.

That investment will go to accelerating efforts to scale sales globally, including through systems integrators and resellers that joined a formal channel program the company launched in April, Jonathan Rende, PagerDuty's senior vice president of product, told CRN.

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The $90 million will also ensure the company has the independence to "double down on opportunities" it sees in the market, both by organically developing new products and through acquisitions, Rende said.

The San Francisco-based company's Software-as-a-Service offering monitors the performance of complex IT systems by ingesting data from third-party monitoring, ticketing, service desk and security platforms. It then uses artificial intelligence to orchestrate fast and efficient responses to any issues that could result in downtime.

PagerDuty has built integrations with more than 300 applications and platforms, including Slack, AppDynamics, New Relic, Amazon CloudWatch, Zendesk and ServiceNow.

The PagerDuty Digital Operations Management platform ingests both machine data and human data from those products, then automates the response process to "surgically seek out all the individuals with the right information and engage them directly," Rende told CRN.

"We allow and enable all the teams that support those businesses in IT and development to make the best use of their time," he said.

PagerDuty has more than 10,000 customers, including name-brands like Netflix, GE, IBM, PayPal and Spotify. Those technology heavyweights, with business models dependent on maintaining service 24/7, rely on its tools to rapidly alert the right people when incidents arise and to orchestrate mitigation actions across their organizations.

The machine-learning engine learns from reactions and responses to previous issues, Rende said.

"We're using AI to make sure the same mistake isn't made twice."

That's especially useful to large organizations that want to ensure continuity in how they fix problems as team members change.

"In the heat of battle, when seconds matter, this is how we fixed things before. Our learning system provides information to help in that real-time battle," Rende said.

Any glitch resulting in downtime and poor performance doesn’t just rapidly lose revenue for those customers, he said, but also deteriorates their brand equity.

Outside its San Francisco headquarters, the company has a large presence in Toronto, and recently opened offices in the U.K. and Australia.