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The AIOps market has grown rapidly during the pandemic, particularly as the worker shortage in the IT industry worsens. Short for “AI in IT Operations,” AIOps refers to software that automates, correlates, and monitors the performance of events in IT systems across enterprise organizations. According to a 2019 AIOps Exchange survey, 45% of IT organizations now look to AIOps to analyze and determine the probable root cause of incidents and to predict future problems. It’s paying dividends for early adopters — PagerDuty estimates that companies that have adopted AIOps are saving as much as 30 minutes on average to resolve IT incidents.
ScienceLogic, Coiled, and OpsRamp are among the vendors providing AIOps solutions for large corporate clients. Another is BigPanda, a Mountain View, California-based startup developing AI to audit changes in IT environments, anticipate issues, and recommend how to fix them. BigPanda today announced that it raised $190 million at a $1.2 billion valuation post-money — the largest valuation in the AIOps segment to date. It’s both a vote of investor confidence and a sign of continued growth in the AIOps space, which is expected to be worth $10 billion by 2027.
Detecting issues autonomously
BigPanda was founded in 2012 by Assaf Resnick and Elik Eizenberg. Resnick was an analyst at Moody’s before becoming a principal at Sequoia Capital and member at Jibe Ventures. Eizenberg, formerly head of IT operations at IDF, worked on algorithms and software at stock-trading startup MarketWindows prior to joining BigPanda.
“Each day, [teams] face a tsunami of data associated with their digital services. In fact, most organizations have anywhere from 50 to 100 monitoring tools that spew out data about specific applications, systems, cloud, and on-premises infrastructure,” Resnick told VentureBeat via email. “None of these provide a complete picture and it is no longer possible for humans to filter through all of their data and piece together the story of an incident … Dozens of people who could be doing high value work are, instead, on multi-hour bridge calls, pointing fingers, and trying to avoid blame. For these reasons, most [executives] and their teams are evaluating and adopting AIOps.”
BigPanda works to prevent outages by combining data from observability, monitoring, change, and topology tools into actionable insights. The platform can automate manual aspects of incident response such as ticketing and notification and optionally connect to third-party runbook automation tools to run workflow automations.
BigPanda also provides analytics to track incident trends and metrics, enabling IT executives and managers to measure progress toward goals. As Resnick explains: “BigPanda’s [platform] provides … root cause analysis capabilities that explain their logic to the user in plain language. We also enrich every incident with business context — the last known outage, who owns the service, etc. — so that the right set of human beings can get involved and begin their incident response workflow. [And the] machine learning models regularly suggest new correlation logic as new infrastructure elements, apps, services and tools are added to environments and new data is ingested and correlated.”
Users can edit BigPanda’s machine learning-generated correlation patterns and then test the patterns against data collected in different windows of time. Once the platform suggests a pattern, admins can decide to activate it, reject it, or further customize it within a control panel using a pattern editor. Teams can tailor the correlation pattern definitions based on their environment to increase the effectiveness of the correlation. BigPanda additionally provides a pre-production tester so that teams can run the edited logic on live data without having to go into production.
BigPanda claims that one of its roughly 100 customers, video game studio Bungie, was able to eliminate its reliance on manual monitoring while reducing 3,000 alerts to 35 tickets. Another subscriber, Sony’s PlayStation Network, says that BigPanda helped its IT operations team transition to working from home while experiencing a surge of new business during the pandemic.
Challenges and opportunities
AIOps has great potential, but it’s far from a perfect science. While platforms like BigPanda excel at tasks like updating infrastructure configurations and firewall rules, they sometimes struggle to respond to more complex issues, like a cyberattack that leverages a variety of exploits.
There are institutional barriers to AIOps adoption, too, including poorly documented IT operations processes and low-quality data. Even the most powerful AIOps tools can be impaired if they don’t have enough data to process — and the data must be of high quality. Noisy data, inconsistent, or insufficient logs across apps can lead to AIOps systems that perform poorly.
On the other hand, if implemented thoughtfully, AIOps eliminates routine, low-skilled tasks — ideally freeing up IT staff to focus on higher-value activities. Other AIOps benefits include the ability to use data-driven insights, predictive analysis, and visualizations to make more informed IT operations decisions.
According to a 2021 Rackspace Technology survey, poor data quality was the main reason for failure in the AI systems that power AIOps platforms. And a majority of respondents in a 2021 Juniper report said their organizations were struggling with expanding their workforce to integrate with AI systems like AIOps systems.
The promise of AIOps is driving 59% of companies to explore the technology for use in their organization, according to a 2019 Loom Systems report. By 2023, 40% of companies will be using AIOps for app and infrastructure monitoring, Gartner predicts.
“Once acknowledged only when outages occurred, IT operations teams are now recognized for maintaining every organization’s mission-critical digital presence. This shift dramatically accelerated with the onset of the pandemic as digital services exploded overnight in terms of their scale and importance to consumers’ everyday lives,” Resnick said. ” In the race to improve online experiences, [executives] needed to quickly accelerate digital transformation initiatives. This put a spotlight on [teams] who are charged with maintaining the availability and performance of applications, systems, and networks that are the backbone of digital services.”
BigPanda says that new annual recurring revenue (ARR) in the first three quarters of 2021 grew by nearly 150% year-over-year. (Resnick says the company’s ARR is currently “under $100 million” with an 80% gross margin profile.) With the new funding — which was led by Insight Partners and Advent Partners, and which brings BigPanda’s total capital raised to $320 million — the 290-employee company plans to open a new office in London to support new and existing customers.
“We continue to invest in product differentiation, hiring R&D, and engineering expertise to expand our capabilities in AI-powered incident automation,” Resnick added. “In a few weeks, we will be announcing our expansion into Europe, the Middle East, and Africa as well as the formation of a dedicated go-to-market team focused on midsize enterprises. [Also,] as we grow our customer base, we are investing in enablement, services, partners and people to ensure customers experience value from BigPanda every day.”