New Relic Launches AI for DevOps (AIOps)
New Relic unveiled a new suite of artificial intelligence- and machine learning-based on-call DevOps capabilities Tuesday aimed at site reliability engineering (SRE) and network operations center (NOC) teams responsible for operating modern infrastructure.
New Relic AI combines "applied intelligence" and machine learning technologies to provide on-call teams with intelligence and automation that augments their existing incident management teams and workflows to get closer to root causes faster, the company said.
"One of the biggest challenges for on-call engineers is around finding signals in the flood of alerts that often create noise, as well as being able to prioritize and take action on the issues that matter most,", Michael Olson, New Relic's director of product marketing, told PureAI. "We believe that, as the complexity of software continues to grow, DevOps and SRE teams really need faster and easier ways to resolve incidents, and that's where AIOps technology can step in and help."
Gartner coined the term "AIOps" in 2016 to categorize a set of machine learning analytics technologies that enhance IT operations.
In a 2019 report ("Artificial Intelligence for IT Operations Delivers Improved Business Outcomes"), Gartner analyst Charley Rich wrote: "AIOps will detect patterns a human would be unlikely to uncover, including those that reveal cause and effect. From this determination of causality, models should be created that will help decide which IT metrics should be mapped to which business objective. Observe these over time to refine each model; ensure that it is up-to-date and that any assumptions it makes remain accurate. Through its usage of machine learning algorithms, AIOps specifically offers a mathematical way to find the hidden connections, causes and opportunities in the data that make this process possible."
The New Relic AI capabilities have been integrated with New Relic One, the company's application performance management (APM) platform (the company calls it an "observability platform"). They were designed to provide a "holistic" AIOps solution, explained Guy Fighel, general manager of applied intelligence and VP of product engineering at New Relic, to give on-call engineers a way to proactively detect anomalies before an issue hits production or impacts customer experience, to help teams prioritize their alerts and focus on issues that matter most, and to route and escalate incidents in a more intelligent way
"Our goal is to help reduce the toil and anxiety of running modern systems for engineering teams," Fighel said.
New Relic AI is provides access to the company's NRDB (the New Relic Database) a unified telemetry database, which fuels ML models and provides an intelligent, context-rich incident response workflow, drawing on key capabilities that include: proactive detection of anomalies; incident correlation; and integration with Slack, PagerDuty, ServiceNow, OpsGenie, VictorOps and other tools to fit within customers' existing incident management workflow.
"We're making it very fast and easy for customers to get value from day one," Olson said, "with really simplified configuration requirements and making it extremely easy for customers to connect those data sources with a few clicks via guided configuration UI."
John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He's been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he's written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS. He can be reached at email@example.com.