Keeping watch over application performance, availability and security is a 24/7 job under the best of circumstances. Throw in the coronavirus lockdown and you have a potential nightmare if things start to go wrong.
The timing could not be better for new tools that can help application managers and site reliability engineers (SREs) do their jobs more efficiently. Enter New Relic, which this month announced the general availability of New Relic AI, a new suite of AI-based IT operations — AIOps — tools that enable applications teams to prioritize issues better and to proactively detect and resolve incidents faster.
New Relic AI Features
New Relic AI adds the ability to detect anomalies and to group and correlate incidents, events and alerts from multiple sources, explained Michael Olson, director of product marketing at New Relic.
The artificial intelligence consists of statistical models and built-in algorithms that can offer several out-of-the-box solutions, Olson said. But the key is the ability for customers to do their own tuning with their own operational data as time goes on. “The system gets smarter over time as it as it continues to study and learn from your day,” Olson said.
The product also includes new integrations with incident management systems from Slack, PagerDuty, ServiceNow and others that enable users to access correlated incident data that New Relic AI provides directly within the interfaces for those tools.
“We make it really easy for customers to be able to connect those tools as data sources, where we then ingest that data, normalize it and establish relationships across incidents and alerts and events,” Olson said. “And then we correlate those into one more actionable issue that our customers can take.”
New Relic AI is an add-on to New Relic One, which was released late last year. Customers can add the New Relic AIOps capabilities with a license option and pay on a per-event basis, Olson said. The basis for the new AI technology is from SignifAI, an events-intelligence vendor New Relic acquired a little more than a year ago.
Observability — of applications, servers, processes and events — has been a big story the past year as tools mature and the market starts to consolidate. Application performance management (APM) tools have enabled IT managers to keep up with the growth of SaaS and mobile apps for enterprise and consumer users and the demands for performance and reliability that come with that.
How Signify Health is Using New Relic AI
New Relic is a key part of the operations of Signify Health, a provider of home health risk assessments and continuity-of-care services based in Dallas. Jeffrey Hines is senior site reliability engineer in charge of a scheduling system for the company’s network of clinicians, doctors and nurses who visit homes. He said his company runs New Relic APM, Browser, Mobile Insight and Infrastructure products, and is trying out the new AI tools.
Amid the lockdown, Signify Health is in the process of migrating many applications to the Microsoft Azure cloud. "We’ve got some older applications that need to be rewritten so that they’re more compatible with the cloud," Hines said. "We’re moving everything up into Azure in Kubernetes Docker containers. … And, of course, that creates new challenges for me as a site reliability engineer: [needing] to monitor [on-premises], in the data center and in the cloud as well."
The company is running the new Proactive Detection feature of New Relic AI alongside existing alerts, he said, and evaluating the fidelity of those alerts and then correlating those with other system data. “We’re becoming more comfortable with it every day. It’s definitely a good thing in terms of telling us where to look first,” Hines said.
Signify is also trying out the integration with Slack and plans to integrate New Relic with its Atlassian Opsgenie incident response tool, Hines added.
Hines said his current work-from-home setup includes several monitors running New Relic dashboards. So far, things have worked out well. “It has been a challenge,” he said. “Anything that reduces the load on the teams and helps us find the answers easier definitely makes a difference. AIOps still has some ways to go before it’s where it needs to be, but I get a lot of noise, and I have to sort through the noise. The more that I can reduce that noise, the better.”
Scot Petersen is a technology analyst at Ziff Brothers Investments, a private investment firm. He has an extensive background in the technology field. Prior to joining Ziff Brothers, Scot was the editorial director, Business Applications & Architecture, at TechTarget. Before that, he was the director, Editorial Operations, at Ziff Davis Enterprise. While at Ziff Davis Media, he was a writer and editor at eWEEK. No investment advice is offered in his blog. All duties are disclaimed. Scot works for a private investment firm, which may at any time invest in companies whose products are discussed in this blog, and no disclosure of securities transactions will be made.
