New Relic delivers next-gen AIOps

Engineers can now automatically detect changes instantly, cut alert noise, and see probable root cause across any data source with New Relic’s observability platform–without guesswork, lengthy setup, or a credit card.

  • 3 years ago Posted in

New Relic has launched new capabilities in New Relic Applied Intelligence to help engineers detect, understand, and resolve incidents faster than ever. This latest update to New Relic One allows engineers to uncover anomalies automatically, now enabled by default and available for free to all users. Engineers can now also see the probable root cause of every incident from any data source automatically, with guidance on suggested responders on their team who may be best equipped to revolve each issue. Also available in public beta today, engineers can quickly spot patterns and outliers in all of their log data using machine learning (ML) to dramatically reduce troubleshooting time. 

 

“AIOps has promised engineers the ability to harness AI and machine learning to predict possible issues, determine root causes, and intelligently drive automation to resolve them,” said Bill Staples, president & chief product officer at New Relic. “Despite the hype, many DevOps and SRE teams have struggled to achieve the value of AIOps, as steep learning curves, long implementation and training times, prohibitive pricing, and lack of confidence in AI and machine learning have stood in the way. With our next-gen AIOps capabilities launched today, New Relic is solving these challenges, putting the power of observability in the hands of every engineer to finally deliver the promised value of AIOps to everyone.”



“As a tech-forward eCommerce company with a mission to help drivers get back on the road, delivering a fast, easy-to-use experience for our customers is a top priority. Critical to this is our ability to proactively detect and resolve any incidents before they impact our platform,” said Eugene Kovshilovsky, SVP of software engineering at CarParts.com, Inc., (NASDAQ: PRTS). “New Relic Applied Intelligence was fast and easy to implement, enabling us to quickly bubble up issues from across the stack to allow us to take a targeted approach to determine what needs to be optimized or fixed, and how many human hours will be required. We look forward to New Relic's next-gen AIOps continuing to unleash the power of our data by automatically filtering out alert noise, detecting patterns and outliers, and identifying probable root cause faster. This will help us continue to deliver a smooth, hassle-free customer journey for our fellow drivers."



The modern capabilities now available in New Relic Applied Intelligence are designed to deliver on the promise of AIOps with speed of deployment, out of the box integrations, ease of use, and simplicity to help engineers quickly and easily:



·  Detect unusual changes instantly: Automatically spot anomalies based on golden signals like throughput, errors, and latency across all applications, services, and log data—at no additional cost, with zero configuration needed, and now available to all users including those signed up for New Relic’s free tier. Engineers get notified in Slack and other collaboration tools, and can troubleshoot faster with in-depth anomaly analytics to detect potential problems early, before they impact customers.

·  Cut down alert noise from any source: Instead of alert storms across multiple tools, events are auto-correlated based on time, context from alert messages, and now relationship data across systems so engineers see one issue with all the data needed to take action. Pre-trained ML models accelerate speed to value by eliminating steep and costly learning curves.

·  Get to root cause faster: Eliminate guesswork and solve problems faster with automatic insights into the probable root cause for incidents. Engineers can quickly see why each open issue occured, which services and systems are impacted, and what action is needed for resolution. They get ML-based guidance on suggested responders on their team who may be best equipped to revolve each issue.

·  Detect patterns and outliers in log data: Launching in public beta today, machine learning detects patterns and outliers in log data to reduce troubleshooting time. Engineers can explore millions of log messages with a single click and reduce manual querying by automatically clustering their log data to quickly find anomalous patterns and problematic needles in the haystack. Because New Relic uniquely enables teams to instrument all telemetry data from any source in one place, log patterns are stored in New Relic's Telemetry Data Platform as events. This enables engineers to easily create dashboards, alerts, and queries based on log patterns for faster rollup analysis and troubleshooting of trends in their log data.

·  Integrate seamlessly with PagerDuty and other popular incident management tools: Eliminate the toil of managing incidents across tools via a new integration that synchronizes the state of correlated issues in New Relic bi-directionally with PagerDuty and other popular incident management tools. As the state of correlated issues changes in New Relic and these platforms, they are all now automatically updated to help on-call engineers manage and resolve incidents more efficiently and effectively.

 

“Great customer experiences are the cornerstone of financial services and our business. Critical to our digital transformation journey to the cloud is our effort to standardize on the New Relic One platform to embrace full-stack observability across development, engineering, and operations,” said Stephen Rylander, SVP and global head of engineering at Donnelley Financial Solutions. “Leaning on New Relic AIOps will go hand-in-hand with this full-stack visibility so that my engineering and SRE teams are empowered to catch any problems before they impact our SaaS platform and, in turn, our customers.”  

 

Beacon, NY, Dec 20, 2024– DocuWare unveils its AI-powered Intelligent Document Processing...
85% of IT decision makers surveyed reported progress in their companies’ 2024 AI strategy, with...
Lopitaux joins as global companies embrace GenAI solutions at scale and look to build their own...
Predictive maintenance and forecasting for security and failures will be a growing area for MSPs...
NVIDIA continues to dominate the AI hardware market: powering over 2x the enterprise AI deployments...
Hitachi Vantara survey finds data demands to triple by 2026, highlighting critical role of data...
81% of enterprises plan to increase investments in AI-powered IT operations to accelerate...
Hitachi Vantara survey finds data demands to triple by 2026, highlighting critical role of data...