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New Relic Adds AI Recommended Alerts

New Relic further enhanced its AIOps capabilities with recommended alerts. This provides the ability to quickly detect and easily resolve alert coverage gaps by using AI to identify anomalous behavior, determine areas of the technology stack that aren’t being monitored, and recommend new alerts to engineers.

An observability solution that reduces the need to manually build numerous alert conditions using AI makes it easier to understand which signals are most important or what thresholds indicate performance problems. Now, every engineer, regardless of their experience level, can eliminate alerting blindspots—empowering them to detect, resolve, and respond to issues faster.

“In an increasingly dynamic landscape, it’s easy for engineering teams to be overwhelmed by the need to configure alerts across different layers of the technology stack, especially since manually creating alert policies can be time- and resource-intensive. This can cause enormous gaps in the team’s alerting policies, leaving them blind and incapable of responding quickly and confidently when things break,” said New Relic Chief Product Officer Manav Khurana. “We designed New Relic recommended alerts to remove those barriers, so teams have the alerts they need to proactively monitor their stack, diagnose incidents and prioritize them for immediate action before it impacts their customers, business, and bottom line.”

Powered by AIOps, New Relic recommended alerts streamlines alerting with its alert coverage gaps feature, which continuously and automatically highlights areas in an organization’s technology stack that are missing alert coverage across application performance monitoring (APM), mobile and browser entities. Then, New Relic fills alerting gaps by recommending new alerts with pre-populated alert conditions, such as error percentage or response time. Using the recommendations as a starting point, engineers can also customize their alerts by implementing additional parameters to tailor the alert conditions and drive even better coverage for the team.

New Relic recommended alerts builds upon New Relic AI, a suite of AIOps capabilities that understands historical alerts and applies machine learning (ML) and AI to significantly reduce alert noise, enrich incidents with context, and provide intelligence and automation to engineering teams in real-time. With New Relic AI, engineers can detect, diagnose and resolve incidents faster, and continuously improve incident management workflow.

Coming soon, engineering teams will also be able to utilize New Relic Grok (currently in early access) to further enhance alerting by asking questions in natural language like “Hey Grok, what are the uncovered entities that I should be monitoring and what are the recommended conditions for this alert?” which will enhance the team's alert strategy and provide engineers with even better alert coverage.

Currently available as part of the New Relic platform, recommended alerts are now available at no additional cost to existing New Relic users.

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New Relic Adds AI Recommended Alerts

New Relic further enhanced its AIOps capabilities with recommended alerts. This provides the ability to quickly detect and easily resolve alert coverage gaps by using AI to identify anomalous behavior, determine areas of the technology stack that aren’t being monitored, and recommend new alerts to engineers.

An observability solution that reduces the need to manually build numerous alert conditions using AI makes it easier to understand which signals are most important or what thresholds indicate performance problems. Now, every engineer, regardless of their experience level, can eliminate alerting blindspots—empowering them to detect, resolve, and respond to issues faster.

“In an increasingly dynamic landscape, it’s easy for engineering teams to be overwhelmed by the need to configure alerts across different layers of the technology stack, especially since manually creating alert policies can be time- and resource-intensive. This can cause enormous gaps in the team’s alerting policies, leaving them blind and incapable of responding quickly and confidently when things break,” said New Relic Chief Product Officer Manav Khurana. “We designed New Relic recommended alerts to remove those barriers, so teams have the alerts they need to proactively monitor their stack, diagnose incidents and prioritize them for immediate action before it impacts their customers, business, and bottom line.”

Powered by AIOps, New Relic recommended alerts streamlines alerting with its alert coverage gaps feature, which continuously and automatically highlights areas in an organization’s technology stack that are missing alert coverage across application performance monitoring (APM), mobile and browser entities. Then, New Relic fills alerting gaps by recommending new alerts with pre-populated alert conditions, such as error percentage or response time. Using the recommendations as a starting point, engineers can also customize their alerts by implementing additional parameters to tailor the alert conditions and drive even better coverage for the team.

New Relic recommended alerts builds upon New Relic AI, a suite of AIOps capabilities that understands historical alerts and applies machine learning (ML) and AI to significantly reduce alert noise, enrich incidents with context, and provide intelligence and automation to engineering teams in real-time. With New Relic AI, engineers can detect, diagnose and resolve incidents faster, and continuously improve incident management workflow.

Coming soon, engineering teams will also be able to utilize New Relic Grok (currently in early access) to further enhance alerting by asking questions in natural language like “Hey Grok, what are the uncovered entities that I should be monitoring and what are the recommended conditions for this alert?” which will enhance the team's alert strategy and provide engineers with even better alert coverage.

Currently available as part of the New Relic platform, recommended alerts are now available at no additional cost to existing New Relic users.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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