AI observability

New Relic ✓

AI-powered observability platform that predicts and prevents issues.

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Verdict

A quick read before you dig into the full page.

Best if
AI-powered observability platform that predicts and prevents issues
Skip if
Potentially complex initial setup
Pick this when
Automated remediation

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Overview

New Relic is an AI-empowered observability platform designed for comprehensive system telemetry. It is geared to consolidate and correlate data from your entire stack, assisting you in pinpointing the root cause and subsequently minimizing Mean Time To Resolution (MTTR).

The platform offers various features aimed at ensuring optimal system performance. This includes functionalities for automated remediation, AI-guided session replay, multi-cloud and Kubernetes spend visibility, AI and agent monitoring, and adherence to open telemetry standards.

Providing a platform for delivering observability insights to AI agents in the work environment, New Relic considers both precision and scale. Having integrated AI in its monitoring functions, the platform is capable of detecting and addressing friction points, enabling real-time control over AI system behavior and resource usage.

Furthermore, it offers infrastructure monitoring and log management, ensuring a full overview of cloud-native and Kubernetes environments with the added ability to query data logs in-place.

Included in its toolkit is a dedicated security feature which uses production impact data for prioritizing and resolving vulnerabilities, implementing additional AI reasoning for more efficient outcomes.

As an outcome, New Relic aims to seamlessly blend application performance with the customer experience, maintaining a user-centric focus that maximizes conversions and reduces friction in user experiences.

New Relic website

Access & connections

Where you can use New Relic, and what it plugs into.

Platforms

Web

Integrations

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API

Output

  • API

Pros & cons

Pros

  • Automated remediation
  • Multi-cloud spend visibility
  • Kubernetes spend visibility
  • Agent monitoring
  • Supports open telemetry standards
  • Optimized resource usage
  • Infra monitoring
  • Log management
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  • Cloud-native environment monitoring
  • Kubernetes environment tracking
  • In-place data log queries
  • Dedicated security feature
  • Uses production impact data
  • Prioritizes vulnerabilities resolution
  • User-centric
  • Maximizing conversions
  • Reduced user experience friction
  • Precision and scale
  • Friction point detection
  • Root cause detection
  • Minimizes MTTR
  • Correlates telemetry data
  • Comprehensive system overview
  • Session friction pinpointing
  • Customer experience driven
  • Optimal system performance
  • Unified vulnerability management
  • Unified application performance
  • Developer productivity
  • Business-aligned
  • Instant data search
  • Data compliance simplification
  • Data toil reduction
  • Optimized cloud costs
  • Unified customer experience
  • Universal OpenTelemetry standard
  • Observability in work environment
  • Prevent infrastructure outages
  • Cost optimization
  • Comprehensive telemetry correlation

Cons

  • No offline functionality
  • Potentially excessive data monitoring
  • Limited customization options
  • Potentially complex initial setup
  • Only provides in-place data query
  • Requires comprehensive stack for full functionality
  • No mentioned mobile compatibility
  • Full feature use may require extensive cloud services
Show 1 more
  • No explicit multi-language support

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Releases 1

Initial release August 1, 2023 Current
Initial release of New Relic.

FAQ 12

What is the main purpose of New Relic?
New Relic's main purpose is to provide an AI-empowered observability platform designed for comprehensive system telemetry. It assists in consolidating and correlating telemetry across an entire stack, with the goal of pinpointing the root cause of issues and minimizing Mean Time To Resolution (MTTR). It aims to maintain optimal system performance while enhancing user experience and maximizing conversions.
How does New Relic utilize AI functionality?
AI in New Relic is integrated within its monitoring functions and is used to detect and address friction points in real-time. AI intelligence is used to deliver observability insights to AI agents in the work environment. It also enhances session replays by identifying friction points automatically. In their security feature, AI reasoning is employed to prioritize and resolve vulnerabilities more efficiently.
What kind of data can New Relic consolidate and correlate?
New Relic is capable of consolidating and correlating a wide array of data from your entire stack. This includes telemetry data, AI system behavior, multi-cloud and Kubernetes spend data, log data, production impact data, and data related to infrastructure health and performance.
How does New Relic assist in pinpointing the root cause of system issues?
New Relic assists in pinpointing the root cause of system issues by providing a consolidated view of fault, configuration, and performance data collected from the entire technology stack. By correlating this data, it helps in isolating where and when issues happened thereby reducing the mean time to identify the root cause.
What does Mean Time To Resolution (MTTR) mean in the context of New Relic?
In the context of New Relic, Mean Time To Resolution (MTTR) stands for the average time required to resolve a fault or failure in a system, from the time an issue is identified to the time it is resolved. New Relic's data consolidation, correlation, and observability features are designed to assist in reducing the MTTR by facilitating quicker identification and resolution of issues.
What features does New Relic provide for automated remediation?
New Relic provides features like automated remediation which move beyond assistance to automatic resolution of system issues. It achieves this by leveraging AI capabilities to predict and prevent potential system issues before they impact the performance.
Can New Relic monitor multi-cloud and Kubernetes spend?
Yes, New Relic is designed to provide real-time visibility into multi-cloud and Kubernetes spend, thus enabling effective overall resource management and cost optimization.
What is AI-guided session replay in New Relic?
The AI-guided session replay in New Relic is a feature that employs AI to automatically identify potential friction points within user sessions without the need for manual search through the video. It assists in pinpointing elements of the user session that may create a less than optimal user experience.
How does New Relic adhere to open telemetry standards?
New Relic adheres to open telemetry standards by providing a platform that is capable of delivering observability insights to AI agents where they work. It doesn't require additional instrumentation or vendor-specific agents, thus enabling a future-proof universal open standard for every signal.
How does New Relic help in controlling AI system behavior and resource usage in real-time?
New Relic helps in real-time control over AI system behavior and resource usage by utilizing AI-powered observability. It provides a unified view of all AI and agent activities across the stack, and enables automatic monitoring and control of behavior and token usage across the AI system.
Does New Relic offer infrastructure monitoring and log management?
Yes, New Relic offers infrastructure monitoring and log management capabilities. It assists in managing cloud-native and Kubernetes environments while enabling querying of data logs in-place.
How does New Relic contribute to overseeing cloud-native and Kubernetes environments?
New Relic contributes to overseeing cloud-native and Kubernetes environments by providing infrastructure monitoring features. It offers end-to-end visibility of the health and performance of these environments, thus ensuring system-wide context and optimization.
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