New Relic ✓
AI-powered observability platform that predicts and prevents issues.
Trial; then from $10/mo
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
Considering Traccia instead? Compare side by side
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.
Access & connections
Where you can use New Relic, and what it plugs into.
Platforms
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
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- No explicit multi-language support
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