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New Relic AI

Name: New Relic AI
Brand: New Relic AI
Availability: InStock
Rating: 4.6 (11 reviews)

AI-powered observability platform that provides intelligent monitoring, anomaly detection, and automated root cause analysis for applications and infrastructure

Starting at$0/month (Free tier with 100 GB data ingest); paid plans usage-based, per-GB rates vary by data type and tier

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In Plain English

AI-powered observability platform that provides intelligent monitoring, anomaly detection, and automated root cause analysis for applications and infrastructure

Overview

New Relic AI transforms application performance monitoring and observability through advanced artificial intelligence and machine learning capabilities. The platform ingests telemetry data from across your entire technology stack—applications, infrastructure, containers, serverless functions, logs, and browser sessions—and applies AI-driven analysis to surface anomalies, correlate incidents, and suggest root causes automatically. Unlike traditional monitoring tools that rely on static thresholds and manual configuration, New Relic AI continuously builds dynamic baselines from billions of data points and detects meaningful deviations before they escalate into customer-facing outages.

Designed for DevOps engineers, SREs, platform teams, and development organizations of all sizes, New Relic AI serves as a unified observability layer that eliminates the need to stitch together multiple point solutions. The platform's AI assistant, New Relic AI (NRAI), allows users to query their telemetry data using natural language, build dashboards conversationally, and get plain-English explanations of complex system behaviors. This dramatically lowers the barrier for on-call engineers and less experienced team members to diagnose production issues quickly.

New Relic operates on a consumption-based pricing model with two billing dimensions: data ingest and user seats. The free tier includes 100 GB of monthly data ingest, one full-platform user, and access to all 30+ observability capabilities—making it one of the most generous free offerings in the monitoring space. Paid tiers add volume discounts, advanced compliance certifications, and premium support. With over 700 pre-built integrations spanning AWS, Azure, GCP, Kubernetes, major programming languages, CI/CD tools, and third-party services, New Relic connects to virtually any component in a modern technology stack with minimal configuration.

The platform's AI capabilities extend beyond simple anomaly detection. New Relic AI correlates related incidents across services, infrastructure, and deployments to automatically identify probable root causes. It understands application dependency maps and business impact, prioritizing alerts based on actual customer experience rather than raw technical metrics. The AI engine continuously learns from system behavior patterns and operator feedback to improve detection accuracy and reduce false positives over time, adapting to each organization's unique operational patterns.

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Editorial Review

New Relic AI is widely praised for its comprehensive full-stack observability platform that consolidates monitoring into a single unified view. Users consistently highlight the generous free tier, powerful NRQL query language, and the AI assistant's ability to simplify complex investigations. Common criticisms center on data ingest costs that can escalate unpredictably at scale and per-user pricing that becomes expensive for larger teams. The platform's breadth is seen as both a strength and a challenge, with some users noting a steep initial learning curve.

Key Features

•AI-powered anomaly detection and root cause analysis
•Natural language querying via New Relic AI assistant
•Full-stack observability across APM, infrastructure, logs, and browser
•700+ out-of-the-box integrations
•NRQL query language for ad-hoc telemetry analysis
•Distributed tracing across microservices
•Kubernetes and container monitoring
•Consumption-based pricing with generous free tier

Pricing Plans

Free

$0/month

✓100 GB free data ingest per month
✓1 full-platform user
✓Unlimited basic users
✓Access to all 30+ observability capabilities
✓Community support

Standard

Usage-based

✓100 GB free data ingest included
✓Additional data charged per GB (rates vary by data type; see current pricing page)
✓Up to 5 full-platform users
✓Core platform features
✓Email support

Pro

Usage-based

✓100 GB free data ingest included
✓Unlimited full-platform users (per-user pricing)
✓Advanced alerting and AI capabilities
✓HIPAA and FedRAMP eligibility
✓Priority technical support with SLAs

Enterprise

Custom

✓Volume-based data ingest discounts
✓Unlimited full-platform users (per-user pricing)
✓Advanced security and compliance certifications
✓Dedicated account management
✓Premium support with training and onboarding

See Full Pricing →Free vs Paid →Is it worth it? →

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Best Use Cases

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Microservices incident response: SRE teams investigating production outages across distributed architectures can use AI-driven root cause analysis and distributed tracing to pinpoint the failing service in a dependency chain within minutes rather than hours

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Kubernetes platform monitoring: Platform engineering teams running multi-cluster Kubernetes environments can monitor cluster health, resource utilization, pod scheduling issues, and application performance in a single unified view with automated anomaly detection

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E-commerce performance optimization: Online retail teams can correlate frontend browser performance, backend API latency, and infrastructure metrics to identify bottlenecks in the purchase funnel and quantify the revenue impact of performance degradation

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CI/CD pipeline observability: DevOps teams can instrument deployment pipelines with change tracking markers and correlate deployments with performance regressions, enabling automatic detection of which release introduced a latency increase or error rate spike

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Cloud cost and performance balancing: Engineering teams running workloads on AWS, Azure, or GCP can use infrastructure monitoring alongside APM to right-size instances, identify underutilized resources, and ensure auto-scaling policies are responding appropriately to actual demand patterns

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On-call triage for junior engineers: Teams with rotating on-call schedules can leverage the natural language AI assistant to help less experienced engineers investigate alerts and understand system behavior without requiring deep institutional knowledge of every service

Integration Ecosystem

38 integrations

New Relic AI works with these platforms and services:

🗄️ Databases

MySQLPostgreSQLMongoDBRedisElasticsearch

View full Integration Matrix →

Limitations & What It Can't Do

We believe in transparent reviews. Here's what New Relic AI doesn't handle well:

⚠Data retention on lower tiers is limited to 8 days for raw data, which may be insufficient for teams needing long-term trend analysis or compliance-driven audit trails
⚠The platform requires instrumentation agents to be deployed in application code and infrastructure, which adds operational overhead and can introduce compatibility issues with certain runtime environments or legacy systems
⚠Real-time alerting has a minimum evaluation window, meaning sub-second anomalies or extremely transient issues may not trigger notifications reliably
⚠Custom instrumentation for proprietary protocols or niche frameworks requires manual SDK integration work, as the auto-instrumentation agents primarily support mainstream languages and frameworks
⚠Multi-account and cross-organization data correlation is limited, making it challenging for large enterprises with complex organizational structures to get a unified view across business units

Pros & Cons

✓ Pros

✓Generous free tier with 100 GB/month data ingest and full platform access makes it accessible for small teams and startups
✓Unified platform consolidates APM, infrastructure, logs, browser, and synthetics into a single pane of glass, reducing tool sprawl
✓Natural language AI assistant allows engineers to query complex telemetry data without memorizing query syntax
✓Over 700 integrations provide broad coverage across cloud providers, languages, frameworks, and CI/CD tools with minimal setup
✓Consumption-based pricing means you only pay for the data you ingest, avoiding per-host or per-container licensing surprises in dynamic environments
✓NRQL query language is powerful and flexible, enabling sophisticated ad-hoc analysis that goes well beyond pre-built dashboards

✗ Cons

✗Data ingest costs can escalate rapidly at scale—high-volume environments with verbose logging may face unexpectedly large bills without careful governance
✗Per-user pricing for full-platform seats adds up quickly for larger engineering organizations where many people need query and dashboard access
✗NRQL has a learning curve for teams accustomed to Prometheus PromQL or Elasticsearch query syntax, requiring investment in training
✗The sheer breadth of features and configuration options can overwhelm new users, making initial setup and dashboard customization time-consuming
✗Some advanced AI and compliance features are locked behind Pro and Enterprise tiers, limiting value on lower plans

Frequently Asked Questions

How does New Relic AI differ from traditional APM monitoring?+

Traditional APM tools rely on manually configured static thresholds to trigger alerts—for example, alerting when CPU exceeds 80% or response time crosses 500ms. New Relic AI instead builds dynamic baselines by continuously analyzing your system's normal behavior patterns and detects statistically significant deviations automatically. This means it can catch subtle performance degradations that static thresholds would miss, while also reducing alert noise from benign spikes that fall within normal variance. The AI also correlates anomalies across related services to surface root causes rather than just symptoms.

What is included in New Relic's free tier and is it suitable for production use?+

New Relic's free tier includes 100 GB of data ingest per month, one full-platform user, unlimited basic users, and access to all 30+ observability capabilities including APM, infrastructure monitoring, log management, and browser monitoring. This is genuinely usable for production workloads in small teams or startups with moderate telemetry volumes. The key limitation is the single full-platform user seat—only one person gets full query, alerting, and dashboard capabilities, while basic users have read-only access. There are no feature gates on the free tier, making it one of the more generous offerings in the observability space.

How does New Relic's pricing work and what should I watch out for?+

New Relic uses a consumption-based model with two billing dimensions: data ingest (charged per GB beyond the free 100 GB/month) and user seats (charged per full-platform user per month). Data pricing varies by type—metrics, events, logs, and traces each have different per-GB rates. Exact rates depend on your plan tier and committed volume; check New Relic's current pricing page for the latest per-GB rates as these are updated periodically. The biggest cost surprise for most teams is log data, which can be extremely voluminous. To manage costs, New Relic provides data management tools including drop filters, sampling rules, and ingest dashboards. Setting data ingest budgets and alerts before onboarding production workloads is strongly recommended.

Can New Relic monitor Kubernetes and containerized environments?+

Yes, New Relic provides comprehensive Kubernetes observability through its Kubernetes integration, which deploys as a Helm chart into your cluster. It collects metrics from nodes, pods, containers, and deployments, and correlates them with APM data from instrumented applications running in those containers. The platform provides pre-built Kubernetes dashboards showing cluster health, resource utilization, pod restarts, and deployment status. Distributed tracing works across containerized microservices, and the Kubernetes cluster explorer provides a visual map of your cluster topology with real-time health indicators.

How does the New Relic AI assistant work and what can it do?+

The New Relic AI assistant (NRAI) is a conversational interface embedded in the platform that lets you interact with your telemetry data using natural language. You can ask questions like 'What caused the latency spike in the checkout service at 3pm?' and it will generate and execute the appropriate NRQL queries, analyze the results, and explain findings in plain English. It can also help build dashboards, create alert conditions, and explain error traces. The assistant is powered by large language models with access to your New Relic data context, making it particularly useful for on-call engineers who need to investigate incidents quickly without deep platform expertise.

🔒 Security & Compliance

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SOC2

Unknown

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GDPR

Unknown

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HIPAA

Unknown

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SSO

Yes

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Self-Hosted

Unknown

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On-Prem

Unknown

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RBAC

Yes

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Audit Log

Unknown

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API Key Auth

Unknown

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Open Source

Unknown

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Encryption at Rest

Unknown

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Encryption in Transit

Unknown

Data Residency: US, EU

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What's New in 2026

In 2025-2026, New Relic has continued enhancing its AI-powered observability capabilities. The New Relic AI assistant (NRAI) has received significant updates with improved natural language understanding and broader coverage for root cause analysis across distributed systems. The platform has expanded its integration ecosystem beyond 700 connectors and introduced enhanced Kubernetes observability features including improved cluster explorer views and resource optimization recommendations. New Relic has also refined its consumption-based pricing model and updated data governance tools to help teams better manage ingest costs. The platform added expanded compliance certifications and data residency options to address growing enterprise security requirements.

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