8 Best Alternatives to New Relic for Observability in 2026

Why look beyond New Relic

New Relic provides a comprehensive suite of observability tools covering application performance monitoring (APM), infrastructure, logs, and real user monitoring (RUM). Its platform is designed for full-stack visibility, supporting distributed tracing across microservices and offering detailed performance analytics for various applications New Relic documentation. Developers often value its unified dashboards and query capabilities for diagnosing issues across complex systems.

However, organizations may seek alternatives due to several considerations. New Relic's usage-based pricing model, primarily on data ingest and user seats New Relic pricing page, can become a significant factor for large-scale deployments with high data volumes. Teams might also look for platforms with deeper integrations into specific cloud ecosystems, specialized AI-driven anomaly detection, or different approaches to data retention and customization. Some alternatives offer open-source components that allow greater control over data and infrastructure, which can be appealing for organizations prioritizing cost control or specific compliance requirements.

Top alternatives ranked

1. 1. Datadog — unified monitoring and security platform

   Datadog is a monitoring and security platform for cloud applications. It combines infrastructure monitoring, application performance monitoring (APM), log management, user experience monitoring, and security monitoring into a unified platform. Datadog features over 600 integrations Datadog integrations overview, allowing it to collect metrics, traces, and logs from a wide array of services, databases, and cloud providers. Its strength lies in its ability to correlate data across different layers of the stack, providing context for performance issues and security threats. The platform offers customizable dashboards, real-time alerts, and a query language for data analysis.

   Datadog's APM provides distributed tracing, code-level visibility, and service maps to understand application dependencies. Its infrastructure monitoring offers host-level metrics, container monitoring, and serverless function tracking. For security, Datadog offers Cloud SIEM, Cloud Security Posture Management (CSPM), and Application Security Management (ASM) to detect threats and vulnerabilities across cloud environments. The platform is designed for rapid deployment and scalability, making it suitable for dynamic cloud-native architectures.

   Best for:

   • Cloud-native architectures with extensive integrations
   • Unified security and observability
   • Real-time alerting and customizable dashboards
   • Large-scale distributed systems

2. 2. Dynatrace — AI-powered full-stack observability

   Dynatrace offers an AI-powered software intelligence platform designed for full-stack observability, application security, and automation. Its core strength is its proprietary OneAgent technology, which automatically discovers, monitors, and analyzes applications, microservices, infrastructure, and user experience. Dynatrace uses its Davis AI engine to provide automatic root-cause analysis and anomaly detection Dynatrace AI-powered observability, reducing manual effort in identifying performance bottlenecks. The platform supports a wide range of environments, including multi-cloud, hybrid-cloud, and mainframe systems.

   Dynatrace's APM capabilities include distributed tracing, code-level visibility, and service-level objective (SLO) tracking. Its infrastructure monitoring covers hosts, containers, and serverless functions, while its log management solution provides automated log ingestion and analysis. Dynatrace also offers digital experience monitoring (DEM), including real user monitoring (RUM) and synthetic monitoring, to track user journeys and application availability. The platform emphasizes automation, from deployment to problem remediation, which can reduce operational overhead for development and operations teams.

   Best for:

   • Organizations requiring AI-driven root-cause analysis
   • Automated discovery and monitoring of complex environments
   • Comprehensive digital experience monitoring
   • Hybrid and multi-cloud observability

3. 3. Splunk — data platform for security, observability, and operations

   Splunk provides a data platform for security, observability, and operations, enabling organizations to collect, index, search, and analyze machine-generated data. While traditionally known for its security information and event management (SIEM) capabilities, Splunk has expanded significantly into observability with products like Splunk Observability Cloud. This suite includes APM (formerly SignalFx), infrastructure monitoring, log investigation, real user monitoring, and synthetic monitoring. Splunk's core strength is its ability to ingest and process vast amounts of unstructured and semi-structured data from diverse sources Splunk Data Platform overview.

   Splunk Observability Cloud offers high-fidelity metrics, traces, and logs for cloud-native applications, providing rapid insights into performance issues. Its APM solution supports distributed tracing and code-level visibility, while its infrastructure monitoring provides real-time visibility into hosts, containers, and serverless functions. Splunk's log investigation tools allow for powerful searching and analysis of operational data. The platform's extensible architecture and SPL (Splunk Processing Language) enable users to create custom dashboards, alerts, and reports, making it flexible for various use cases beyond traditional monitoring.

   Best for:

   • Organizations with large volumes of machine data
   • Unified security and operational intelligence
   • Customizable data analysis and reporting
   • Cloud-native application observability

4. 4. Firebase — mobile and web app development platform with analytics

   Firebase, a platform developed by Google, offers a comprehensive suite of tools for building, deploying, and monitoring mobile and web applications. While not a direct full-stack observability platform in the same vein as New Relic, Firebase provides critical monitoring and analytics capabilities essential for app performance and user experience. Its features include Crashlytics for real-time crash reporting, Performance Monitoring for app startup times and network requests, and Google Analytics for Firebase to track user engagement and behavior Firebase Analytics documentation. These tools provide developers with insights into issues that affect app quality and user satisfaction.

   Firebase's ecosystem extends beyond monitoring, offering backend services like Cloud Firestore (a NoSQL database), Authentication, Cloud Functions (serverless backend), and Storage. This integrated approach allows developers to build entire applications and monitor their performance within a single platform. For many mobile-first or web-first applications, Firebase provides sufficient telemetry for critical application health and user metrics without requiring separate observability agents. Its free tier and scalable infrastructure make it attractive for startups and projects that need integrated development and monitoring tools.

   Best for:

   • Mobile and web application development with integrated monitoring
   • Real-time crash reporting and performance insights
   • User behavior analytics and engagement tracking
   • Startups and projects needing a comprehensive backend-as-a-service

5. 5. Elastic Stack — open-source observability with powerful search

   The Elastic Stack, composed of Elasticsearch, Kibana, Beats, and Logstash (ELK Stack), offers an open-source solution for searching, analyzing, and visualizing large volumes of data in real time. It serves as a robust foundation for building custom observability solutions, handling logs, metrics, and traces. Elasticsearch provides a distributed, RESTful search and analytics engine, while Kibana offers powerful visualization capabilities, enabling users to create interactive dashboards and explore data. Beats are lightweight data shippers that send data from machines to Elasticsearch or Logstash, and Logstash is a server-side data processing pipeline that ingests, transforms, and loads data Elastic Stack overview.

   For observability, the Elastic Stack provides dedicated solutions: Elastic APM for distributed tracing and application performance monitoring, Elastic Logs for centralized log management, and Elastic Metrics for infrastructure monitoring. Users can deploy Elastic Cloud for a managed service or self-host the stack for complete control over their data. Its flexibility and extensibility make it suitable for organizations that prefer open-source solutions and require granular control over their observability data and infrastructure. The ability to customize every component allows tailoring the stack to specific operational needs and data processing pipelines.

   Best for:

   • Organizations preferring open-source solutions
   • Customizable log, metrics, and trace management
   • Powerful search and analytics capabilities
   • Self-hosting and granular data control

6. 6. Grafana, Loki, Tempo, Prometheus — open-source monitoring ecosystem

   This combination represents a powerful open-source ecosystem for observability, often used together to provide a comprehensive monitoring solution. Prometheus is an open-source monitoring system with a dimensional data model, flexible query language (PromQL), and alert management Prometheus documentation. It is primarily used for collecting and storing time-series metrics. Grafana is an open-source platform for analytics and interactive visualization, allowing users to create dashboards and visualize data from multiple sources, including Prometheus, Loki, and Tempo Grafana documentation.

   Loki is a horizontally scalable, highly available, multi-tenant log aggregation system inspired by Prometheus. It indexes only metadata about logs, not the logs themselves, making it efficient for log management. Tempo is a distributed tracing backend designed to be cost-efficient and scalable, integrating with Prometheus and Grafana for full observability. Together, these tools provide robust capabilities for metrics, logs, and traces, allowing organizations to build a complete observability stack with open-source components. This approach offers significant flexibility and avoids vendor lock-in, though it requires more self-management.

   Best for:

   • Organizations committed to open-source technologies
   • Customizable and scalable monitoring solutions
   • Metrics, logs, and traces as separate, specialized components
   • Avoiding vendor lock-in with community-driven tools

7. 7. Azure Monitor — native cloud monitoring for Azure environments

   Azure Monitor is the native monitoring solution for applications and infrastructure running on Microsoft Azure. It collects and analyzes telemetry data from Azure resources, on-premises environments, and other clouds. Azure Monitor provides comprehensive capabilities for collecting metrics, logs, and traces, offering insights into the performance and health of applications and services. It integrates deeply with other Azure services, providing out-of-the-box monitoring for virtual machines, databases, web apps, and serverless functions Azure Monitor overview.

   Key features include Application Insights for APM, providing distributed tracing, dependency mapping, and user session analysis for .NET, Java, Node.js, and other applications. Azure Monitor Logs (based on Log Analytics Workspace) offers a powerful query language for analyzing operational logs. Azure Monitor Metrics provides real-time performance data with customizable alerts and dashboards. For organizations heavily invested in the Azure ecosystem, Azure Monitor offers a seamless and integrated monitoring experience, often simplifying deployment and management compared to third-party tools. It also integrates with Azure Security Center and Azure Sentinel for a unified security and operations view.

   Best for:

   • Organizations primarily leveraging Microsoft Azure services
   • Native integration with Azure infrastructure and applications
   • Unified logging, metrics, and APM within the Azure ecosystem
   • Simplified management for Azure-centric deployments

Side-by-side

How to pick

Selecting an observability platform requires evaluating your organization's specific technical requirements, operational philosophy, and budget. The ideal choice will align with your existing infrastructure, application stack, and security protocols.

Consider your primary environment:

• If your infrastructure is primarily on Microsoft Azure, Azure Monitor offers the most seamless and native integration for monitoring resources, applications, and services within that ecosystem. It simplifies deployment and management by leveraging existing Azure accounts and practices.
• For organizations with a significant investment in cloud-native architectures and a need for extensive third-party integrations, Datadog stands out. Its unified platform for monitoring and security, combined with a vast array of integrations, makes it suitable for complex, distributed cloud environments.
• If you are building mobile-first or web-first applications and seek an integrated development and monitoring experience, Firebase provides strong analytics, crash reporting, and performance monitoring capabilities alongside its backend services. This can be particularly beneficial for startups or projects seeking a comprehensive platform for app lifecycle management.

Assess your need for AI and automation:

• If AI-driven root-cause analysis and highly automated observability are critical for your operational efficiency, Dynatrace provides advanced capabilities with its Davis AI engine, automating much of the discovery and problem identification process.
• For those prioritizing comprehensive security and operational intelligence alongside observability, Splunk, with its powerful data platform and SIEM heritage, offers robust capabilities for ingesting and analyzing vast amounts of machine data for both security and performance insights.

Evaluate your preference for open-source vs. commercial solutions:

• Organizations that prefer open-source tools for flexibility, control, and cost management should consider the Elastic Stack or the combination of Prometheus, Grafana, Loki, and Tempo. The Elastic Stack provides a consolidated platform for logs, metrics, and traces, while the Grafana ecosystem offers specialized, best-of-breed components that can be highly customized. These options require more self-management but offer significant control and can be more cost-effective for large-scale deployments when managed effectively.

Consider pricing models and scalability:

• Review the pricing structures of each alternative. New Relic's model is based on data ingest and user seats. Alternatives like Datadog, Dynatrace, and Azure Monitor also use various consumption-based models (hosts, containers, data volume, DEM units). Open-source solutions generally have no software license cost but incur infrastructure and operational costs. Ensure the chosen platform's pricing scales predictably with your anticipated growth in traffic and data volume.

By carefully weighing these factors against your organization’s unique requirements, you can identify the observability solution that best supports your development, operations, and business goals.