Best Application Performance Monitoring (APM) Software for GraphQL

Find and compare the best Application Performance Monitoring (APM) software for GraphQL in 2025

Use the comparison tool below to compare the top Application Performance Monitoring (APM) software for GraphQL on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    AppSignal Reviews

    AppSignal

    AppSignal

    $23 per month
    Trusted by over 1,500 development teams, AppSignal delivers a comprehensive monitoring toolkit designed to help developers confidently ship code. AppSignal offers easy-to-use tools for performance monitoring, error tracking, log and host management, uptime checks, and more—all within a single, intuitive platform. Built for simplicity, AppSignal ensures fast setup, responsive support, and clear pricing that fits teams of all sizes. Developers choose AppSignal for its lightweight, effective monitoring that lets them focus on building great software instead of troubleshooting.
  • 2
    Kloudfuse Reviews
    Kloudfuse is an observability platform powered by AI that efficiently scales while integrating various data sources, including metrics, logs, traces, events, and monitoring of digital experiences into a cohesive observability data lake. With support for more than 700 integrations, it facilitates seamless incorporation of both agent-based and open-source data without requiring any re-instrumentation, and it accommodates open query languages such as PromQL, LogQL, TraceQL, GraphQL, and SQL, while also allowing for the creation of custom workflows through notifications and webhooks. Organizations can easily deploy Kloudfuse within their Virtual Private Cloud (VPC) through a straightforward single-command installation and manage operations centrally using a control plane. The platform automatically collects and indexes telemetry data with smart facets, which helps deliver rapid search capabilities, context-aware alerts powered by machine learning, and service level objectives (SLOs) with minimized false positives. Users benefit from comprehensive visibility across the entire stack, enabling them to trace issues from user experience metrics and session replays all the way down to backend profiling, traces, and metrics, which makes troubleshooting more efficient. This holistic approach to observability ensures that teams can quickly identify and resolve code-level issues while maintaining a strong focus on enhancing user experience.
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