Meteor Error and Performance Monitoring
Get complete visibility into your Meteor errors and performance issues that are impacting your end user experience. Fix critical issues sooner with in depth data points that helps you in analyzing and resolving issues with great speed.
Unlock complete visibility into Meteor reactivity, publications, and real-time data flows
Meteor publication/subscription waterfalls
Track pub/sub latency, minimongo merges, and reactive query execution during live Meteor real-time application sessions.
Tracker recomputation profiling
Monitor reactive computations, autorun dependencies, and template helpers across Meteor full-stack workloads.
MongoDB oplog tailing performance
Measure real-time data sync, change stream processing, and minimongo oplog integration timing.
Meteor runtime error isolation
Capture Blaze template errors, reactive session failures, and DDP connection drops with full client/server context.
Real-time UI responsiveness
Detect delayed reactive UI updates, cursor subscription stalls, and live data rendering bottlenecks.
Pub/sub to UI correlation
Trace Meteor publications through DDP, minimongo, Tracker, to final template rendering paths.
Isomorphic SSR performance
Analyze Meteor server-side rendering, Flow Router transitions, and client hydration across deployments.
Meteor package optimization
Validate atmosphere package performance, bundle analysis, and reactive dependency graphs in production.
Break Down Meteor App Performance From Client to Server
Measure end-to-end method and publication timing, data fetch cost, API latency, and environment metrics so you expose where performance time is actually spent.
Unclear Timing for Meteor Methods
Without detailed spans, slow data updates or subscriptions can feel arbitrary, and per-request breakdowns are needed to show how long each method or publication actually takes.
External API Calls Inflate Perceived Delays
Live data sync through DDP or outbound HTTP calls can add noticeable waits, and capturing latency along these paths reveals which networks or APIs extend round-trip time.
Database Round-Trips Add Hidden Duration
Heavy MongoDB queries or repeated fetches inflate total method or publication execution time, and tying database cost to traces shows which calls drive duration.
Client-Side Interaction Metrics Are Masked
Slow UI updates, re-renders, or data merges can feel sluggish without clear breakdowns, and correlating client interaction timing with route and data traces shows where time accumulates.
Host Resource Conditions Affect End-to-End Timing
CPU saturation, garbage collection activity, or memory pressure on backend hosts can influence method and publication speed, and correlating infrastructure metrics with trace timing highlights real systemic impacts.
Why Choose Atatus for Meteor RUM?
Master Meteor real-time reactivity, pub/sub scaling, and isomorphic performance without Galaxy complexity
Built for Meteor reactivity
Native Tracker autorun tracing, minimongo merge analysis, and publication/subscription lifecycle monitoring.
Meteor real-time diagnostics
DDP message waterfalls, oplog tailing traces, and reactive computation profiling for production apps.
Zero-config Meteor integration
Automatic instrumentation for Meteor 1.10+, Blaze/React/Vue, and atmosphere packages—no manual pub/sub wrapping.
Meteor Core Web Vitals attribution
LCP/CLS/INP metrics tied to publication latency, Tracker recomputes, and minimongo sync timing.
Real-time app scaling
Enterprise-grade monitoring for high-concurrency Meteor deployments with live data synchronization.
Meteor growth pricing model
Scalable costs for Meteor real-time user sessions—no platform lock-in or deployment complexity.
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Trace requests, debug errors, and identify performance issues at the code level with clear context.
DevOps
Track deployments, monitor infrastructure impact, and understand how releases affect application stability.
Release Engineer
Measure service health, latency, and error rates to maintain reliability and reduce production risk.
Frequently Asked Questions
Find answers to common questions about our platform