Last updated: March 2026
TraceKit vs Prometheus: Full-Stack APM vs Metrics and Alerting
Prometheus is the CNCF-graduated standard for metrics and alerting -- pull-based collection, PromQL queries, and rock-solid reliability. But Prometheus is not a tracing or APM tool. TraceKit provides what Prometheus does not: distributed tracing, error tracking, frontend monitoring, and live code debugging.
Information is based on publicly available data as of March 2026. Prometheus is a CNCF project -- check the official documentation for the latest.
Why developers choose TraceKit
Distributed Tracing Built In
Prometheus collects metrics. TraceKit collects traces, errors, and metrics. When a metric spikes, you can drill into the exact trace that caused it -- no context switching between tools.
Live Code Monitoring
Set live breakpoints in production code to inspect variable state. Prometheus can tell you something is slow via metrics, but TraceKit shows you exactly why at the code level.
Full-Stack in One Tool
Traces, errors, frontend monitoring, session replay, metrics, and dashboards. Prometheus handles metrics and alerting only -- you need Jaeger or Tempo for traces, Loki for logs, and Grafana for dashboards.
Feature Comparison
| Feature | TraceKit | Prometheus |
|---|---|---|
| Tracing | ||
| Distributed Tracing | Yes | No (metrics only) |
| Trace Visualization | Waterfall + Flamegraph | No |
| Monitoring | ||
| Metrics Collection | Yes (push-based) | Yes (pull-based, best-in-class) |
| PromQL Query Language | No | Yes (industry standard) |
| Live Code Monitoring | Yes -- breakpoints without redeploy | No |
| Error Tracking | Yes (browser + backend) | No |
| Alerting | Yes | Yes (Alertmanager) |
| Custom Dashboards | Yes | No (pair with Grafana) |
| Frontend Observability | ||
| Session Replay | Yes (linked to traces) | No |
| Source Maps | Yes (debug ID + upload CLI) | No |
| Browser-to-Backend Traces | Yes (W3C traceparent) | No |
| Platform | ||
| Setup Time | Under 5 minutes | 30 min - hours (scrape config + storage) |
| Long-term Storage | Built-in | Requires Thanos or Cortex |
| Pricing | ||
| Pricing Model | $29/month flat | Free (software) + infrastructure costs |
Pricing Comparison
TraceKit
$29/month
Flat monthly
One price includes distributed tracing, custom metrics, live code monitoring, dashboards, alerts, and security scanning. Built-in long-term storage.
None. What you see is what you pay.
Prometheus
Free (software), $100-500+/month (infrastructure with long-term storage)
Self-hosted (open source)
Free and open-source. Prometheus itself is lightweight, but production deployments need long-term storage (Thanos, Cortex, or Mimir) to retain metrics beyond 15 days. A production setup with HA and long-term storage costs $100-500+/month in infrastructure.
Cardinality management is an ongoing operational challenge -- high-cardinality labels can cause out-of-memory crashes. Thanos or Cortex for long-term storage adds significant infrastructure complexity. No managed support.
Pricing considerations with Prometheus
- Prometheus itself is free, but long-term storage (Thanos/Cortex) adds $100-500+/month in infrastructure
- Cardinality explosion from high-dimensional labels can crash Prometheus or spike storage costs
- Prometheus provides metrics only -- you still need separate tools for tracing, errors, and frontend monitoring
- HA setup (multiple Prometheus instances + deduplication) adds operational and infrastructure cost
Setup Comparison
See how TraceKit's setup compares to Prometheus:
// Prometheus: Instrument code + configure scrape targets
// # prometheus.yml
// scrape_configs:
// - job_name: 'my-app'
// static_configs:
// - targets: ['localhost:8080']
// // Expose /metrics endpoint, manage retention, add Thanos for long-term
// TraceKit: One-line SDK for traces, errors, and metrics
tracekit.Init("tk_your_key")When to choose Prometheus
We believe in honesty. Prometheus is a great product, and there are situations where it is the better choice.
- You only need metrics and alerting, not distributed tracing or error tracking
- You are running Kubernetes and want native service discovery and monitoring
- Your team has PromQL expertise and relies on Prometheus-based dashboards
- You need a proven, battle-tested metrics system with a massive ecosystem
Frequently Asked Questions
They solve different problems. Prometheus excels at metrics collection and alerting with its pull-based model and PromQL. TraceKit excels at distributed tracing, error tracking, frontend monitoring, and live debugging. If you only need metrics, Prometheus is the standard. If you need full APM, TraceKit covers more ground in one tool.
Absolutely. Many teams use Prometheus for infrastructure metrics and alerting alongside TraceKit for application-level tracing, error tracking, and frontend monitoring. They complement each other well -- Prometheus for the infrastructure layer, TraceKit for the application layer.
Prometheus is free software, but production infrastructure is not. A basic setup is cheap, but long-term storage via Thanos or Cortex costs $100-500+/month in infrastructure. Factor in engineering time for cardinality management and HA setup, and realistic TCO is $200-800+/month.
No. TraceKit has its own query interface for traces, metrics, and errors. If your team relies heavily on PromQL for dashboards and alerting rules, Prometheus remains the right choice for that use case. TraceKit focuses on simplicity over query language power.
Developers searching for monitoring solutions often evaluate both. The key insight is that Prometheus is metrics-focused while TraceKit is APM-focused. Understanding what each tool does and does not do helps you choose the right tool -- or decide to use both.
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