Portkey vs Sentry (2026)
Updated March 10, 2026
Overview
Portkey provides LLM observability alongside its gateway capabilities, offering detailed logging, metrics, and tracing for LLM API calls. Teams can monitor latency, costs, token usage, and error rates across providers, with request-level debugging and analytics dashboards for production AI applications.
Sentry provides runtime error monitoring and performance observability for AI applications. Its LLM monitoring capabilities track model calls, token usage, and latency alongside traditional error tracking. Sentry helps teams catch and debug issues in production AI pipelines with detailed stack traces and context.
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Enterprise-scale monitoring (10B requests/month)
- Sub-40ms overhead
- Comprehensive analytics and tracing
- Strong security certifications
Cons
- Professional tier expensive (USD 2-5k/mo)
- Open-source has limited features
- Complex for small teams
Pros
- Developer-friendly platform
- Production-ready
- Good performance
- Active development
Cons
- Enterprise pricing varies
- Setup complexity
- Learning curve
Compare Portkey and Sentry on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.
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