Respan vs Sentry: Observability, Prompts & Evals Comparison
Compare Respan and Sentry side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose Respan if unified observability across all LLM providers in one dashboard.
Choose Sentry if developer-friendly platform.
Want to compare Respan 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 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
Quick Comparison
Pros & Cons: Respan vs Sentry
- +Unified observability across all LLM providers in one dashboard
- +Real-time alerting for cost spikes, latency, and quality issues
- +Built-in evaluation tools for automated quality scoring
- +Prompt management with versioning and A/B testing
- +Easy integration with popular AI frameworks
- −Newer platform building out integrations with more frameworks
- −Advanced evaluation features require configuration effort
- −Smaller community compared to established observability tools
- +Developer-friendly platform
- +Production-ready
- +Good performance
- +Active development
- −Enterprise pricing varies
- −Setup complexity
- −Learning curve
Pricing: Respan vs Sentry
- · 10,000 traces/month
- · 7-day retention
- · Basic dashboards
- · Community support
- · 100,000 traces/month
- · 30-day retention
- · Advanced analytics
- · Priority support
- · Unlimited traces
- · Custom retention
- · SSO and RBAC
- · Dedicated support
- · Core features
- · Community support
- · Basic limits
- · Advanced features
- · Higher limits
- · Priority support
- · Custom solutions
- · Dedicated support
- · SLA guarantees
About Respan
Respan Observability provides comprehensive LLM monitoring and debugging for AI applications in production. The platform tracks every prompt, completion, latency metric, cost, and quality signal across all LLM providers from a single dashboard, giving engineering teams full visibility into their AI stack.
The observability suite includes real-time tracing of LLM calls with detailed breakdowns of token usage, response times, and error rates. Teams can set up alerts for cost spikes, latency degradation, or quality drops, and drill into individual traces to debug issues. Built-in evaluation tools enable automated quality scoring of LLM outputs using custom rubrics or reference-based evaluation.
Prompt management features allow teams to version, test, and deploy prompts without code changes. A/B testing capabilities enable comparing model performance across different configurations, and semantic caching identifies repeated queries to reduce costs. The platform integrates with popular frameworks like LangChain, LlamaIndex, and the Vercel AI SDK.
About Sentry
Sentry provides error tracking and performance monitoring with AI-powered insights for applications. The platform provides comprehensive features for production AI applications with focus on reliability and developer experience.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
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Run Observability, Prompts & Evals in production with Respan
One platform for routing, observability, tracing, and evals across every LLM provider.