Keywords AI
Datadog LLM vs Sentry
Compare Datadog LLM and Sentry side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Enterprise | — |
| Best For | Enterprise teams already using Datadog who want to add LLM monitoring | — |
| Website | datadoghq.com | sentry.io |
| Key Features |
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| Use Cases |
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When to Choose Datadog LLM vs Sentry
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
About Datadog LLM
Datadog's LLM Observability extends its industry-leading APM platform to AI applications. It provides end-to-end tracing from LLM calls to infrastructure metrics, prompt and completion tracking, cost analysis, and quality evaluation—all integrated with Datadog's existing monitoring, logging, and alerting stack. Ideal for enterprises already using Datadog who want unified observability across traditional and AI workloads.
About Sentry
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.
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.
Browse all Observability, Prompts & Evals tools →