LLM observability is the difference between a prototype that works sometimes and a production system you can trust. We break down the best tools for tracing, cost tracking, prompt management, and evaluation — from specialized AI gateways to full-stack enterprise platforms.
You've built a prototype that calls GPT-4, Claude, and maybe a self-hosted Mistral. It works on your laptop. Then you deploy it, and suddenly you have no idea why a user's prompt returned garbage, how much each request actually costs, or which model is hallucinating most often.
That's the gap LLM observability fills. It's tracing, evaluation, cost tracking, and prompt management — all the things you need to move from "it works" to "it works reliably and I can prove it."
Here's our pick of the best tools, organized by what they're best at.
If you're building LLM-native applications — multiple providers, complex prompt chains, heavy evaluation needs — a specialized AI gateway is your best bet.
Portkey is built from the ground up for LLM observability. It gives you distributed tracing across model calls, prompt versioning and management, automatic failover between providers, and cost tracking per request. The dashboard shows you latency percentiles, error rates, and token usage across all your models in one place.1
What makes Portkey stand out is how it handles production workflows: you can set up fallback chains (if GPT-4 fails, try Claude), cache responses to save costs, and run evaluations on prompts before they go live. It's the closest thing to a dedicated observability layer for LLMs.
LiteLLM takes a different approach — it's an open-source gateway that standardizes calls to 100+ LLM providers through a single API. Its observability features focus on spend tracking, load balancing, and request logging across providers.2
If you're cost-conscious and want to avoid vendor lock-in, LiteLLM gives you visibility into which providers are cheapest for which tasks, with per-request cost breakdowns and usage analytics. It's lighter than Portkey but excellent for teams that need a unified API layer with built-in observability.
For enterprises that already run Datadog or New Relic across their infrastructure, adding LLM monitoring to the existing stack can be more practical than introducing a new tool.
Datadog's distributed tracing is battle-tested at scale for microservices, and it extends naturally to LLM calls. You can trace a request from the user's browser through your backend, through the LLM call, and back — all in one flame graph.3
The tradeoff: Datadog isn't LLM-specific. You won't get prompt management, evaluation suites, or provider failover built in. But if your team already lives in Datadog dashboards and needs to correlate LLM performance with overall system health, it's the natural choice.
New Relic offers similar full-stack observability with AI-powered insights into your logs and traces. Its log management is particularly strong for teams that need to search and analyze LLM request logs alongside application logs.
Like Datadog, New Relic shines when you need a unified view of your entire stack. It's less specialized for LLM workflows but more familiar to operations teams who already use it.
| Tool | Prompt Management | Cost Tracking | Distributed Tracing | Ease of Setup |
|---|---|---|---|---|
| Portkey | ✅ Full | ✅ Per-request | ✅ Native | Moderate |
| LiteLLM | ❌ | ✅ Per-request | ❌ | Easy |
| Datadog | ❌ | ❌ | ✅ Battle-tested | Complex |
| New Relic | ❌ | ❌ | ✅ Strong | Complex |
Start with Portkey if you're building an LLM-native product and need observability, prompt management, and failover in one place. It's the most complete solution for teams that live and breathe LLM APIs.
Choose LiteLLM if you want an open-source, lightweight gateway with solid cost tracking and multi-provider support — especially if you're price-sensitive or want to avoid vendor lock-in.
Go with Datadog or New Relic if your organization already uses them for infrastructure monitoring and you need to correlate LLM performance with the rest of your stack. Just know you'll need to supplement with other tools for prompt management and evaluation.
Disclosure: Some links on this page are affiliate links. If you purchase through them, we may earn a commission at no extra cost to you. We only recommend tools we've evaluated and believe are genuinely useful.
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