Prompt
What platform is best for production monitoring of agents?
Latest observation
“Best” depends on what kind of agents you mean and what you need to monitor.
If you mean AI/LLM agents in production
Top choices are usually:
- LangSmith — best for teams already using LangChain/LangGraph; strong tracing, debugging, evals, and dataset-based testing.
- OpenTelemetry + a backend like Datadog / New Relic / Grafana — best if you want vendor flexibility and standard observability across your whole stack.
- Helicone — good for lightweight LLM request monitoring, cost tracking, and prompt/response logs.
- Arize Phoenix — strong for evaluation, tracing, and LLM debugging, especially if you care about quality analysis.
- Weights & Biases Weave — useful for experiment tracking plus tracing and evaluation workflows.
If you mean traditional software agents / distributed services
- Datadog is often the strongest all-around production monitoring platform.
- Grafana + Prometheus + Loki + Tempo is great if you want open-source and control.
- New Relic is also a solid full-stack APM option.
Practical recommendation
- Best all-around for production AI agents: LangSmith if you’re in the LangChain ecosystem.
- Best open standard approach: OpenTelemetry + Datadog/Grafana.
- Best for simple LLM usage monitoring: Helicone.
If you tell me:
- what kind of agents you’re running,
- your stack, and
- whether you care most about traces, evals, cost, or alerts,
I can recommend a more specific platform.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.