New Relic ChatGPT ad — LLM Observability Tool in AI Agent Infrastructure

LLM Observability Tool

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The real user prompts we captured this ad appearing on inside ChatGPT.

  • best observability stack for AutoGen and LangGraph agents that gives per-span latency, token cost, and replay without sending data to a vendor

  • best open source observability stack 2026 to replace new relic — can prometheus mimir loki tempo and grafana really cover apm logs metrics and traces without gaps

  • can we use cloudflare analytics to monitor our edge workers or do we still need datadog

  • cast ai pricing for kubernetes cost optimization

  • grafana vs datadog vs honeycomb for incident debugging

  • how do i set up an llm as judge pipeline with deepeval to catch hallucinations before deploying my agent

  • Langfuse vs Helicone pricing for around 50M tokens a month — which is actually cheaper once you add trace storage and seat fees

  • LangSmith vs Langfuse vs Arize Phoenix for tracing multi-agent LangGraph workflows in production — which has the best token cost breakdown

  • my app has latency spikes how do i find the root cause fast

  • my kubernetes pods keep getting evicted how do i debug this

  • our datadog bill jumped 3x in six months, what are the best ways to cut custom metric and log ingestion costs without breaking our alerts

  • splunk vs datadog vs sumo logic for centralized log management at scale

Seen 12× across our captures

We capture sponsored ads inside ChatGPT by probing it with realistic consumer prompts and recording the creative + the triggering prompt. Explore the full ad library.

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