Datadog LLM Observability Alternative · EU · Self-hosted · Open Core

Looking for a Datadog LLM Observability alternative?
LLM observability without enterprise contracts.

Datadog's LLM observability is powerful — and locked behind enterprise contracts that start at multi-thousand monthly minimums. AgentLens delivers the core observability layer at a fraction of the cost, with EU residency and air-gap by default.

Book a Migration Call See Live Demo →
Quick Comparison

Feature-by-feature

Capability AgentLens Datadog LLM Observability
Self-hosted (free path)✓ open-core, BSL 1.1Limited / managed cloud only
Starting price✓ €299/mo flatCustom enterprise (often $5k+/mo)
Multi-step agent waterfalls✓ trace_agent + spans✓
Automatic quality + hallucination flags✓ heuristic, zero configEval framework, manual
Air-gap mode (single env var)✓ tcpdump-verifiedLimited (Datadog requires data flow to their cloud)
EU-hosted (default for managed)✓ FrankfurtEU region available
Plan-tier feature gating✓ Free / Starter / Team / Scale / EnterpriseEnterprise tiers
Compliance workflows (DPA, audit, retention)✓ Scale plan✓
Vendor lock-in surfaceLowHigher (Datadog agent + APM)

Based on public Datadog LLM Observability pricing as of May 2026. Verify at https://www.datadoghq.com/pricing/.

When to choose what

Honest recommendation

Choose Datadog LLM Observability if…

  • You're already a Datadog customer for APM + infrastructure
  • You have enterprise-tier budget approved
  • Cross-stack correlation (logs + APM + LLM) is valuable
  • You want a single vendor for full observability

Choose AgentLens if…

  • Your budget is mid-market, not enterprise (€299–2,999/mo)
  • You want LLM-specific observability without an APM agent in your runtime
  • EU residency / air-gap matter
  • You want to start free (self-hosted) and grow into a paid plan when ready
Migration

Switching from Datadog LLM Observability takes ~30 minutes

Both tools share a similar mental model. The SDK surface is different but migration is mechanical.

# Before (Datadog LLM)
from datadog import initialize, statsd
initialize(api_key="...", app_key="...")
 
# After (AgentLens)
import agentlens
agentlens.init("http://localhost:8000/ingest")
agentlens.patch_openai() # or patch_anthropic()
FAQ

Common questions

Why pick AgentLens over Datadog LLM observability?

Cost (10x cheaper at the entry point), no agent footprint in your runtime, EU residency by default, and a free self-hosted path so you can evaluate without procurement.

Can I run AgentLens alongside Datadog?

Yes — they're complementary. Datadog handles infrastructure + APM; AgentLens handles LLM-specific traces and evaluations.

Does AgentLens have anything Datadog doesn't?

Built-in heuristic quality scoring, hallucination flags, verifiable air-gap mode, and a clear self-hostable path with no enterprise contract gate.

Ready to own your LLM data?

15-minute migration call. We'll map your Datadog LLM Observability setup to AgentLens and get you running.

Book a Migration Call View Core Repo on GitHub