Datadog is the enterprise observability standard. If you already pay for APM, you can get basic LLM observability by adding Datadog's LLM Observability product. It's good at aggregated metrics, alert correlation with infra, and enterprise compliance. It's weaker at per-request assertions, agent-specific failure modes, and outside-in monitoring of third-party model providers.
One-line summary
- Agent Status: Agent Status is purpose-built for AI agents. Outside-in validations, semantic assertions, and per-request verdicts are native primitives.
- Datadog: Datadog is a full-stack observability platform with an LLM Observability add-on. Strongest when correlated with APM, infra, and logs across your whole stack.
Feature matrix
| Capability | Agent Status | Datadog |
|---|---|---|
| Outside-in synthetic agent validations | Native | Via Synthetics addon |
| Semantic assertions on response body | Native | Limited |
| APM + infra correlation | No | Strong |
| Prompt / trace visualization | Limited | Native |
| Agent-specific failure taxonomy | Native | No |
| Enterprise SSO + audit log | On Agency plan | Native |
| Per-model geographic p99 tracking | Native | Via Synthetics addon |
When to use Agent Status
- You need to know your users' experience, not your servers'.
- Your agent depends on a third-party model provider and you need to catch their outages.
- Your users are distributed geographically and you need regional alerting.
- You want alerts in seconds, not minutes of aggregated latency data.
When to use Datadog
- You already pay for Datadog APM and want one pane of glass.
- You need to correlate LLM metrics with infra, logs, and traces across the stack.
- You require enterprise compliance certifications Datadog already has.
- You're running models across many teams and need unified billing and RBAC.
What Datadog does that we don't
Correlating an LLM latency spike with an infra event four hops away in your stack. Datadog's breadth is its moat - if you're already paying, adding LLM Observability is the cheapest thing to try first.
What we do that Datadog doesn't
Agent-specific validations that actually assert on response content. Datadog's LLM Observability can show you what requests hit and how long they took; it cannot tell you that a response contained the wrong answer. Also dramatically lower cost at scale for outside-in validating.
Pricing
- Agent Status: Free tier: 30 tests/month, 1 agent, 3 regions, 6-hour minimum interval. Paid tiers unlock unlimited agents and regions with usage-based pricing. No per-seat fees.
- Datadog: LLM Observability priced per host + per million spans. Typically $15–40/host/month before volume discounts.
Most teams use both
If you already pay for Datadog, add LLM Observability and also add Agent Status. Datadog gives you the context of what was happening in the rest of your infrastructure; Agent Status gives you the validation that pages when a user in Singapore is getting a bad answer. At our price point, running both is almost free compared to either gap.
Related
- /vs/new-relic - New Relic comparison.
- /vs/langfuse - Langfuse comparison.
- /blog/what-is-outside-in-monitoring - Why outside-in matters.
- /platform - The product overview.
Frequently asked questions
Is Agent Status a replacement for Datadog?
No. Datadog LLM Observability adds agent metrics to enterprise APM (inside-out). Agent Status is purpose-built outside-in validation for agents. They complement each other.
When should I pick Agent Status over Datadog?
When you need to know whether the agent's answer is actually correct and fast for users worldwide - not just whether the service is up. Datadog is stronger for infrastructure-wide APM.
Can I use both?
Yes. Many teams keep Datadog for infrastructure and add Agent Status for agent-specific, user-facing validation.
How does setup compare?
Agent Status needs no agents or instrumentation - point it at your endpoint and you're live in about 10 minutes. Datadog requires its APM stack.
Try Agent Status alongside Datadog
Free tier includes 30 tests/month on 1 agent from 3 regions - enough to validate the pattern against your real traffic with a 10-minute setup and no code changes to the agent itself. See pricing or jump straight to the platform overview.
