Top 9 AgentOps Alternatives 2026

What is Datadog Agent Observability?

Datadog Agent Observability traces every step of an agent in production with span-level inputs, outputs and metadata across prompts, retrieval, the actions the agent takes and the decisions it makes, then correlates that with the backend services, infrastructure and real user sessions already ...

What is OpenLIT?

OpenLIT is an open-source platform for watching the whole harness an agent runs inside: the agent framework, the models it calls, the MCP servers it reaches, the vector databases it reads and the GPUs underneath. Everything is emitted as OpenTelemetry, so the same traces can be read in OpenLIT ...

What is Pydantic Logfire?

Pydantic Logfire records agent runs as OpenTelemetry spans and keeps them beside the traces from the rest of the application, so an agent step and the database query it triggered sit in the same timeline. It reads instrumentation from 26 or more agent frameworks, and because the query language ...

What is Scorecard?

Scorecard runs an agent through large numbers of realistic scenarios and returns scores in minutes, so a prompt, model or logic change is judged on measured results rather than a few manual checks. Test sets are managed in the platform and prompts can be edited and compared in a playground, ...

What is Coval?

Coval puts a voice agent through simulated calls before real callers reach it, then keeps scoring the calls it takes in production. Agents built on Vapi, Retell, ElevenLabs and other platforms connect over SIP or an API, and the behaviours you care about are defined as metrics applied per call. ...

What is Okareo?

Okareo tests voice, text and headless agents by driving simulated users at them and grading what the agent did. Voice agents are exercised the way a real call arrives, with a set of simulation drivers per run, and the trace and the transcript are shown together so a bad turn can be traced to ...

What is Laminar?

Laminar is an Apache 2.0 agent observability platform that records every run and then groups the failures it finds across all of them. Laminar Signals reads each run, extracts the task the agent was given, and reports the distribution of behaviours and failure modes rather than one trace at a ...

What is Future AGI?

Future AGI runs agents against realistic multi-turn conversations, edge cases and adversarial inputs at volume, then scores what each run did. The interface is built around the agent graph: nodes for each step, the path a run actually took, pass and fail counts per flow, and latency measured at ...

What is Judgment Labs?

Judgment is built for agents whose runs are long rather than short, where a single task can span hundreds of steps and the stored trace runs to a very large amount of text. Storage and indexing are shaped around that, so a billion tokens of agent data stay searchable. Background agents read the ...