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Batch evaluation - Amazon Bedrock AgentCore

Batch evaluation

Batch evaluation runs evaluators against multiple agent sessions in a single job with server-side orchestration. Unlike on-demand evaluation where you collect spans and call the Evaluate API yourself, batch evaluation handles session discovery, span collection, and scoring entirely on the service side. You submit a job, and the service processes all matching sessions and returns aggregate results.

Use batch evaluation when you need to:

  • Measure a baseline before making changes to your agent’s prompt, tools, or model.

  • Validate improvements by comparing scores before and after a configuration change.

  • Run regression tests across a curated set of sessions or scenarios.

  • Monitor quality periodically across production sessions from a specific time window.

How it works

A batch evaluation job follows this flow:

  1. You start a job by specifying a session source (where to find agent sessions) and an evaluation configuration (which evaluators to run). Optionally, you provide ground truth metadata for reference-based scoring.

  2. The service discovers sessions from CloudWatch Logs based on the log groups and filters you specify.

  3. The service runs evaluators against each discovered session. Each evaluator scores each session independently. If ground truth is provided, evaluators that support reference-based scoring use it.

  4. You poll for results. The job transitions through PENDING → IN_PROGRESS → COMPLETED (or FAILED). When complete, the response includes aggregate summaries with per-evaluator average scores, session counts, and token usage.

  5. Per-session detail is available in CloudWatch Logs at the location specified in outputDataConfig in the response.

Comparison with other evaluation types

Aspect On-demand Online Batch

Trigger

Caller-initiated, synchronous

Continuous, event-driven

Caller-initiated, asynchronous

Session source

Caller provides spans inline

Watches a log group

Service discovers from CloudWatch Logs

Scope

Single session

All sessions matching sampling rules

Multiple sessions (time range, session IDs, or full log group)

Ground truth

Via evaluationReferenceInputs

Not supported

Via sessionMetadata with inline ground truth

Results

Synchronous response

CloudWatch metrics and dashboards

Aggregate summaries with per-evaluator averages, plus per-session detail in CloudWatch

Use case

Dev-time spot checks, CI/CD

Production monitoring

Baseline measurement, pre/post comparison, regression testing
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