Agent Release Control Plane
A release workspace compares prompt, model, retrieval, and tool versions against governed evaluation datasets. Automated scoring and human review create an explicit gate before production promotion.
Agent Release Control Plane system boundary
A version registry binds prompts, models, retrieval settings, and tool contracts into a candidate. Evaluation workers run governed datasets, scoring services compare results and thresholds, and a reviewer controls promotion or rollback.
Agent Release Control Plane execution path
An engineer registers a candidate, queued workers execute regression suites, deterministic scorers and review queues collect evidence, failure clustering highlights changes, and the release reviewer approves, rejects, or returns the candidate.
Agent Release Control Plane context movement
Dataset versions, candidate configuration, trace spans, outputs, scores, latency, and cost observations remain linked by a release identifier. Production data is excluded unless its use and retention are explicitly authorized.
Agent Release Control Plane ownership limits
The candidate agent can perform only evaluation-scoped actions. It cannot promote itself, change thresholds, rewrite datasets, or access production credentials.
Agent Release Control Plane enforced controls
Version immutability, dataset checksums, deterministic scorers, cost and latency thresholds, credential separation, release approvals, rollback pointers, and evidence retention remain outside the agent.
Agent Release Control Plane trust boundaries
Authorized or synthetic test data, trace redaction, role-based release permissions, isolated evaluation credentials, and controlled retention protect the evaluation plane.
Agent Release Control Plane operating model
Evaluation jobs use queues, partitioned datasets, concurrency limits, cached fixtures, and provider rate limits. Partial suites can retry without losing the full release record.
Agent Release Control Plane recovery paths
Provider outages pause affected jobs, incomplete traces are marked invalid, scorer failures are rerun independently, threshold failures block promotion, and rollback restores the last approved version.
Agent Release Control Plane deterministic test coverage
Tests cover dataset integrity, version binding, scoring determinism, threshold enforcement, permissions, worker retries, release rejection, and rollback selection.
Agent Release Control Plane behavior evaluation
Suites assess task completion, grounding, retrieval, tool selection, authorization, escalation, latency, cost, and known regressions. Human review handles criteria that cannot be reduced to deterministic scoring.
Agent Release Control Plane operational evidence
Dashboards connect candidate versions to runs, traces, scores, failure clusters, queue state, provider errors, and release decisions.
Agent Release Control Plane deployment boundaries
Evaluation workers remain isolated from production. Approved version manifests move through staged environments while the control plane preserves audit evidence and rollback references.
Agent Release Control Plane deliberate constraints
Broader suites increase evidence and cost. The design prioritizes representative risk coverage and explicit release ownership rather than treating one aggregate score as proof of reliability.
Agent Release Control Plane claim boundary
Illustrative AgentOps architecture only. No accuracy, reliability, latency, cost, or adoption metric is claimed.
Need this architecture adapted to your workflow?
DeepVention Labs can map the requirements, boundaries, integrations, evaluation, and operating model for your system.