aquilia-mlops-model-lifecycle - SKILL.md Agent Skill

name: aquilia-mlops-model-lifecycle description: "Build Aquilia MLOps model packaging, registry, serving, rollout, observability, plugins, lineage, experiments, export, and admin workflows. Use for aquilia.mlops APIs and aq pack/model/mlops-deploy/observe/export/plugin/lineage/experiment commands."

Aquilia Mlops Model Lifecycle

Purpose

Use Aquilia's implemented MLOps stack for model packaging, registry, runtime serving, deployment rollout, observability, plugins, lineage, and experiments.

Trigger Conditions

Use for modelpack archives, registry push/inspect/verify, serving models, ONNX/edge export, drift detection, metrics, rollout plans, plugin management, lineage queries, and A/B experiments.

Inputs

Model path, name, version, framework/runtime, env lock, signing key, registry URL, rollout versions, drift data, plugin package, or experiment arms.

Execution Flow

Use CLI groups from mlops_cmds.py: pack, model, mlops-deploy, observe, export, plugin, lineage, and experiment.
Use MLOpsManifest, runtime/base classes, registry service/storage, orchestrator, scheduler, and observe modules where programmatic integration is needed.
Configure workspace with Integration.mlops(...) or Workspace.mlops(...) when app-level MLOps is required.
Use blueprint APIs for request/response schemas when exposing MLOps endpoints.
Verify archives and signatures before deployment or registry push.

Constraints

Optional dependencies are split by extras: core mlops, onnx, torch, s3, bento, explain.
Do not fake support for a runtime if select_runtime or exporter code does not implement it.
Signing and registry credentials must not be committed.

Implementation Anchors

aquilia/mlops/, aquilia/cli/commands/mlops_cmds.py, aquilia/integrations/mlops.py, aquilia/admin/templates/mlops.html, tests/test_mlops_*.py, examples/mlops_model_registry_app/.

Examples

aq pack save model.pkl --name recommender --version 1.0.0 --framework sklearn.
aq model serve modelpack.aq --runtime python --port 9000.
aq mlops-deploy rollout fraud --from-version 1.0 --to-version 1.1 --strategy canary.

Failure Handling

Pack integrity/signature failures should stop deployment. Missing optional ML dependencies should produce actionable install guidance. Drift/metrics failures should map to MLOps observe faults.