> ## Documentation Index
> Fetch the complete documentation index at: https://doc.blueapi.ir/llms.txt
> Use this file to discover all available pages before exploring further.

# Storage Operations: Cleanup, Retention, and Tiering

> Artifact cleanup, retention enforcement, cold tier migration, capacity thresholds, and the automated storage lifecycle flow for model weights and experiment data.

Model weights, checkpoints, evaluation artifacts, and datasets consume terabytes of object storage. Without automated lifecycle management, costs grow and performance degrades. This page defines the storage operations that keep the artifact store efficient and within budget.

## Lifecycle Flow

```mermaid theme={null}
flowchart TD
    START([Scan Artifacts]) --> CLASSIFY[Classify by Age + State]
    CLASSIFY --> POLICY[Apply Retention Policy]
    POLICY --> ACTION{Action}
    ACTION -->|Migrate| COLD[Move to Cold Tier]
    ACTION -->|Archive| ARCH[Move to Archive Tier]
    ACTION -->|Delete| DEL[Delete with Audit Log]
    ACTION -->|Keep| KEEP[Retain in Hot Tier]
    COLD --> VERIFY[Verify Integrity]
    ARCH --> VERIFY
    DEL --> VERIFY
    KEEP --> VERIFY
    VERIFY --> UPDATE[Update Registry Metadata]
    UPDATE --> END([End])
```

## Retention Rules

| Artifact Type              | Hot Tier               | Cold Tier  | Archive    | Delete               |
| -------------------------- | ---------------------- | ---------- | ---------- | -------------------- |
| Model weights (RELEASED)   | 30 days                | 1 year     | 2 years    | After archive expiry |
| Model weights (DEPRECATED) | 7 days                 | 90 days    | 1 year     | After archive expiry |
| Merge candidates (PASS)    | 14 days                | 90 days    | 1 year     | After archive expiry |
| Merge candidates (FAIL)    | 7 days                 | 30 days    | N/A        | After cold expiry    |
| Checkpoints                | Duration of experiment | 30 days    | 90 days    | After archive expiry |
| Evaluation artifacts       | 30 days                | 90 days    | 1 year     | After archive expiry |
| Dataset copies             | Per dataset policy     | Per policy | Per policy | Per policy           |
| Logs and metrics           | 7 days                 | 30 days    | 1 year     | After archive expiry |

## Capacity Thresholds

| Threshold | Action                                                                    |
| --------- | ------------------------------------------------------------------------- |
| 70%       | Alert P4: capacity trending                                               |
| 80%       | Alert P3: trigger accelerated cleanup of FAIL candidates                  |
| 90%       | Alert P2: block new large uploads; emergency cleanup of deprecated models |
| 95%       | Alert P1: read-only mode for non-critical operations                      |

## Cleanup Procedures

### Automated Cleanup

A scheduled job scans artifacts daily. It classifies each artifact by:

* Lifecycle state (REGISTERED, CANDIDATE, EVALUATED, RELEASED, DEPRECATED, ARCHIVED)
* Last access timestamp
* Size and tiering cost

The job applies the retention table and generates a manifest of actions. The manifest is reviewed by policy: P4 and below actions are automatic; P3 and above require operator confirmation.

### Manual Cleanup

Operators may trigger emergency cleanup via API or CLI. Emergency cleanup targets:

* FAIL candidates older than 7 days
* DEPRECATED models older than 30 days
* Orphaned checkpoints with no parent experiment

All deletions are logged with artifact ID, size, reason, and operator identity. Deleted artifacts are soft-deleted for 7 days before physical removal.

## Cold Tier Migration

Migration to cold storage is asynchronous and verifies integrity before deleting the hot copy. The registry metadata is updated with the new tier location. A failed migration retries once and alerts if it fails again.

## Cross-Links

* [Backup Strategy](/operations/backup-strategy)
* [Monitoring](/operations/monitoring)
* [Alerting](/operations/alerting)