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

# Data Lifecycle

> Understand how data flows through Avala

Learn how data moves through the Avala platform from ingestion to archival.

## Lifecycle Stages

### 1. Ingest

Data enters Avala through:

* **Direct upload**: Web UI or API
* **Pipeline**: Automated cloud storage sync
* **Streaming**: Real-time from vehicles

### 2. Process

Automatic processing includes:

* **Validation**: Schema and format checks
* **Indexing**: Full-text search indexing
* **Thumbnails**: Preview generation for visual data
* **Metadata extraction**: Automatic tag inference

### 3. Active Storage

Data in active storage:

* Immediately accessible via API and UI
* Stored on high-performance SSDs
* Replicated across availability zones
* Included in search results

### 4. Archive

Move older data to archive storage:

* Lower storage costs
* Retrieval requires restore request
* Maintain full metadata and searchability
* Configurable retention policies

### 5. Delete

Permanent deletion:

* Removes all data and metadata
* Cannot be undone
* Required for compliance (GDPR, etc.)

## Retention Policies

Configure automatic lifecycle rules:

```yaml theme={null}
retention:
  active_days: 90
  archive_days: 365
  delete_after: 730

exceptions:
  - tag: "golden-set"
    action: keep_forever
  - tag: "temporary"
    active_days: 7
```

<Warning>
  Deletion is permanent. Ensure you have backups before enabling automatic deletion policies.
</Warning>

## Storage Tiers

| Tier           | Use Case            | Retrieval Time | Cost     |
| -------------- | ------------------- | -------------- | -------- |
| **Standard**   | Active development  | Instant        | \$\$\$\$ |
| **Infrequent** | Older recordings    | \< 1 minute    | \$\$\$   |
| **Archive**    | Long-term retention | 1-12 hours     | \$       |