Learn how data moves through the Avala platform from ingestion to archival.Documentation Index
Fetch the complete documentation index at: https://avala.ai/docs/llms.txt
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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:Storage Tiers
| Tier | Use Case | Retrieval Time | Cost |
|---|---|---|---|
| Standard | Active development | Instant | $$$$ |
| Infrequent | Older recordings | < 1 minute | $$$ |
| Archive | Long-term retention | 1-12 hours | $ |