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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.

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:
retention:
  active_days: 90
  archive_days: 365
  delete_after: 730

exceptions:
  - tag: "golden-set"
    action: keep_forever
  - tag: "temporary"
    active_days: 7
Deletion is permanent. Ensure you have backups before enabling automatic deletion policies.

Storage Tiers

TierUse CaseRetrieval TimeCost
StandardActive developmentInstant$$$$
InfrequentOlder recordings< 1 minute$$$
ArchiveLong-term retention1-12 hours$