Collection Lifecycle

Not every collection needs to serve low-latency vector search all the time. Seasonal campaigns, completed projects, and long-tail archives can move to cheaper tiers — without losing the data, and without re-processing anything to bring them back.

Lifecycle states

State	Vector search	Storage	Restorable
`active` (default)	Fast, fully indexed	Hot vector index	—
`cold`	Evicted from the hot index; vectors preserved in object storage	Object-storage backup	Yes — rehydrate to `active` at any time
`archived`	Removed	Vectors permanently deleted; documents’ metadata remains	No

Allowed transitions: active → cold, active → archived, cold → active, cold → archived. Archival is permanent — the vectors are deleted, not parked.

Going cold does not delete documents or metadata — it evicts the collection’s vectors from the hot index after backing them up. Rehydrating restores search without re-running any extraction or embedding.

Check lifecycle status

curl "https://api.mixpeek.com/v1/collections/{collection_id}/lifecycle" \
  -H "Authorization: Bearer $API_KEY" \
  -H "X-Namespace: my-namespace"

Returns the current state plus counts from both the hot index and the object-storage backup, so you can verify a transition completed.

Transition a collection

curl -X PATCH "https://api.mixpeek.com/v1/collections/{collection_id}/lifecycle" \
  -H "Authorization: Bearer $API_KEY" \
  -H "X-Namespace: my-namespace" \
  -H "Content-Type: application/json" \
  -d '{"lifecycle_state": "cold"}'

cold evicts the collection from the vector store (vectors preserved via object storage).
active (from cold) rehydrates — the backup is restored into the hot index.
archived permanently removes the vectors.

archived is irreversible for vectors. If there is any chance you’ll search this collection again, use cold — restoring from cold is cheap; rebuilding from archive means re-processing the source objects.

When to use each tier

active — anything queried by production retrievers.
cold — completed campaigns and historical projects you want restorable on demand (for example, an annual review): rehydrate, query, and send back to cold.
archived — data you’re retaining for record-keeping where the documents’ metadata is enough and vector search will never be needed again.

Buckets & storage classes — tiering for the source objects (this page covers the index tier; the two are independent)
Manage data — document-level operations
Deduplication & re-processing — what happens if you do need to rebuild from source

​Lifecycle states

​Check lifecycle status

​Transition a collection

​When to use each tier

​Related

Lifecycle states

Check lifecycle status

Transition a collection

When to use each tier

Related