Databases
Managed Qdrant on your own cluster
Vector database for embeddings: similarity search, recommendations and retrieval for AI apps, over HTTP and gRPC.
Created inside a project, beside the apps that use it. Each project gets its own instance, storage and credentials.
01What it does
Qdrant, run for you
Qdrant on the vendor's own chart.
Somewhere for embeddings to live: similarity search, recommendations and retrieval for the AI features your app is growing. Qdrant speaks HTTP and gRPC, and bound apps receive both ports beside an API key generated for them.
Vectors are held in memory, so the size is what decides how large a collection stays fast. The disk for collections and snapshots is chosen once. The HTTP API can be published on a hostname, and the gRPC port can be opened on a public cluster.
02Options
What you choose
What the console asks when you create it, in the catalog's own numbers. Anything marked chosen once cannot change without creating a new instance.
- Sizes
- small 1Gi, medium 4Gi, large 8Gi of memory
- Storage
- 10Gi by default, chosen once
- Hostname
- The HTTP API (6333) can be published on a domain
- Public port
- gRPC (6334) can be opened on a public cluster
- Pause
- Yes; the volume is kept
03Binding
What your app receives
Bind it to an app and these arrive as environment variables. The values are generated once into a secret and reach the app from there, rather than as something you copy.
- QDRANT_HOST
- QDRANT_PORT
- QDRANT_GRPC_PORT
- QDRANT_API_KEY
- QDRANT_URL
04Adding it
Add Qdrant to a project
The same four steps as every service in the catalog.
- 01Open a project and go to Services.
- 02Pick it from the catalog and choose its options. Only the size is required; everything else has a default.
- 03Create it. Anyport installs it into the project's namespace, generates its credentials into a secret there, and tracks its health.
- 04Bind it to an app. The connection details arrive as environment variables, and rotating the credential never means editing an app.