This page answers the common questions.

Please refer to the troubleshooting page when you encounter operation problems.


What is the ingress filter?

The ingress filter is the user-defined component that connects to the vald-filter-gateway component. For example, you can convert object data (e.g., image binary, text, etc.) to the vector using your ML models as pre-process of each request.

What is the egress filter?

The egress filter is the user-defined component that connects to the vald-filter-gateway component. You can use it for filtering search results, e.g., when you’d like to get a white T-shirt list, use it to remove other colors of T-shirts from search results that the vald-lb-gateway component returns.

We recommend using it when you’d like to operate as a cluster. It helps you to manage indexing timing for each Vald Agent.

Custom options

What are the pluggable options?

Vald has three pluggable options:

  1. Backup with the external storage for Vald Agent
    • You can connect the external storage like S3, or GCS, or etc. to Vald Agent Sidecar component for backup.
  2. Algorithm of the core engine for Vald Agent
    • We’re going to add another algorithm in near future.
  3. Filtering with filter gateway
    • you can filter the search results by own defined filter component by connecting to the filter gateway before returning the search result
    • you can convert object data to vector by own defined ingress filter component by connection to filter gateway before inserting


How to deploy the Vald cluster?

We recommend using Helm for deployment the Vald cluster. You can deploy by following steps.

  1. Install Helm(v3~) and prepare the Kubernetes cluster
  2. Configure helm chart as your demand
  3. Deploy by Helm command


Is there any support for bulk insert?

Vald provides MultiInsert and StreamInsert for bulk insert. Please refer to the insert API documentation for more detail.

Vald also provides MultiXXX and StreamXXX as bulk operation for each service. For more detail, please refer to the API document overview


Can Vald handle multi-embedding vectors?

Unfortunately, the current Vald cannot directly handle multi embedding spaces with a single Vald cluster. For handling the multi-embedding vectors in Vald, you have to do from 2 options.

  1. Deploy multiple Vald cluster
  2. Covert vector to new vector in the specific space by some methods

How to backup index data?

There are three ways for backup index data:

  1. Using external storage (S3, GCS)
  2. Using Persistent Volume
  3. Using the external storage and Persistent Volume

Please refer to the sample configurations.