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Resourcing Overview

Vespa (the vector database used by Gorbit) does not allow writes once disk usage hits 75%.

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Local Deployment (Docker)

You can control the resources available to Docker in the Resources section of the Docker Desktop settings menu.
Often old, unused Docker images take up sizeable disk space. To clean up unused images, run docker system prune --all.

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Cloud Providers (AWS, GCP, etc.)

For small to mid scale deployments, we recommend deploying Gorbit to a single instance in your cloud provider of choice. When evaluating your instance, follow the Preferred resources in the table above.
Vespa requires Haswell (2013) or later CPUs.For older CPUs, use the vespaengine/vespa-generic-intel-x86_64 image in your Docker Compose file. This generic image is slower.For more details, see Vespa CPU Support.

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Container-Specific Resourcing

For more efficient scaling, you can dedicate resources to each Gorbit container using Kubernetes or AWS EKS. See the Gorbit Helm chart values.yaml for our default requests and limits.
The vespa recommendation is the minimum for a production deployment. With 50GB of documents, we recommend at least 10 CPU, 20Gi Memory.
All together, this comes out to a total available node size of at least ~14 CPU and ~30GB of Memory.

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How Resource Requirements Scale

The main driver of resource requirements is the number of indexed documents. This primarily affects the index component of Gorbit (a Vespa vector database), which is responsible for storing the vectorized documents and handling search requests.
Vespa’s resource requirements scale linearly with the document count.
Based on our experience with large scale deployments, in addition to the previously mentioned minimums, Vespa needs:
  • ~3GB of memory for each additional 1GB of documents
  • ~1 CPU for each additional 2GB of documents
These are our rough estimates. Other factors that may affect resource requirements include:
  • The embedding model
  • Whether you have quantization and dimensional reduction enabled

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Resourcing Example

For a deployment with 10GB of text content, your index component will need:
  • CPU: 4 + 10 * 0.5 = 9 cores
  • Memory: 4 + 10 * 3 = 34GB
If deploying in a single instance, this would be in addition to the base requirements. Overall, that would take us to
= 13 CPU and >= 50GB of memory.
Given these requirements, a m7g.4xlarge or a c5.9xlarge EC2 instance would be appropriate. If deploying with Kubernetes or AWS EKS, this would give a per-component resource allocation of: Total available node size: ~20 CPU and ~60GB of Memory.

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Next Steps

Guide: Deploy Gorbit Locally

Deploy Gorbit locally with Docker.

Guide: Deploy on AWS

Deploy Gorbit on an EC2 instance.