Running Locally
When running locally through Docker, we recommend making at least 4 vCPU cores and 10GB of RAM available to Docker (16GB is preferred).This can be configured in the Resources section of the Docker Desktop settings menu.
Single Cloud Instance
For small- to mid-scale deployments, setting everything up on a single instance (e.g., AWS EC2, GCP Compute Engine, Azure VM) via Docker Compose is the simplest way to get started.Check out our EC2 deployment guide for a step-by-step walkthrough. We recommend the following for a single instance:
- CPU: ≥ 4 vCPU cores (≥ 8 vCPU cores recommended for larger document volumes)
- Memory: ≥ 16 GB RAM
- Disk: ≥ 50 GB + ~2.5× the size of the indexed documents
💡 Note: Vespa does not allow writes when disk usage exceeds 75%, so always allocate extra disk space.
🧹 Tip: Old/unused Docker images can consume significant space. Run docker system prune --all regularly to free space.
⚠️ Compatibility: Vespa requires Haswell (2013) or later CPUs. For older CPUs, use the vespaengine/vespa-generic-intel-x86_64 image. This version is slower but compatible.
Kubernetes / AWS ECS
For deployments where each component gets its own resources, allocate at least:| Component | CPU | Memory |
|---|---|---|
api_server | 1 | 2Gi |
background | 2 | 8Gi |
indexing_model_server | 2 | 4Gi |
inference_model_server | 2 | 4Gi |
postgres | 2 | 2Gi |
vespa | ≥4 | ≥8Gi |
nginx | 250m | 128Mi |
⚠️ Important: TheMinimum Node Size: 14 vCPU / 23GB RAMvespacomponent’s needs scale with the number of indexed documents.
For production, we recommend more than the minimum (e.g., 10 CPU, 20Gi+ RAM for 50GB of documents).
How Resource Requirements Scale
The primary factor for scaling is the size of the indexed documents. For every 1GB of raw text documents, expect:- +3GB RAM
- +0.5 CPU core
4 vCPU and 16GB RAM
📘 A “1GB document” means raw text. PDFs with images may be large in file size, but the actual text may be small.
🧠 Dimensionality of embedding models and techniques like quantization can reduce requirements.
Example: 10GB of Text Documents
Index Component Requirements:
- CPU: 4 + 10 × 0.5 = 9 cores
- Memory: 16 + 10 × 3 = 46GB
Single Instance Total Recommendation:
- CPU: ≥ 13 cores
- Memory: ≥ 50GB
🖥️ Suggested instance types:m7g.4xlarge,c5.9xlarge
Kubernetes / AWS ECS Breakdown:
| Component | CPU | Memory |
|---|---|---|
api_server | 1 | 2Gi |
background | 2 | 8Gi |
indexing_model_server | 2 | 4Gi |
inference_model_server | 2 | 4Gi |
postgres | 2 | 4Gi |
vespa | 10 | 34Gi |