The below compute requirements should be sufficient for deploying OmniAI vis Docker container. Recommended configuration may vary based on total data throughput:

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Compute Requirements (For API + Workers + Frontend)

Recommended: t3.large or t3.xlarge, offering 2–4 vCPUs and 8–16 GiB of memory. This setup is sufficient to support a Node.js API, a few background workers, and a lightweight frontend without overprovisioning resources.

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Database

Use a mid-tier Amazon RDS PostgreSQL instance (e.g., db.m6g.large or db.m5.large), which offers a good balance of performance and cost for moderate query volumes and storage needs.

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GPU Requirements (For Document Processing)

Use a single g5.12xlarge instance (approx. $5.672/hr on-demand). This configuration is capable of processing approximately 1 million pages per month, making it suitable for high-throughput document extraction workloads.

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Storage

EBS-optimized instances with Provisioned IOPS SSD (io1 or io2) volumes are recommended. For most deployments, starting with at least 500GB of storage with 3,000 IOPS is advisable, allowing for high-performance read/write operations and accommodating the storage demands of our Docker images and data.

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Networking

Choose instances with at least 10 Gigabit connectivity to ensure high throughput and low latency, particularly crucial for maintaining performance and responsiveness in network-intensive operations.