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 Optimized Instances (For CPU-bound applications)

  • Minimum: c5.xlarge, offering 4 vCPUs and 8 GiB of memory, sufficient for basic operations.
  • Recommended: c5.2xlarge, providing 8 vCPUs and 16 GiB of memory, suitable for enhanced parallel processing and increased efficiency in handling larger workloads.

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Memory Optimized Instances (For applications requiring high memory)

  • Minimum: r5.xlarge, equipped with 4 vCPUs and 32 GiB of memory, ideal for applications needing substantial memory but not excessive compute power.
  • Recommended: r5.2xlarge equipped with 8 vCPUs and 64 GiB of memory, which provides a robust platform for handling moderate to large datasets efficiently.

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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.