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This document outlines the pre-deployment prerequisites, verification steps, and considerations required for the successful On-Premise installation and deployment of the Odin AI Platform product. It is intended to serve as a comprehensive checklist to ensure that the client’s environment is properly configured and meets all necessary requirements before proceeding with the deployment.

Prerequisites

Access Requirements

  • Server Access:
    • Confirm access to deployment servers with sudo privileges.
    • Verify that all necessary network routes are established via a secure VPN or dedicated network configuration.
  • User Permissions:
    • Ensure that the deployment team has been granted the necessary access rights.
    • Validate that any required two-factor authentication (2FA) or security tokens are in place.

System Requirements

Operating System:      
           Ubuntu 22 or RHEL 8.10
Hardware Specifications:     
      For each deployment tier, ensure that the hardware meets or exceeds the following:
  • GPU (Required when deploying an LLM on the same machine as the Odin AI Platform platform.)
  • SMALL: ~500 (100 Concurrent) users can be supported by a single VM 16 cores, 64gb ram, 1 TB
    • SSD these machines cost ~$600 per month. This is a minimum size deployment.
  • MEDIUM ~ 2000 (500 Concurrent)  users can be supported by a larger machine 32 cores, 128gb ram, 2 TB
    • SSD these machines are around ~$1,200 per month
  • LARGE: ~10000 (1000+ Concurrent)  users should be deployed across containers so that the infrastructure
    • can scale to support the needs, this typically costs a minimum of $2,000 per month it is
    • suggested to calculate $2,000 per month per additional 1,000 Active Users. This is a fully
distributed deployment.

Deployment Tools & Software Dependencies

  • Deployment Scripts:
    • Verified and version-controlled Bash deployment scripts.
  • Dependency Management Tools:
    • Python 3
    • Git (current version)
    • Docker (v27.1.1) or Podman
  • Additional Tools (Optional):
    • Logging and monitoring tools (e.g., ELK Stack, Prometheus, Grafana) as per the client’s monitoring requirements.

Credentials and Keys

  • Server Credentials:
    • Ensure that all server access credentials are up to date and securely stored.
  • Application API Keys and Licenses:
    • Verify that all application-specific API keys and licenses (e.g., OpenAI, SERP, Sentry) are available and valid.

Pre-Deployment Checklist

Hardware and System Verification

Ensure that the client’s hardware and system configurations match the specifications:

3.2 Software and Dependency Verification

Verify that all necessary software components are installed and correctly versioned:

3.3 Network and Connectivity Check

Ensure the network is correctly configured and that there is adequate internet connectivity for external dependencies or updates:

3.4 Additional Verifications

Services and ports Protocol support
Notes: All internal machines must be able to communicate freely with each other. We recommend using SSL (HTTPS) connections; HTTP is supported during PoCs.
Firewall and Security Settings: Validate that firewall rules or security groups allow for required traffic.

General Architecture

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Architecture Diagram – On-Premise

Deployment architecture flow for single virtual machine box with mentioned prerequisite resource allocation general-arc.png

Deployment architecture flow for AWS Cloud deployment

general-arc.png general-arc.png