AI Mini Datacenter Proposal

AI Mini Datacenter Proposal
Prepared for: ABC Company  |  Prepared by: 365 Admin Support and Services
Infrastructure Proposal
Confidential
Talluri Naveen Kumar
Datacenter Solution Provider
📞 +91 9848001400
✉ naveen@365adminsupport.com
365 Admin Support and Services
Hyderabad-based IT Infrastructure & Networking Solutions Provider — designing, deploying, and managing enterprise-grade datacenter environments.
About 365 Admin Support and Services
365 Admin Support and Services is a full-spectrum IT infrastructure and networking solutions provider headquartered in Hyderabad. We specialize in building enterprise-grade datacenter environments tailored to the evolving needs of modern AI-driven organizations.
Datacenter Design
End-to-end design and implementation of scalable datacenter infrastructure
Network Deployment
Enterprise networking, structured cabling, and rack deployment
Server Virtualization
Cloud infrastructure, VM hosting, and hypervisor management
IT Security
Enterprise firewall deployment, IPS, and network segmentation
DC Monitoring
Real-time performance monitoring, alerting, and operational management
Project Objective
Strategic Vision
The objective of this engagement is to establish a Mini AI Datacenter for ABC Company — a purpose-built, high-performance computing environment capable of running GPU-accelerated AI and machine learning workloads at enterprise scale. This facility will serve as the technological backbone for ABC Company's AI initiatives.
🖥️ GPU Computing
High-performance NVIDIA GPU servers optimized for AI model training and inference
🔗 Redundant Connectivity
Multi-ISP internet with BGP routing for uninterrupted uptime
🔒 Secure Infrastructure
Enterprise-grade firewall, IPS, and segmented network zones
📈 Scalable Design
Architecture designed to grow with future compute and capacity demands
Scope of Implementation
The project encompasses a comprehensive, end-to-end build-out of ABC Company's AI datacenter infrastructure — from physical rack deployment to logical network configuration and security hardening. Every layer of the stack is addressed to ensure a production-ready environment from day one.
01
Datacenter Infrastructure Setup
Physical rack, cabling, power, and cooling installation
02
GPU Server Deployment
5-unit high-performance GPU server rack mounting and OS configuration
03
Network & Connectivity
BGP router, core switch, multi-ISP failover, and firewall configuration
04
Security & Monitoring
Intrusion prevention, CCTV, access control, and real-time monitoring platform
05
Backup & Disaster Recovery
On-site and remote backup servers with automated scheduling and DR planning
AI Datacenter Overview
The proposed AI datacenter is engineered as a high-density GPU compute facility — a purpose-designed environment that goes far beyond conventional IT infrastructure. It provides the raw computational power needed for modern AI workloads, delivered with enterprise-level reliability and security.
Machine Learning
Distributed ML training pipelines with GPU-accelerated frameworks such as TensorFlow and PyTorch
AI Model Training
Large language model (LLM) and deep learning model training on dedicated GPU clusters
GPU Compute Services
On-demand GPU compute provisioning for internal teams and application workloads
VM Hosting
Virtualized server instances for application hosting, dev/test, and staging environments
Chapter 1
Hardware Infrastructure
The initial deployment is designed to establish a robust, production-ready hardware foundation. Five high-performance GPU servers form the core compute layer, supported by enterprise networking and redundant power systems — all mounted within a professional 42U rack environment.
5
GPU Servers
High-performance NVIDIA GPU compute nodes
42U
Rack Form Factor
Enterprise rack-mounted datacenter layout
10Gb
Network Speed
Core switching fabric for inter-server communication
2N
Power Redundancy
Dual redundant power supply chains with UPS backup
GPU Server Configuration
Each GPU server is configured to deliver maximum AI compute performance, combining AMD EPYC or Intel Xeon processors with NVIDIA's most capable GPU hardware. This configuration is validated for enterprise AI workloads including deep learning, simulation, and large-scale data processing.
Compute Specification (Per Node)
CPU: AMD EPYC / Intel Xeon (multi-core, high-frequency)
RAM: 128 GB – 256 GB DDR5 ECC Registered
GPU: NVIDIA RTX 4090 / Enterprise-class GPU
Storage: NVMe SSD (OS + fast scratch) + Enterprise HDD (bulk data)
Network: Dual-port 10Gb Ethernet NIC
Why This Configuration?
The selected hardware profile strikes the ideal balance between raw AI compute throughput and infrastructure reliability. NVMe SSD storage eliminates I/O bottlenecks for data-intensive training runs, while ECC RAM ensures memory integrity across extended workloads. The dual-GPU-capable motherboard platform also allows future GPU upgrades without server replacement.
Chapter 2
Networking Architecture
The datacenter network is built on a resilient, high-throughput architecture designed to ensure zero single points of failure. Every layer — from the core switch to the internet edge — is engineered for performance, security, and maximum availability.
The architecture follows a classic spine-leaf design principle adapted for a GPU compute environment — ensuring east-west traffic between servers remains low-latency while north-south internet traffic is optimally load-balanced across multiple ISPs.
Multi-ISP Connectivity Strategy
Relying on a single internet service provider introduces unacceptable risk for a production AI datacenter. ABC Company's facility will connect to three independent ISPs simultaneously, ensuring that no single provider failure can disrupt operations.
ISP 1 — Primary
High-bandwidth primary internet link. Carries the majority of outbound and inbound traffic under normal operating conditions.
ISP 2 — Secondary
Active secondary link used for load balancing and failover. Automatically assumes traffic load if ISP 1 degrades.
ISP 3 — Backup
Tertiary backup provider. Acts as the final safety net during simultaneous primary and secondary failures.
BGP Routing Architecture
What is BGP and Why It Matters
Border Gateway Protocol (BGP) is the routing protocol that powers the global internet. By deploying BGP at the datacenter edge, ABC Company gains full control over how internet traffic enters and exits the facility — enabling intelligent, automatic failover between ISPs and optimal path selection for every connection.
IP Prefix Advertisement
ABC Company's public /23 IP block is announced to all three ISPs simultaneously via BGP
Automatic Failover
BGP detects ISP link failures in real time and reroutes all traffic within seconds — with no manual intervention required
Traffic Engineering
BGP policies can be tuned to prefer certain paths, balance load, or prioritize latency-sensitive AI API traffic
Public IP Infrastructure
A /23 IPv4 address block (512 usable addresses) has been identified as the appropriate allocation to support the full scope of ABC Company's AI datacenter operations — from GPU servers and AI services to customer virtual machines and future expansion capacity.
50
GPU Servers
Dedicated IPs for compute nodes and out-of-band management
80
AI Services
Application and API service endpoints for AI platform workloads
150
Virtual Machines
Customer-facing VM instances and hosted application environments
20
Network Infra
Switches, routers, firewalls, and management interfaces
10
Load Balancers
Security appliances and application delivery controllers
200
Future Expansion
Reserved capacity for planned growth and new service rollouts
Total: ~510 IPs required — a /23 IPv4 block (512 addresses) from IRINN/NIXI is the appropriate and justified allocation.
Chapter 3
Power Infrastructure
Continuous Power — Zero Compromise
GPU servers draw significant sustained power loads. A single power interruption — even for milliseconds — can corrupt active AI training runs, resulting in hours or days of lost compute work. ABC Company's power infrastructure is designed with multiple redundancy layers to eliminate this risk entirely.
Online UPS System
Double-conversion online UPS provides clean, conditioned power with zero transfer time during outages
Battery Backup
Extended battery bank sustains full server load during short-duration outages and generator startup
Rack PDUs
Intelligent power distribution units with per-outlet monitoring and remote switching
Generator Backup
Diesel generator provides sustained power for extended grid outages
Cooling Infrastructure
NVIDIA GPU servers operating at full compute load generate extreme thermal output — up to 350–450W per GPU unit. Without purpose-designed cooling, thermal throttling will degrade performance and dramatically reduce hardware lifespan. ABC Company's cooling design uses a hot aisle containment strategy to manage heat efficiently and precisely.
Precision Cooling Units
Computer room air conditioners (CRAC) with precision temperature control rated for high-density GPU loads
Hot Aisle Containment
Hot aisle / cold aisle design separates hot exhaust from cool supply air — dramatically improving cooling efficiency
Temperature Monitoring
Continuous environmental sensors at rack-level with automated alerts when thresholds are exceeded
Storage Architecture
Tiered Storage for Maximum Performance
AI workloads have highly varied storage demands. Model training requires fast random-access storage for datasets, while long-term archives and backups benefit from high-capacity, cost-efficient media. The proposed tiered storage architecture serves both needs without compromise.
1
2
3
1
Network Storage — Backup Tier
High-capacity network-attached storage for scheduled backups and archival data
2
RAID Storage — Capacity Tier
Enterprise RAID arrays with redundancy for persistent VM and application data
3
NVMe SSD — Performance Tier
Ultra-low latency NVMe for active AI training datasets and model checkpointing
Data Backup Strategy
Data loss in an AI datacenter can mean the loss of weeks of compute work, trained models, and critical business data. ABC Company's backup strategy follows the industry-standard 3-2-1 rule — three copies of data, on two different media types, with one copy stored off-site — ensuring full recoverability in any failure scenario.
1
Continuous Snapshot
Application-consistent snapshots taken at frequent intervals for near-zero recovery point objectives
2
On-Site Backup
Dedicated on-premise backup server for fast local restoration of VMs and critical datasets
3
Off-Site / Remote Backup
Encrypted replication to a geographically separate remote backup location
4
Disaster Recovery
Documented DR runbooks with tested recovery procedures and defined RTO/RPO targets
Chapter 4
Security Architecture
A datacenter that hosts AI workloads, customer virtual machines, and public IP infrastructure is a high-value target. ABC Company's security design implements a defense-in-depth strategy — multiple overlapping security layers that ensure no single breach can compromise the entire environment.
Enterprise Firewall
Sophos or equivalent next-generation firewall with deep packet inspection and application-layer filtering
IPS / IDS
Intrusion Prevention System with real-time threat signature updates and behavioral anomaly detection
Network Segmentation
VLANs and access control lists (ACLs) isolate GPU compute, management, and customer VM traffic
Restricted Port Access
Only whitelisted ports and protocols are permitted — all others are denied by default policy
Monitoring & Alerting System
Real-Time Operational Visibility
Maintaining a healthy AI datacenter requires constant, granular visibility across every infrastructure layer. The proposed monitoring platform aggregates performance data from all hardware and network components, delivering real-time dashboards and automated alerts — so issues are detected and resolved before they impact workloads.
Server Performance
CPU, GPU utilization, memory usage, and disk I/O tracking per node
Network Uptime
ISP link status, BGP session health, and bandwidth utilization dashboards
Environmental Sensors
Temperature and power usage effectiveness (PUE) monitoring with threshold alerts
Instant Alerts
Automated SMS and email alerts dispatched to operations team in real time
Disaster Recovery Planning
A comprehensive Disaster Recovery (DR) plan ensures ABC Company's AI datacenter can withstand and recover from both physical and cyber threats. The DR framework defines clear recovery time objectives (RTOs) and recovery point objectives (RPOs) for every critical system, with tested runbooks for each scenario.
Scalability Roadmap
One of the core design principles of ABC Company's AI datacenter is future-proof scalability. The initial five-server deployment is intentionally designed as Phase 1 of a multi-phase growth roadmap — ensuring that expansion never requires a rip-and-replace of existing infrastructure.
Phase 1 — Foundation (Current)
5 GPU servers, /23 IP block, multi-ISP BGP, core switching, security, and monitoring deployed
Phase 2 — Compute Expansion
Additional GPU server nodes added to existing rack infrastructure; IP pool scaled within existing /23 block
Phase 3 — Service Expansion
AI-as-a-Service APIs, managed VM hosting, and GPU rental services offered to external clients
Phase 4 — Hybrid Cloud
Cloud burst capacity via AWS, Azure, or Google Cloud integrated with on-premise GPU cluster for overflow workloads
Chapter 5
Network Architecture Diagram
The following diagram illustrates the complete logical network topology of the AI GPU Datacenter — from internet ingress through the BGP routing layer, firewall cluster, core switching fabric, and down to the GPU compute and storage networks.
All internet-facing traffic passes through the BGP edge router and firewall cluster before reaching the internal server network — ensuring that the GPU compute environment is never directly exposed to the public internet.
IRINN IP Justification
IRINN / NIXI
/23 IPv4 Request
Subject: Request for IPv4 Allocation (/23) for AI Datacenter Infrastructure
365 Admin Support and Services formally requests a /23 IPv4 address block from IRINN/NIXI for the purpose of operating an AI and GPU compute datacenter serving ABC Company. The infrastructure will operate with multi-ISP BGP routing to ensure high availability and redundant connectivity at all times.
1
GPU Compute Servers
50 IPs — Compute node management, IPMI, and primary network interfaces
2
AI Application Services
80 IPs — AI model inference APIs, training orchestration endpoints
3
Customer Virtual Machines
150 IPs — Tenant VM instances and hosted application services
4
Network Infrastructure
20 IPs — Routers, switches, firewalls, and management interfaces
5
Load Balancers & Security
10 IPs — Application delivery controllers and security appliances
6
Future Expansion Reserve
200 IPs — Reserved for Phase 2/3 growth and new service rollouts
Total Justified Requirement: ~510 IPs → /23 IPv4 Block (512 addresses). We respectfully request IRINN to review and approve this allocation to support the deployment of ABC Company's AI datacenter infrastructure.
Chapter 6
Project Cost Estimate
The following investment breakdown covers all hardware, infrastructure, networking, power, cooling, and security components required for the complete Phase 1 AI Mini Datacenter deployment. All figures are indicative and subject to final vendor quotations.
GPU servers represent the dominant cost at ₹60,00,000 — reflecting the premium nature of AI-grade NVIDIA hardware. All remaining infrastructure components total ₹11,80,000, making the complete datacenter investment highly efficient relative to cloud GPU costs at equivalent compute capacity.
Detailed Cost Breakdown
Total Investment Summary
Project Investment
₹71.8L
Total Project Cost
Complete Phase 1 datacenter deployment
This investment delivers a fully production-ready AI datacenter with enterprise-grade reliability, security, and scalability — positioned to support ABC Company's AI ambitions for 5+ years.
Investment vs. Cloud GPU Equivalent
Five NVIDIA GPU nodes on a public cloud platform (e.g., AWS p4d instances) would cost approximately ₹2,50,000–₹3,50,000 per month in rental fees alone — meaning the on-premise investment pays for itself in under 24–30 months, while delivering greater data security, lower latency, and no egress bandwidth costs.
₹60,00,000
GPU Hardware
₹11,80,000
Infrastructure
Conclusion & Recommendation
The AI Mini Datacenter proposed for ABC Company represents a strategically sound, technically robust, and commercially viable investment in next-generation AI compute infrastructure. Built on proven enterprise hardware, redundant networking, and a defense-in-depth security model, this facility will empower ABC Company to run AI workloads with confidence, control, and cost efficiency.
🚀 High Performance
NVIDIA GPU clusters delivering enterprise AI compute on demand — owned, not rented
🔒 Secure & Reliable
Multi-layer security, redundant power, cooling, and multi-ISP connectivity for maximum uptime
📈 Future-Ready
Scalable architecture designed to grow from 5 servers today to a full AI cloud platform tomorrow
We recommend proceeding with Phase 1 deployment at the earliest opportunity. 365 Admin Support and Services is ready to begin detailed engineering design, vendor procurement, and project scheduling upon approval.
Next Steps
365 Admin Support and Services is fully prepared to begin execution immediately upon ABC Company's approval. The following action plan outlines the immediate next steps to initiate the project.
1
Proposal Approval
ABC Company executive team reviews and approves this proposal and the associated investment budget
2
Site Assessment
365 Admin Support conducts a physical site survey of the proposed datacenter location at ABC Company premises
3
Vendor Finalization
Hardware and infrastructure vendors are shortlisted and final purchase orders are placed
4
IRINN IP Application
Formal /23 IPv4 allocation request submitted to IRINN/NIXI with full justification documentation
5
Project Kickoff
Full project team mobilized — installation, configuration, testing, and handover commences
Thank You
We appreciate the opportunity to present this proposal to ABC Company's leadership team. 365 Admin Support and Services is committed to delivering a world-class AI datacenter infrastructure that meets your technical requirements, budget expectations, and long-term strategic vision.
Contact Us
Talluri Naveen Kumar
Datacenter Solution Provider
365 Admin Support and Services
📞 +91 9848001400
✉ naveen@365adminsupport.com
365 Admin Support and Services
Hyderabad, India
Specializing in enterprise datacenter design, GPU infrastructure, network architecture, and IT security — delivering solutions that power the AI era.
AI Infrastructure
Datacenter Design
Network Architecture