Network & Infrastructure

Our robust network design and infrastructure implementation ensures high-performance, reliable, and secure connectivity for AI hosting environments.

Back to Playbook

Network & Infrastructure Overview

The ComputeComplete Network & Infrastructure framework provides a comprehensive approach to designing, implementing, and managing high-performance network infrastructure specifically optimized for AI workloads. Our methodology ensures that converted mining facilities meet or exceed the connectivity, reliability, and security requirements of enterprise AI customers.

Network Design Principles

  • High Performance: Network infrastructure designed to deliver maximum throughput and minimal latency for demanding AI workloads.
  • Redundancy: Multiple paths and components throughout the network to eliminate single points of failure and ensure continuous operation.
  • Scalability: Modular design that allows for seamless expansion as capacity requirements grow without disrupting existing operations.
  • Security: Comprehensive security controls integrated at all layers of the network to protect against unauthorized access and attacks.
  • Manageability: Centralized monitoring and management systems that provide visibility and control across the entire network infrastructure.

Core Infrastructure Components

Dual-Fiber Entry

Physically diverse fiber entry points to ensure continuous connectivity even in the event of a fiber cut or carrier outage.

Key Features:
  • Geographically diverse entry points
  • Separate conduit paths to property line
  • Redundant carrier handoff rooms
  • Automated path failover
  • 24/7 monitoring and alerting

Redundant Meet-Me Rooms

Separate physical spaces for carrier equipment and cross-connects to ensure isolation and redundancy.

Key Features:
  • Physically separated rooms with independent systems
  • Redundant power and cooling
  • Diverse cable pathways to data halls
  • Carrier-neutral connectivity options
  • Comprehensive fire suppression systems

Secure VLAN Segmentation

Logical network segmentation to isolate customer environments and control traffic flow between network segments.

Key Features:
  • IEEE 802.1Q VLAN implementation
  • Private VLANs for customer isolation
  • Micro-segmentation capabilities
  • Traffic filtering between segments
  • Automated VLAN provisioning

VPN Remote Management

Secure remote access infrastructure for management and monitoring of network and systems.

Key Features:
  • Site-to-site and client VPN options
  • Multi-factor authentication
  • Encrypted tunnels with perfect forward secrecy
  • Granular access controls
  • Comprehensive connection logging

Network Architecture Diagram

Network Architecture Diagram Would Be Displayed Here

Key Components:

  • Dual Fiber Entry Points: Physically diverse paths for carrier connectivity
  • Redundant Meet-Me Rooms: Separate physical spaces for carrier equipment
  • Core Network Fabric: High-performance, non-blocking network core
  • Distribution Layer: Redundant connections to each rack row
  • Access Layer: High-density ToR switches with redundant uplinks
  • Security Perimeter: Next-generation firewalls with advanced threat protection

Implementation Methodology

Our network infrastructure implementation follows a structured methodology to ensure comprehensive coverage and optimal performance:

1

Network Assessment

Comprehensive evaluation of existing network infrastructure, identification of reusable components, and gap analysis against AI hosting requirements.

2

Architecture Design

Development of a tailored network architecture blueprint that addresses identified gaps and aligns with performance, reliability, and security requirements.

3

Carrier Selection

Evaluation and selection of telecommunications carriers that best meet the bandwidth, latency, and reliability requirements of AI workloads.

4

Equipment Selection

Selection of network equipment (switches, routers, firewalls) that provides the necessary performance, features, and scalability.

5

Implementation Planning

Development of detailed implementation plans, including timelines, resource requirements, and risk mitigation strategies.

6

Phased Deployment

Structured implementation of network infrastructure in prioritized phases to minimize operational disruption.

7

Testing & Validation

Comprehensive testing of all network components and end-to-end performance validation to ensure requirements are met.

8

Documentation & Training

Development of detailed network documentation and comprehensive training for operations staff.

Case Study: High-Density AI Network

A former cryptocurrency mining facility in Washington state required a network infrastructure upgrade to support high-density AI compute clusters with demanding bandwidth and latency requirements.

Our team implemented a comprehensive network solution that included:

  • 400G backbone network with non-blocking architecture for maximum throughput
  • Direct connectivity to three Tier 1 carriers with automated failover
  • RDMA over Converged Ethernet (RoCE) implementation for ultra-low latency
  • Advanced QoS implementation to prioritize AI workload traffic

Result: The facility achieved consistent sub-5ms latency and sustained 100Gbps+ throughput for AI model training workloads, enabling the client to secure contracts with premium AI research organizations.

In This Section

Need Network Design Assistance?

Our network architects are available to help you design and implement a high-performance network infrastructure for your AI hosting facility.

Contact Our Network Team

Related Playbook Sections

Ready to Upgrade Your Network Infrastructure?

Contact our team today to learn how our comprehensive network design can help optimize your AI hosting data center for performance and reliability.

Schedule a Network ConsultationExplore Other Playbook Sections