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WHAT WE DO

Visit the ePlus AI Experience Center

Experience the full AI infrastructure lifecycle before deploying it at scale. Our experts guide you through design best practices, implementation approaches, operational models, and real-world GPU, networking, and storage architectures so you can make confident decisions.

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HOW ePLUS CAN HELP

Experiencing AI Infrastructure

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In partnership with Digital Realty, we provide hands-on demonstrations of the complete advanced AI infrastructure stack and the platform requirements needed to run enterprise AI. You’ll be able to explore real-world AI solutions built for AI workloads and interact with automated deployment, management, and monitoring demos. Read the digital brochure.

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Automated AI Infrastructure Provisioning

Full-stack Deployment: Demonstration across compute, storage, and networking
Infrastructure as Code: Consistent, repeatable workflows for faster time-to-value
Automation Tools: Scalable provisioning to reduce manual effort

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Managing Your AI Infrastructure – Intelligent Automation

Daily Ops Automation: Patch management, upgrades, compliance checks
Infrastructure Visualization: Real-time status, drift detection, remediation workflows
Lifecycle Efficiency: Automated maintenance and lifecycle operations

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GPU Resource Management Demo with Run:ai and SLURM

GPU Optimization: Dynamically schedule and isolate GPU workloads across teams and projects
Intelligent Scheduling: Improve utilization and reduce idle time
Interactive and batch workloads: Maximize throughput and flexibility

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Monitoring Your AI Infrastructure

Real-Time Metrics: Monitor GPU, memory, and network stats via Grafana and Prometheus
Alerting and Thresholds: Custom thresholds and proactive alerting
Automated Ticketing: Seamless integration with ServiceNow, Jira
Capacity Planning: Forecast trends to optimize resources

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Experience the full ML lifecycle with Weights & Biases integration

MLOps with Weights & Biases (W&B)

Experiment Tracking: Log hyperparameters, metrics, system stats
Artifact Management: Version datasets, models, and outputs
Model Registry: Promote models across dev/staging/production
Reporting and Collaboration: Auto-generated dashboards for audit trails and team sharing

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Engage with AI experts to discuss real world use cases and best practices

Advanced AI Infrastructure Use Cases

Dynamic GPU Management: Efficient GPU utilization with Run:ai and SLURM
Orchestration: Centralized scheduling via NVIDIA Base Command Manager
AI on Kubernetes: Scalable container-based AI infrastructure
High-Performance Networking: Optimized Ethernet fabric for distributed workloads
Scalable Storage: High-throughput systems designed for AI data pipelines
Hybrid and Multi-Cloud Deployments: Manage AI workloads across edge, on-prem, and cloud
GPU-as-a-Service: A consumption-based platform demonstrating bare metal provisioning and VM-based provisioning along with billing, orchestration, and integrated management and monitoring

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WHY ePLUS

Our Unique Differentiators

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Confidence to Deploy at Scale

Learn best practices for automated provisioning, management, and monitoring of AI infrastructure by leveraging automation, real-time insights, GPU resource management, MLOps lifecycle management, and more.

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AI building blocks

Purpose-Built for AI

Our AI Experience Center provides access to the latest AI infrastructure solutions, enabling you to explore a variety of AI technologies. Learn how to design power, cooling, compute, networking, storage, and security solutions to support your AI needs.

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Partnership with Digital Realty

ePlus partners with Digital Realty, a leading global provider of cloud- and carrier-neutral data center, colocation, and interconnection solutions who operates the largest global data center platform with 315+ data centers across 50+ metros in 26 countries.