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Why Now

Legacy data center
architecture wasn't built
for AI-era demands 

57%

of data center operators say their most recent major outage cost more than $100,000 (Uptime Institute, 2026) 

23%

of impactful outages in 2024 were caused by IT and network failures (Uptime Institute data) 

10–30x

more power per rack that AI workloads draw compared to conventional servers, straining legacy infrastructure (industry analysis, 2026) 

Outcome in numbers

Data center outcomes you can measure 

Typical roi

99.99%+

reduction in mean time to detect, compared to internal teams (AI SOC) 

50-70%

reduction in mean-time-to-resolution through unified telemetry 

60-80%

reduction in manual operational tasks through automation 

Track record

400+

data center projects delivered 

11+ years

of data center practice experience 

Core services

Five ways we deliver datacenter networking

From fabric architecture to unified compute, storage, and management,
pick the entry point that matches where you are today.

Design and implementation of data center network topologies, from traditional three-tier hierarchical designs to modern spine-leaf architectures on Cisco NX-OS, that provide the foundation for all compute, storage, and application workloads.

For organizations:

  • Requiring reliable, high-performance networks for business-critical applications
  • Scaling infrastructure and needing modern, flexible architectures
  • Running databases, analytics, or real-time applications demanding low latency
Engagement Model Fixed-fee project or time-and-materials for phased implementations
Download solutions brief

Problems It Solves

  • Legacy network complexity that's hard to manage
  • Scalability limitations that constrain business growth
  • Insufficient bandwidth causing congestion and performance issues
  • Operational inefficiency from manual configuration and troubleshooting

How It Works

  1. 1 Discovery & AssessmentAnalyze current infrastructure, traffic patterns, capacity, and pain points
  2. 2 Proposal & DesignArchitect the target fabric against business and performance requirements
  3. 3 Implementation & DeliveryDeploy switching infrastructure, integrate, test, and document
  4. 4 Optimization & Ongoing Support Performance tuning, capacity planning, and optional managed

Deliverables

  • Detailed architecture documentation and topology diagrams
  • Standardized configuration templates
  • Implementation runbooks with rollback plans
  • As-built documentation and knowledge transfer
  • Performance baseline reports

Outcomes

  • 10–800 Gbps connectivity with sub-millisecond latency
  • 99.99%+ uptime through fault-tolerant design
  • Reduced provisioning time via standardized, automated designs
  • Platform readiness for 100G/400G/800G and SDN integration

Deployment and optimization of Cisco ACI and related SDN technologies that translate business intent into network configuration, automating policy enforcement across physical, virtual, and cloud environments.

For organizations:

  • Modernizing data centers with automation and cloud-native capabilities
  • Running multi-cloud environments needing consistent policy
  • Requiring microsegmentation and zero-trust architectures
Engagement model Fixed-price project or phased engagement, with optional managed policy services

Problems it solves

  • Manual, error-prone configuration overhead
  • Inconsistent policy enforcement across infrastructure
  • Slow application deployment blocking time-to-market
  • Limited visibility into traffic flows and policy compliance

How it works

  1. 1 Discovery & AssessmentMap application dependencies, security needs, and SDN readiness
  2. 2 Proposal & DesignDesign ACI fabric topology, APIC clusters, and policy framework
  3. 3 Implementation & DeliveryDeploy the fabric, implement policy, migrate workloads, validate
  4. 4 Optimization & Ongoing SupportPolicy refinement, performance tuning, and security posture reviews

Deliverables

  • ACI fabric design documentation and architecture blueprints
  • Policy framework: tenant structure, EPG/ESG, contracts, filters
  • Migration playbooks with rollback procedures
  • Automation templates (Ansible, Terraform, or Python)
  • Operations guide and administrator training

Outcomes

  • Faster application deployment through automation
  • Reduced attack surface via microsegmentation
  • Consistent policy enforcement with audit trails
  • Seamless workload mobility across on-prem and cloud

Complete lifecycle services for Cisco UCS platforms, blade and rack servers, fabric interconnects, and unified management, integrating computing, networking, and storage access into a programmable, self-aware system.

For organizations

  • Running VMware, Hyper-V, or Red Hat OCP virtualization
  • Operating database-intensive workloads (SQL Server, Oracle, SAP HANA)
  • Deploying GPU-accelerated compute for AI/ML
Engagement model Fixed-price implementation or time-and-materials, with optional managed administration

Problems it solves

  • Complex, manual server deployment processes
  • Configuration inconsistency across servers
  • Management complexity from disparate tools
  • Lengthy provisioning times measured in hours or days

How it works

  1. 1 Discovery & Assessment Analyze workload, capacity, and high-availability requirements
  2. 2 Proposal & DesignDesign chassis, fabric interconnects, service profiles, and connectivity
  3. 3 Implementation & Delivery Deploy hardware, configure profiles, integrate, and validate
  4. 4 Optimization & Ongoing SupportPerformance tuning, firmware lifecycle, and capacity planning

Deliverables

  • UCS architecture documentation and connectivity diagrams
  • Service profile templates for repeatable deployments
  • Configuration standards (vNICs, vHBAs, boot, BIOS)
  • Validation reports and performance benchmarks
  • Operations guide and hands-on training

Outcomes

  • Server deployment cut from hours to minutes
  • Configuration drift eliminated via templates
  • Wire-once architecture for rapid I/O reconfiguration
  • Higher server density, smaller data center footprint

Expert design and deployment of Cisco MDS-based Fibre Channel SAN environments, 64G-capable, NVMe/FC-ready, delivering high-performance, highly available storage connectivity for mission-critical applications.

For organizations

  • Requiring mission-critical storage for production databases
  • Implementing NVMe/FC or all-flash storage systems
  • In compliance-driven industries (financial services, healthcare)
Engagement model Fixed-price project or time-and-materials, with optional managed monitoring

Problems it solves

  • Storage performance bottlenecks impacting applications
  • Availability gaps risking downtime
  • SAN management complexity
  • Limited troubleshooting visibility

How it works

  1. 1 Discovery & AssessmentEvaluate storage requirements, I/O profiles, and availability needs
  2. 2 Proposal & Design Design fabric topology, zoning architecture, and VSANs
  3. 3 Implementation & DeliveryDeploy MDS switches, zoning, VSANs, and integrate storage arrays
  4. 4 Optimization & Ongoing Support Performance monitoring, capacity planning, firmware lifecycle

Deliverables

  • SAN architecture documentation and topology diagrams
  • Zoning database and naming conventions
  • VSAN design for multi-tenant segmentation
  • Performance baseline and capacity reports
  • Operational procedures and administrator training

Outcomes

  • 32G/64G Fibre Channel with ultra-low latency
  • 99.999% availability through redundant design
  • Faster problem resolution via integrated analytics
  • Investment protection for future protocols

Implementation of Cisco Nexus Dashboard for unified visibility, automation, and lifecycle management across ACI and NX-OS environments, with AI-driven intelligence and streamlined workflows.

For organizations

  • Managing multiple data center locations
  • Running Cisco ACI needing simplified orchestration
  • Managing hundreds or thousands of switches
Engagement model Fixed-price implementation or time-and-materials, with optional managed administration

Problems it solves

  • Management fragmentation across multiple tools
  • Limited visibility across the data center estate
  • Reactive operations instead of proactive issue resolution
  • Manual, error-prone provisioning and monitoring

How it works

  1. 1 Discovery & Assessment Evaluate fabric inventory, site topology, and integration needs
  2. 2 Proposal & DesignDesign cluster sizing, service selection, and site onboarding strategy
  3. 3 Implementation & DeliveryDeploy Nexus Dashboard, onboard sites, enable services, validate
  4. 4 Optimization & Ongoing SupportPlatform maintenance, workflow development, proactive monitoring

Deliverables

  • Platform architecture documentation (cluster design, nodes)
  • Service configuration for Insights, Orchestrator, Fabric Controller
  • Custom dashboards and reports
  • API integration documentation
  • Operations guide and platform training

Outcomes

  • Operational overhead reduced by 40–60%
  • MTTR reduced 50–70% via advanced telemetry
  • Manual tasks reduced by up to 60–80%
  • Uniform policy enforcement across all sites

Trusted by Security Leaders

"Enterprises need secure AI infrastructure that is simple to deploy,
trusted, and easy to manage from day one. Our work with Gruve brings
assurance directly into the PulseAI Platform, so enterprises can move
fast without compromising on governance or control."

https://gruve.ai/wp-content/uploads/2026/05/Frame-236-1.png

Cassie Roach

Global VP of Cloud and AI Infrastructure Partner Sales at Cisco
See Cisco x Gruve architecture
WHY GRUVE

Why Gruve for datacenter networking

400+ data center projects delivered, backed by CCIE-certified engineers and a global NOC.

Proven track record

400+ data center projects delivered over 11+ years of practice experience.

Deep certification

CCIE Data Center and CCIE Routing/Switching engineers on every engagement.

Multi-vendor expertise

Vendor-agnostic assessments and delivery across Cisco, Juniper, Arista, and HP Aruba.

Global NOC

24×7 real-time monitoring, incident response, and SLA compliance for data center and cloud network environments.

Compliance-ready

Delivery aligned to SOX, PCI DSS, ISO/IEC 27001, NIST 800-53, HIPAA/HITRUST, GDPR, FFIEC, and GLBA.

Multi-Site Data Center Deployment (Hospital)

Challenge: Legacy network with poor security, no redundancy, and limited visibility caused outages.

Solution: Deployed ACI Multi-Site with EVPN/VXLAN, PBR, and NGFW.

 

DCNM to NDFC Migration

Challenge: DCNM's slow VLAN deployments and multi-fabric inefficiencies.

Solution: Migrated to NDFC with validated hardware, streamlined configuration imports, and automation.

FAQs

Frequently asked questions about
datacenter networking

What's the difference between traditional and spine-leaf network designs?

We deliver both traditional three-tier hierarchical designs and modern spine-leaf architectures on Cisco NX-OS. Spine-leaf topologies flatten the network for lower latency and more predictable east-west traffic performance, which is why most new deployments favor it — but the right choice depends on your workload requirements and growth plans.

Do you support multi-vendor environments?

Yes. Our network health checks and assessments are vendor-agnostic, covering Cisco, Juniper, Arista, and HP Aruba environments.

Can this integrate with our existing VMware or cloud environment?

Yes. Our SDN and unified compute engagements are designed to integrate with your existing virtualization platform (VMware, Hyper-V, Red Hat OCP) and extend consistent policy to AWS, Azure, and Google Cloud.

What compliance frameworks do you support?

Our delivery aligns to SOX, PCI DSS, ISO/IEC 27001/2, NIST 800-53/171, HIPAA/HITRUST, GDPR, FFIEC, and GLBA.

Do you offer ongoing managed services after deployment?

Yes. Every service — network fabric, SDN, unified compute, SAN, and data center management — can include optional subscription-based managed services for ongoing monitoring, administration, and optimization, backed by our global NOC.

Get Started

Modernize your data center
for the age of AI

Modernize your data center for the age of AI
from first assessment to full production, and everything after.

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