How Cisco and Pure are Shaping the Future for Enterprise AI

Artificial Intelligence (AI) continues to transform modern business, shaping everything from product development to customer engagement. Cisco's FlashStack Datacenter stands at the forefront of this evolution, integrating high-performance computing, best-in-class GPU acceleration and advanced storage solutions, and the NVIDIA AI Enterprise software suite. This cohesive architecture forms the core of a modern AI stack, essential for driving innovation and efficiency in today's competitive landscape.

Understanding Cisco Validated Designs

Cisco Validated Designs (CVDs) are practical, tested and documented blueprints that help businesses integrate leading-edge technologies in an optimized manner. Each CVD:

Builds on a Systems Design Foundation: Ensures all hardware and software components work seamlessly together.
Undergoes Rigorous Testing: Reduces the guesswork often associated with new deployments by stress-testing every design in real-world scenarios.
Provides Targeted Guidance: Offers both Technology Design Guides and Solution Design Guides, along with a Navigator feature that helps teams identify the right configuration and additional resources.
Serves as a Launching Point: Empowers Cisco partners and customers to move quickly into production with minimal risk.
Remains Easily Accessible: Comprehensive documentation is available via the Cisco Design Zone.

The Power of FlashStack for AI

Cisco's focus on AI shines through the FlashStack Datacenter powered by NVIDIA, bringing together high-performance compute, GPU acceleration and advanced storage, and the NVIDIA AI Enterprise software suite to create a modern AI ecosystem. Key elements include:

Sustainability and Efficiency

Designed with energy efficiency in mind, the solution lowers power and cooling costs, reduces the carbon footprint through higher storage and compute density, and incorporates energy-aware algorithms that dynamically adjust power usage.

Cisco UCS X-Series Modular Platform

UCS X210c M7 Compute Nodes: Equipped with powerful Intel CPUs to handle the enormous computational demands of AI and machine learning.
X440p PCIe Nodes for GPU Expansion: Support multiple NVIDIA GPUs (Tesla A100, H100, L40 and L40S), delivering the necessary horsepower for training deep learning models, inferencing, and other AI tasks.

Pure Storage Portfolio

FlashArray: An all-flash storage solution designed for speed and reliability, delivering consistently high performance in AI environments where low-latency data access is critical.
FlashBlade: Purpose-built for unstructured data, supporting massive throughput at low latency—essential for large-scale AI and machine learning workloads.
Portworx Enterprise: Ideal for containerized applications, providing resilient, scalable data services that complement the speed and capacity of FlashArray and FlashBlade while providing data scientists with self-service access to the data storage.

Integrated Networking and Connectivity

IFM 100G Fabric: Offers high-speed data movement with minimal latency, crucial for real-time processing.
Cisco 6536 and 6454 Fabric Interconnects: Provide high-bandwidth, low-latency Ethernet options (100G and 25G), ensuring balanced performance for data ingestion and advanced analytics.

Software Synergies

NVIDIA AI Enterprise software platform: Accelerates the development and deployment of production-grade AI solutions with easy-to-use microservices that optimize model performance, plus enterprise stability, support, and security.
Red Hat OpenShift: Streamlines AI application deployment, updates and scaling.
VMware vSphere: Adds virtualization efficiencies, enabling AI workloads to run securely in isolated environments.
NVIDIA GPU Optimization: Fine-tunes the software stack to harness the power of NVIDIA accelerated computing for model training and inferencing.
Portworx Data Services: Gives your developers self-service access to deploy, maintain and scale databases within minutes from a broad catalog of database services that utilize recommended best practices and templates managed by your organization.

Cisco AI PODs: A plug-and-play approach to AI infrastructure

Building on the same principles as FlashStack, Cisco AI PODs offer right-sized bundles for specific AI workloads—from edge inferencing to large-scale clusters. Each POD integrates compute, GPU, networking and storage and NVIDIA AI Enterprise software into a unified, plug-and-play solution optimized for accelerated AI deployment and simplified management. Key highlights include:

Pre-validated Bundles: Based on Cisco Validated Designs, making them easy to deploy alongside or independently of other CVD-based solutions.
Comprehensive Software Stack: Includes NVIDIA AI Enterprise, a cloud-native, production-ready platform that simplifies AI pipeline development and deployment.
Centralized Management: Managed via Cisco Intersight, providing real-time visibility and policy-driven automation across the UCS X-Series environment, allowing teams to quickly scale or repurpose resources as needed.
Flexible Integration and Automation: Enhanced by integrated automation tools such as Ansible playbooks and unified monitoring systems, which streamline lifecycle management and simplify operations.
Cost Efficiency and Subscription Models: Offering predictable costs, lower total cost of ownership (TCO), and flexible subscription-based "FlashStack as-a-service" models that optimize financial investments.

Small/ Edge to Scale-Out with Cisco UCS AI POD

Tackling AI deployment challenges

Both FlashStack and Cisco AI PODs address common hurdles in AI deployments:

High Computational Needs: Powerful compute nodes, GPU expansion capabilities, and robust storage meet the demands of large model training and inferencing.
Latency and Real-time Processing: High-speed Ethernet fabric and all-flash storage reduce bottlenecks, ensuring real-time results in latency-sensitive applications.
Complexity and Scale of AI Models: Unified compute and storage frameworks simplify data management and enable easy scaling as models grow more complex.
Monitoring, Visibility and Security: Tools like Cisco Intersight provide proactive monitoring and lifecycle management, while integrated security features protect data at rest and in transit.

Business impact and the WWT AI Proving Ground

Cisco and Pure Storage's integrated designs provide organizations with the confidence to deploy AI without dealing with fragmented infrastructure or unpredictable performance. Teams can focus on advancing AI use cases — such as automating repetitive tasks, fine-tuning customer experiences, or unlocking new insights from data — rather than managing the backend.

WWT's AI Proving Ground (AIPG) plays a crucial role in this ecosystem. By leveraging WWT labs and sandbox environments, businesses can test and refine their AI approach on real hardware — from full-scale FlashStack configurations to smaller Cisco AI POD setups — before making a production commitment. This accelerates time to value and reduces the risk of large-scale AI investments.

Looking ahead: A future-ready blueprint

For organizations exploring or scaling AI initiatives, Cisco and Pure Storage provide the foundational technology, while WWT's AI Proving Ground offers the hands-on expertise and pre-production testing needed for successful implementation. This enables businesses to embrace AI-driven projects with confidence, knowing they have a proven, validated path to efficiency, speed, and transformative outcomes.

Call to action

To learn more, visit our WWT AI Proving Ground for additional resources and demonstrations. Alternatively, reach out to your WWT sales team to discuss how Cisco, Pure Storage and AI PODs can accelerate your AI journey.