Tag Archives: Hewlett Packard Enterprise

Better Together: How HPE, AMD and Nutanix Empower Modern Enterprises

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The rapid evolution of enterprise technology has made modernization an urgent priority. Businesses today face challenges ranging from complex infrastructure and escalating costs to the rising demands of artificial intelligence (AI) and hybrid cloud environments. Together, Hewlett Packard Enterprise (HPE), Advanced Micro Devices (AMD) and Nutanix provide unified solutions that simplify operations, strengthen security and deliver unmatched performance, empowering organizations to navigate current demands and prepare for the future.


Addressing Market Challenges with Innovation

In a dynamic market where infrastructure complexity and cost pressures are top concerns, the combined expertise of HPE, AMD and Nutanix is driving transformative solutions. Nutanix’s hyperconverged infrastructure (HCI) simplifies multicloud management, enabling organizations to run workloads across on-premises, public and private clouds or colocation sites. With intuitive tools like Prism, Nutanix delivers flexibility, cost efficiency and robust security.

On the hardware side, AMD’s EPYC Central Processing Units (CPUs) have revolutionized the data center market, achieving a 34% market share through scalability (i.e. higher core count options that help reduce server footprint). Designed for diverse workloads, including analytics and hybrid workforce applications, AMD solutions like the 4th Gen EPYC CPUs provide outstanding performance while optimizing total cost of ownership (TCO).

Meanwhile, HPE’s ProLiant DX Gen 11 servers offer fast deployment, tailored configurations and scalable options for diverse business needs. Supported by OpEx models like GreenLake, HPE ensures financial flexibility, making modernization accessible for organizations of all sizes.


Unlocking the Potential of AI

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AI is reshaping industries, and the HPE, AMD and Nutanix partnership enables enterprises to meet these infrastructure demands. Nutanix’s HCI platform, paired with AMD’s EPYC CPUs, deliver optimized performance for AI and machine learning (ML) workloads. The Nutanix DX 385 model supports up to four double-wide Graphics Processing Units (GPUs), providing accelerated compute for AI-driven environments. With features like network microsegmentation and automated lifecycle management, Nutanix ensures secure, optimized environments for AI applications.

AMD’s EPYC processors are tailored for AI applications, from small-scale enterprise large language models (LLMs) to large-scale generative AI. High core density and features like Secure Encrypted Virtualization (SEV) ensure robust performance and security. HPE complements this with ProLiant DX servers designed for AI workloads, including their “GPU in a Box” model, which simplifies deployment and scales with demand, making it easier for businesses to meet the demands of AI-driven applications. Together, these technologies provide enterprises with the computational power and flexibility to unlock AI’s potential within hybrid cloud environments.


Simplifying Modernization Across Infrastructure

Modernization is no longer optional—it is a necessity for businesses navigating an evolving IT landscape. Businesses face the dual challenge of balancing legacy infrastructure needs with the demands of the future. HPE, AMD and Nutanix simplify this transition by addressing performance, security, management and integration, ensuring organizations modernize effectively while maintaining operational continuity.

Performance

Nutanix software on AMD EPYC-powered HPE ProLiant DX servers handles workloads like virtualization, analytics, big data and AI/ML with exceptional performance. The 4th Gen EPYC CPUs deliver high performance across metrics including per core and per server, reducing infrastructure costs. High-frequency CPU options enable the provisioning of more virtual machines and workloads without increasing physical cores, ensuring businesses can scale seamlessly as demands evolve. HPE delivers two high-performance NVMe storage options, designed to boost data center performance while ensuring reliability and security. HPE NVMe Mixed Use (MU) SSDs use Peripheral Component Interconnect Express (PCIe) Gen4 to boost performance for Big Data, high-performance computing (HPC) and virtualization with fast transfers and low latency. HPE NVMe Read Intensive (RI) SSDs optimize read-heavy workloads like web servers, storage and caching with high-speed PCIe Gen3 and Gen4.

Security

Nutanix integrates features like automatic auditing, encryption and network microsegmentation to ensure compliance and safeguard IT environments. AMD EPYC processors add another layer of protection with SEV, isolating virtual machines with memory encryption for silicon-level protection. HPE’s Silicon Root of Trust protects firmware from the boot process and continuously monitors the Basic Input/Output System (BIOS), ensuring server integrity and preventing breaches​.

Management

Managing modern IT environments is simplified with Nutanix’s one-click updates and lifecycle management capabilities, which integrate seamlessly with HPE’s Service Pack for ProLiant. Nutanix Prism offers a unified management plane, enabling centralized control for clusters, applications and data. The intuitive management interface reduces complexity, empowering IT teams to handle hybrid cloud environments with ease and efficiency.

Integration

Pre-installed with Nutanix Acropolis OS (AOS), HPE ProLiant DX servers offer out-of-the-box solutions optimized for AMD EPYC processors. These systems support diverse hypervisors, including Nutanix Acropolis Hypervisor (AHV) and third-party options, giving businesses the flexibility to tailor infrastructure setups to specific needs. This collaboration ensures workload-specific performance and seamless integration across various deployment environments, helping businesses modernize without disruption.


HPE, AMD and Nutanix demonstrate the power of collaboration by offering a unified approach to modernization. By combining high performance, robust security, streamlined management and flexible integration, their solutions provide businesses with the tools they need to meet today’s challenges and prepare for tomorrow’s demands. Collectively, they simplify the journey to modernization, proving that they truly are better together.


Discover how HPE, AMD and Nutanix are better together in delivering powerful, secure and scalable solutions for modern enterprises. Watch our webinar, “Modernize Your Infrastructure with HPE & Nutanix – Powered by AMD,” to explore cutting-edge innovations and actionable strategies that transform IT environments.


Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including HPE, AMD and Nutanix, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

Democratizing AI: How Pre-trained Models Plus RAG Can Empower State and Local Agencies

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Smaller state agencies need out-of-the-box options that solve immediate needs without a lot of funding or skilled machine learning expertise. Combining RAG with pre-trained LLMs and the agency’s own data accelerates development of AI capabilities and speeds time to value.

In my role at HPE over the last two years, I’ve had meetings with government agencies, defense departments, and research institutions around the world about AI. We’ve discussed everything from how to identify the right use cases for AI, to ethical concerns to getting a handle on the wild, wild west of AI projects across their organizations.

Some of these larger public sector organizations and government agencies have received funding from sources like the U.S. National Science Foundation, U.S. Defense Advanced Research Projects Agency (DARPA), the European Commission’s EuroHPC Joint Undertaking (EuroHPC JU), or the European Defense Fund, which has allowed them to develop AI centers of excellence and build end-to-end AI solutions. They have far-reaching goals — goals such as building the first large language model (LLM) for their native language, becoming the first sovereign, stable, secure AI service provider in their region, building the world’s most sustainable AI supercomputer, or becoming the world leader for trustworthy and responsible AI.

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But it takes a lot of resources to train an AI model. The infrastructure needed to train a foundational model may include thousands of GPU-accelerated nodes in high performance clusters. Data scientists and machine learning (ML) engineers are also needed to source and prepare datasets, execute training, and manage deployment.

That’s why many agencies are looking for out-of-the-box options that bring rapid capabilities for solving immediate challenges. Many of these are state and local agencies and higher education institutions. They don’t have the same level of requirements, funding, or expertise to build their own LLMs.

So does that mean the door to powerful AI models is closed on smaller state and local agencies?

No — not if you can gain an understanding of the available pre-trained models that can generate value with AI immediately. There is so much that can be accomplished without ever training a model yourself.

Inference is AI in Action

What exactly is inference? It’s the use of a previously trained AI model such as an LLM to make predictions or decisions based on new, previously unseen data.

Sound complicated? It’s just a fancy way of saying that you’re using an existing model to generate outputs.

In contrast with model training, which involves learning from a dataset to create the model, inference is using that model in a real-world application. Inferencing with pre-trained models reduces both funding requirements as well as the amount of expertise needed to deploy and monitor these models in production.

The pre-trained model market has been steadily growing, as have the number of cloud, SaaS, and open source inference options available. Open AI’s GPT-4o, Anthropic’s Claude, Google’s Gemini, and Mistral AI are among the most popular LLMs used for text and image generation. They’re just some of the thousands of models available through libraries like NVIDIA NGC and HuggingFace.

And just last month in Las Vegas, HPE also made an important announcement of their new NVIDIA AI Computing by HPE portfolio of co-developed solutions. These solutions include HPE’s Machine Learning Inference Software (MLIS), which makes it easy to deploy pre-trained models anywhere including inside your firewall.

Pre-trained Models with Your Data

The advantages of running a pre-trained model with the right platform seem pretty clear — you get the capabilities without the costs of training. However, it’s important to note that a pre-trained LLM excels in general language understanding and generation but is trained on some data other than your own. This is great for use cases where broad knowledge is sufficient and the ability to generate coherent, contextually appropriate text are essential.

So what do you do if you need to generate more specific and up-to-date outputs? There is another machine learning (ML) technique called retrieval augmented generation (RAG) which combines the pre-trained LLM with an additional data source (such as your own knowledge base). RAG combines LLM capabilities with a real-time search or retrieval of relevant documents from your source. The resulting system works like an LLM that’s been trained on your data, but with even more accuracy. RAG is particularly useful for tasks requiring specific domain knowledge or recent data.

Improving Outcomes for State Agencies

Getting started with AI models begins with understanding which problem you want to solve and whether it is most efficiently and effectively solved with AI. Here are some ways different kinds of organizations can leverage pre-trained LLMs:

Law enforcement agencies can use pre-trained models for incident reporting and documentation, to analyze crime data for predictive policing, or to analyze audio and video transcription for evidence management. They can improve community engagement through sentiment analysis and reduce administrative burdens through automated report generation.

Conversational AI can also make many types of citizen services more efficient and user-friendly — from permit applications to public query engines for local government agencies. And LLMs can automate document processing, reducing manual tasks for government workers and improving speed and accessibility of services to citizens.

LLMs can enhance the education experience for students and reduce the burden on teachers. AI-powered virtual assistants can provide tutoring and study support to students outside of school hours and assist researchers in conducting literature reviews by summarizing academic papers or extracting information.

As you consider leveraging pre-trained LLMs, think about the unique problems your agency or institution faces and how this approach could quickly solve those challenges without the need for extensive expertise or the burden and cost of training a model from scratch.

Final Thoughts

As the world and society evolves, the relationship between citizens and their governments, students and their teachers, will evolve too. In fact, they already are. Taking advantage of pre-trained models to solve long-standing automation issues or cumbersome documentation processes can give your organization the catalyst it needs to modernize to meet these new dynamics.

AI is being democratized by a growing number of pre-trained LLMs that are available off the shelf. And you don’t need to have complex data science skills to leverage them, just the right tools.

The door to AI is open for state and local agencies, regardless of size or sophistication. A part of my job is to understand the challenges and goals of public sector organizations of all sizes when it comes to AI.

To learn more about HPE Private Cloud AI, visit the Private Cloud AI solutions overview page and contact the HPE team for questions and comments.

This post originally appeared on HPE.com and is re-published with permission.

Better Cloud with Nutanix and HPE

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Today, almost everything online is conducted and saved through the cloud. Government agencies face the obstacle of modernizing their software infrastructure and navigating cloud-based solutions to achieve mandates. That’s why Nutanix, an American cloud computing company that unites public cloud simplicity and agility with private cloud performance and security, has taken up the mission to radically simplify and secure how organizations across all industries and sectors run apps and manage data. With its recent partnership with Hewlett Packard Enterprise (HPE), Nutanix aims to create and provide its own private cloud platform that unifies storage, provides database and desktop services, provides hybrid cloud infrastructure and offers cloud management with the goal of supporting any application and workload. All these objectives have been optimized into one secure, easy-to-use product—Nutanix Cloud Platform.

One Unified Cloud

Nutanix pioneers the cloud market with an adaptable, endlessly scalable user-interface. With its built-in intelligence system, Nutanix Cloud Platform can manage apps and data to maximize efficiency and performance. Its features are robust and resilient, as it will replicate data in small slices so that the software can efficiently recover from outages and withstand cybersecurity attacks.

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HPE and Nutanix’s global partnership brings customers more options. Unlike other cloud spaces, which have predetermined settings, Nutanix Cloud Platform grants users additional flexibility to adapt the cloud to their needs. Users can customize their clouds, apps and technology stacks with rapid time-to-value benefit. The cloud platform has the largest breath of platforms among any cloud, the ability to run ESX AHV and the freedom to scale up or down. Nutanix Cloud Platform includes a hybrid cloud infrastructure, a unified control plane, unified APIs, a secured base, a built-in hypervisor and a built-in lifecycle management.

Nutanix enables every industry to meet its goals. Fourteen different platforms are certified on HPE, giving users the option to choose which solution they use. Over the last 24 months, Nutanix has maintained a 91% Net Promoter Score reflecting its satisfied customer base, considering that the average NPS score is 45%.

Secure with Nutanix

As the world’s largest retailer of software, Nutanix must not only be prepared to deliver a beneficial product, but a secure product. Since multiple Federal, military and intelligence agencies use Nutanix, and since the basics of Government standardize around Nutanix, its cybersecurity is an issue of national security. Nutanix provides several vital security features, including:

  • Factory security hardening and baseline
  • Automated configuration validation and self-healing
  • Data-at-rest encryption
  • Localized encryption key management built into the system
  • Network segmentation and micro segmentation
  • Multi-factor authentication, role-based access and security assertion markup language
  • Data protection, including snapshotting and multi-site capabilities, synchronized replication and constant availability
  • Security on back end that monitors the network and investigates violations to ensure continuous compliance on company scanning tools
  • Encryption capabilities built into the software that cluster lockdown to ensure data cannot be accessed by outside actors

In addition, on request of the Government, Nutanix added a Kernel-based Virtual Machine, which makes the software substantially easier to use. The cloud platform’s certified solutions and joint engineering encourages users to acquire and expand vaster capabilities. By automating the process, Nutanix Cloud Platform promotes sustainable life cycle management.

Nutanix’s cloud is always improving. Manufacturers share testing notes to evaluate the most accurate assessment of the product. There is a dedicated support group for Nutanix and HPE customers that can help users with any issues that arise. Through consistent updates and a shift from capacity-based licensing to processor based, these cloud providers ensure the product is user friendly and easy to bundle with other products.

Better Together

With Nutanix and HPE’s partnership, the cloud has been revitalized as a user-friendly, unified platform to keep industries secure, as well as to provide a streamlined platform for all workloads and data. With Nutanix Cloud Platform, customers can minimize cost, performance and risk all with one product.

View our webinar and dive deeper into the benefits of Nutanix Cloud Platform from Nutanix and HPE’s partnership.