Open Source Tools Seen as Vital for AI in Hybrid Cloud Environments

The convergence of AI, hybrid cloud, and open-source technology is redefining enterprise IT, and AI is no longer just a futuristic concept; it is transforming businesses, industries, and economies at an unprecedented pace. From automating complex processes to uncovering insights buried within massive datasets, AI has become a cornerstone of digital transformation. However, scaling AI for enterprise use comes with its own set of challenges: high infrastructure costs, data privacy concerns, interoperability issues, and the need for continuous innovation.

To tackle these obstacles, organizations are turning to hybrid cloud and open-source solutions, which provide the agility, security, and scalability that AI-driven businesses need. Few companies are as deeply embedded in this transformation as Red Hat, a leader in open-source enterprise solutions. At the helm of Red Hat’s partner ecosystem success is Stefanie Chiras, Senior Vice President, who believes that open-source collaboration and hybrid cloud architectures are key to unlocking AI’s full potential.

In an exclusive interview, Chiras discusses how Red Hat is shaping the AI revolution, the challenges businesses face in adopting AI, and why open-source innovation will define the next era of enterprise IT.

What impact do you see AI having on the future of hybrid cloud platforms, and how is Red Hat positioned to lead this transformation?

Hybrid cloud enables organizations to take advantage of innovation wherever it exists, with the flexibility and choice to select the AI solutions and technologies that best meet their specific requirements. Data lives everywhere, whether it’s on-premises, in the cloud or at the edge – it is hybrid. And, because AI needs to run where your data lives, it must also be hybrid. In fact, Red Hat likes to refer to AI as the ultimate hybrid cloud workload.

Training may be done in the data center, but organizations will need to deploy applications based on that training across multiple platforms — ideally, by adding onto (and not replacing) existing infrastructure and skills. Red Hat brings our years of experience in hybrid cloud to inform AI strategies and implement the technology in an open, hybrid model from the start. This includes not only developing a plan for building, testing, and deploying AI models and applications where they make the most sense from a business perspective, but also tapping into platforms with native, built-in AI capabilities to more efficiently and cost effectively optimize, scale and secure those applications.

Red Hat is an established pioneer for open hybrid cloud, delivering consistent, trusted and comprehensive platforms powered by open source innovation across the hybrid cloud. And now, we’re doing the same for AI. This is a natural evolution for Red Hat given our roots in open source communities, which have always been at the forefront of emerging technologies like AI, and our proven track record with hybrid cloud.

Can you briefly share your perspective on the evolving landscape of enterprise open source solutions and Red Hat's role in it?

The landscape of enterprise open source solutions is evolving rapidly, driven by the need for flexibility, scalability, and innovation. Enterprises are increasingly relying on open source technologies to drive digital transformation, accelerate software development, and foster collaboration across ecosystems. With advancements in cloud computing, AI, and containerization, open source solutions are shaping the future of IT by providing adaptable and secure platforms that meet evolving business needs.

The active and diverse community support ensures continuous improvement, making open source a cornerstone of modern enterprise technology strategies. Red Hat's portfolio, including Red Hat Enterprise Linux, Red Hat OpenShift, Red Hat AI and Red Hat Ansible Automation Platform, provides robust platforms that support diverse workloads across hybrid and multi-cloud environments. Additionally, Red Hat's extensive partner ecosystem provides more seamless integration and support for a wide range of technologies and applications. Our commitment to open source principles and continuous innovation allows us to deliver solutions that are secure, scalable, and tailored to the needs of our customers. Open source has proven to be trusted and secure at the forefront of innovation – Red Hat and our partners are key multipliers to unlock that innovation with enterprise customers.

How is Red Hat's open source approach facilitating the integration of AI into enterprise applications and hybrid cloud platforms?

Red Hat’s open source approach helps break down barriers of entry to AI by fostering innovation, scalability, and flexibility, enabling organizations to more easily and seamlessly integrate  AI into applications and solutions. Through our open hybrid cloud framework, powered by solutions like Red Hat OpenShift AI and Red Hat Enterprise Linux AI, Red Hat provides enterprises with a unified platform to deploy AI-enabled applications and workloads across on-premises, cloud, and edge environments.

By leveraging open standards, enterprises gain access to cutting-edge AI tools and frameworks that are highly adaptable to their specific needs. This approach also allows IT teams to integrate AI more efficiently into their workflows, reducing complexity and accelerating deployment timelines.

In addition, Red Hat’s portfolio is surrounded by a skilled partner ecosystem to further extend AI capabilities. For instance, collaborations with Intel and NVIDIA enable enterprises to optimize AI workloads for advanced hardware, improving performance and cost-efficiency. Red Hat also collaborates with leading systems integrators like Accenture, which empowers clients to adopt AI-driven solutions at scale using Red Hat’s open hybrid cloud technologies. These partnerships showcase how Red Hat’s ecosystem can help pave the way for AI innovation while delivering operational efficiency, positioning enterprises for success in an increasingly AI-driven market.

Can you elaborate on the specific challenges businesses face when scaling AI, and how Red Hat's solutions address these pain points?

Scaling AI poses two significant challenges for businesses: managing costs and energy consumption. Organizations struggle to align gen AI models to their business requirements due to complex training and tuning processes, high costs of training large multipurpose models, and lack of technical expertise. Traditional approaches like fine-tuning require specialized data scientist/AI skills and organizations are challenged to incorporate AI into their business while often hindered by the lack of in-house knowledge.

Red Hat addresses these cost barriers through Red Hat OpenShift AI,  RHEL AI and InstructLab, which democratize AI adoption by enabling IT professionals, even with minimal machine learning expertise, to work with large language models (LLMs) and generative AI applications. This reduces dependency on specialized data scientists, whose scarcity and high salaries make AI adoption prohibitively expensive for many enterprises.

RHEL AI also accelerates the process of going from proof of concept to production server-based deployments by providing all the tools needed and the ability to train, tune, and deploy these models where the data lives, anywhere across the hybrid cloud. When organizations are ready, it also provides an on-ramp to Red Hat OpenShift AI, for training, tuning, and serving these models at scale across a distributed cluster environment using the same Granite models and InstructLab approach used in the Red Hat Enterprise Linux AI deployment. By simplifying AI deployment and broadening accessibility, Red Hat’s solutions help businesses significantly lower the financial barriers associated with AI integration.

On the sustainability front, data centers account for 1-1.5% of the global energy consumption, according to the International Energy Agency. Because AI systems rely on a robust infrastructure, organizations are facing increasing operational costs and environmental impact. Red Hat’s Kepler and Climatik projects directly address this challenge. Kepler provides actionable insights into energy consumption, enabling businesses to monitor and optimize the efficiency of AI workloads. Climatik, on the other hand, introduces innovative power-capping solutions, helping organizations enhance data center sustainability without sacrificing performance.

Together, these tools empower businesses to scale AI responsibly, aligning with modern sustainability goals while optimizing resource usage and reducing their carbon footprint. With these solutions, Red Hat equips enterprises to navigate the complexities of AI scaling while minimizing costs and environmental impact.

Can you share success stories or examples of partners utilizing open source innovation for AI use cases in different cloud environments?

For many organizations, AI is now a business imperative. As an established catalyst for open source innovation, Red Hat’s global partner ecosystem is equipped to bring AI use cases to life for customers across any cloud, datacenter or network edge.  

Spanning hardware providers, systems integrators, independent software vendors (ISVs), cloud and service providers and more, Red Hat partners support customers across the full spectrum of hybrid cloud workloads, including AI. By providing in-depth skills, knowledge and certified workloads built on Red Hat’s industry-leading hybrid cloud platforms, including Red Hat OpenShift, Red Hat Ansible Automation Platform, Red Hat OpenShift AI and Red Hat Enterprise Linux AI, our partners help organizations accelerate innovation and implement transformative AI solutions. For example:

● Hardware providers like Dell and Lenovo work with us to validate and support Red Hat’s AI portfolio, including Red Hat Enterprise Linux AI and Red Hat OpenShift AI, on their industry-leading servers.

● GPU and chip providers like NVIDIA, AMD and Intel are collaborating with Red Hat to integrate support for their AI accelerators and GPUs within Red Hat Enterprise Linux AI and OpenShift AI to streamline AI workflows for customers.

● Application vendors collaborate with Red Hat to deliver solutions that are compatible and supported on Red Hat OpenShift AI for streamlined integration and enhanced performance throughout the AI/ML lifecycle.

● Certified AI/ML partner applications can be natively integrated within Red Hat OpenShift, as well as provide complementary or extended capabilities on Red Hat OpenShift AI.

● Pre-integrated AI/ML partner applications are available within the Red Hat OpenShift AI user interface dashboard to help customers more easily access the latest hardware and software acceleration solutions.

● Leading global systems integrators are delivering managed services and support to drive generative AI workloads across hybrid cloud environments.

How does Red Hat's open source model foster collaboration and innovation among partners and the broader developer community?

Our goal at Red Hat is to build, connect and catalyze an open ecosystem of partners, so together we deliver customer-relevant solutions on Red Hat technologies. At the heart of this model are platforms like Red Hat Enterprise Linux, Red Hat OpenShift and Red Hat Ansible Automation Platform, which are all derived from open source community projects and ongoing upstream collaboration. Another great example is InstructLab – an open source project created by Red Hat and IBM for enhancing large language models (LLMs) used in generative artificial intelligence (gen AI) applications. This collective effort incorporates diverse perspectives to drive technological advancements, accelerating development and enhancing functionality.

Transparency is another cornerstone of Red Hat’s approach to build trust and foster collaboration among partners and customers, as well as open source contributors and developer communities. This openness allows for peer reviews that improve quality and security, while encouraging a wide range of contributors to engage in innovation.

Beyond our own platform development, the open source ethos is at the core of Red Hat’s partner ecosystem. As proven by the world of open source, problem solving gets a whole lot easier when we innovate together. This is what energizes us at Red Hat in working with a vibrant ecosystem. We roll up our sleeves with our partners, working upstream with others like Intel and NVIDIA to enable better technical outcomes, in order to build solutions that help customers do more with less. We take it on together.

What specific initiatives or programs does Red Hat offer to support partners in delivering AI-enabled solutions and services?

Partners are the first line of support for many of our customers, so it is critical that we set up the necessary pillars for partners to not only bring forward innovative capabilities with customers but also carry them through to the finish line and achieve business value. Red Hat offers a comprehensive suite of initiatives and programs designed to help deliver AI-enabled solutions for partners to drive business transformation.

a. Certification opportunities for partners - Red Hat OpenShift Certification continues to be a value-add for ISVs in attracting and servicing customers by providing automation at every level of the stack, from managing the infrastructure that make up the platform all the way to applications that are provided as a managed service.

Red Hat is continuing to invest in certification pathways for partners to serve customers at each stage of the hybrid cloud. For example, Red Hat enables partners to certify edge systems on Red Hat Enterprise Linux, offering customers greater confidence that partner edge systems have been thoroughly tested on Red Hat Enterprise Linux for use in edge scenarios. Dell, HPE, Lenovo, and OnLogic are a few partners who have already achieved this certification.

b. Enabling services through partners - More and more customers are not just looking to consume software, but also managed and professional services. Perhaps the customer doesn’t have the time or resources to manage it themselves, which is where managed services partners (MSPs) come in.

We are investing in the tools and training to better support MSPs and others in the commercial space through initiatives like Red Hat Partner Practice Accelerator, a specialized growth pathway for select partners with validated professional services delivery capabilities, as they bring much-needed services to customers navigating deployments in the hybrid cloud.

c. Helping partners strengthen skills through Red Hat Training - Partners can access extensive Red Hat Training courses at no additional cost to build critical skills in delivering open hybrid cloud solutions. In addition, Red Hat Partner Subscriptions, a no-cost subscription model that allows partners deeper access to the Red Hat open hybrid cloud portfolio, enable partners to more easily develop software solutions and POCs, test product offerings, and deepen technical skills with Red Hat products.

These initiatives and programs enable partners to harness the power of Red Hat open hybrid cloud platforms to extend critical capabilities for AI, edge computing, automation and more to deliver innovative solutions that help drive business transformation across hybrid cloud environments.

How is Red Hat's research and development focused on addressing emerging AI trends, such as Explainable AI or AI at the edge?

While Red Hat's research and development initiatives certainly aim to address emerging AI trends like explainable AI and AI at the edge, we are also capturing these emerging needs through our partnerships to advancing ethical and practical applications of artificial intelligence. By leveraging our open source principles and collaborating with industry leaders, Red Hat is shaping the future of AI in a way that emphasizes transparency, efficiency, and scalability.

As AI adoption grows, there is increasing demand for processing data closer to its source, reducing latency and improving performance. Red Hat has made significant progress in advancing AI at the edge, which involves deploying AI models on edge devices such as sensors, gateways, and IoT-enabled systems, through solutions like Red Hat Device Edge. This is especially prevalent in industries like manufacturing, where edge computing and AI are being used to break down barriers between IT and OT to drive more efficiency on the shop floor.

Furthermore, through collaborations with leaders like Intel, Red Hat is optimizing hybrid cloud environments to support edge computing. For example, Red Hat OpenShift AI is being used to deliver lightweight, containerized AI solutions that can operate seamlessly at the edge. This capability is critical for applications requiring real-time responses, such as autonomous vehicles, predictive maintenance, and IoT-based solutions.  

By enabling AI workloads to run efficiently on edge devices, Red Hat and our robust partner ecosystem are not only improving processing speeds but also enhancing resource efficiency. This is critical in industries such as manufacturing and telecommunications, where vast amounts of data are generated at the edge, and centralized cloud processing is not always feasible.  

Any final thoughts or advice for organizations looking to harness the power of AI and open source solutions for transformative enterprise solutions?

In today’s digital landscape, the convergence of AI and open source solutions is driving enterprise transformation. This synergy offers unparalleled opportunities for innovation, agility, and collaboration, enabling businesses to adapt and grow sustainably.

Open source platforms critical flexibility and transparency for developing scalable AI solutions. These platforms empower organizations to customize features, reduce costs, and avoid vendor lock-in. For instance, Red Hat OpenShift AI provides an integrated MLOps platform for managing the AI/ML lifecycle across hybrid cloud environments and the edge, designed to increase AI adoption and enhance trust in AI initiatives. In addition, Red Hat Enterprise Linux AI offers a foundation model platform to help organizations more consistently develop, test and run Granite family LLMs to power enterprise applications, with built-in InstructLab model alignment tools to provide a community-driven approach to model development through the InstructLab project.

Collaboration accelerates innovation. Red Hat’s open source ecosystem exemplifies how partnerships with industry leaders and communities foster cutting-edge AI solutions. This collaborative approach offers continuous refinement and relevance in evolving technological environments. Finally, upskilling is critical. As technology evolves, so must the workforce. Red Hat Training equips professionals with the skills needed to effectively implement AI and open source technologies, fostering a culture of learning and adaptability.

By integrating open source innovation, collaboration and continuous learning, enterprises can more easily navigate complexities and achieve sustained growth in the modern IT landscape.