Rafay Systems enhances PaaS with GPU support for AI projects

Rafay Systems has introduced new capabilities to its enterprise Platform-as-a-Service (PaaS) aimed at addressing challenges faced by developers and data scientists working on artificial intelligence (AI) projects. The company's PaaS now includes support for GPU-based workloads, providing enterprise-grade guardrails for these specialised compute resources. This development is designed to accelerate AI initiatives within enterprises by making compute resources more readily accessible.

Alongside GPU support, Rafay Systems has launched an AI Suite featuring standards-based pipelines for machine learning operations (MLOps) and large language model operations (LLMOps). This suite is intended to simplify the development and deployment of AI applications for enterprise platform teams, reducing the complexities and costs associated with AI workloads.

Developing AI applications requires access to specialized hardware like GPUs, which are costly and difficult to manage. Rafay's new offerings aim to mitigate these complications. The AI Suite is structured to provide pre-configured workspaces equipped with essential AI tools, including Jupyter Notebooks and Virtual Studio Code (VSCode) integrations. Additionally, the suite offers GPU matchmaking, virtualisation, and enhanced cost management capabilities, allowing enterprises to optimise resource use and control costs effectively.

Haseeb Budhani, Co-Founder and CEO of Rafay Systems highlighted the significance of these advancements. "I am immensely proud of Team Rafay for having extended our enterprise PaaS offering to now support GPU-based workloads in data centres and all major public clouds," he said. Budhani noted that these enhancements make Rafay an essential partner for enterprises and GPU cloud operators aiming to accelerate modern application delivery.

Rafay's new capabilities are expected to address critical industry issues, such as environment standardisation, self-service compute consumption, secure multi-tenant environments, cost optimization, zero-trust connectivity enforcement, and auditability. These features are crucial as more businesses integrate AI into their operations, facing regulatory and cost constraints that can hamper innovation.

Rafay's latest offering is complemented by its collaboration with global partners, including NTT DATA. This partnership aims to deploy the new GPU support and AI Suite to a broader market, underscoring both companies' commitment to providing cutting-edge AI solutions. Mike Jones, Vice President of Partners and Alliances at NTT DATA UK & I, expressed enthusiasm for the expanded collaboration, emphasizing its role in empowering businesses worldwide.

For developers and data scientists within enterprises, Rafay's enhanced platform promises a more seamless and efficient experience. The newly introduced self-service capabilities allow users to request GPU-enabled workspaces easily, while AI-optimized workspaces and GPU matchmaking improve resource efficiency. Additionally, GPU virtualisation features aim to lower the overall costs of running GPU hardware, making advanced AI projects more accessible to a wider range of users.