The AI & Cloud-Native Infrastructure Blog
Stay updated with the latest news and insights on AI and cloud-native infrastructure through Rafay's highly active blog site
Experience What Composable AI Infrastructure Actually Looks Like — In Just Two Hours
The pressure to deliver on the promise of AI has never been greater. Enterprises must find ways to make effective use of their GPU infrastructure to meet the demands of AI/ML workloads and accelerate time-to-market. Yet, despite making significant investments… Read More
GPU PaaS™ (Platform-as-a-Service) for AI Inference at the Edge: Revolutionizing Multi-Cluster Environments
Enterprises are turning to AI/ML to solve new problems and simplify their operations, but running AI in the datacenter often compromises performance. Edge inference moves workloads closer to users, enabling low-latency experiences with fewer overheads, but it's traditionally cumbersome to… Read More
Democratizing GPU Access: How PaaS Self-Service Workflows Transform AI Development
A surprising pattern is emerging in enterprises today: End-users building AI applications have to wait months before they are granted access to multi-million dollar GPU infrastructure. The problem is not a new one. IT processes in most enterprises are a… Read More
Rafay and Netris: Partnering to speed up consumption and monetization for GPU Clouds
Rafay, a pioneer in delivering platform-as-a-service (PaaS) capabilities for self-service compute consumption, and Netris, a leader in networking Automation, Abstraction, and Multi-tenancy for AI & Cloud operators , are collaborating to help GPU Cloud Providers speed up consumption and monetization… Read More
Is Fine-Tuning or Prompt Engineering the Right Approach for AI?
While prompt engineering is a quick and cost-effective solution for general tasks, fine-tuning enables superior AI performance on proprietary data. We previously discussed how building a RAG-based chatbot for enterprise data paved the way for creating a comprehensive GenAI platform.… Read More
GPU PaaS™ Unleashed: Empowering Platform Teams to Drive Innovation
GPUs underpin cutting-edge AI, machine learning, and big data workloads. They also provide critical acceleration for simulation, video rendering, and streaming tasks. With modern enterprises likely to be investing in some or all of these fields, easy access to GPU… Read More
Optimizing AI Workloads for Multi-Cloud Environments with Rafay and GPU PaaS
Rafay’s platform enables you build a GPU PaaS for AI workloads so you can confidently operate machine learning models, generative AI, and neural networks at scale. It orchestrates your hybrid and multi-cloud computing resources, improves operational flexibility, and includes precise… Read More
Operationalizing AI: Solutions to Machine Learning Workflow Automation Challenges
Machine learning (ML) has emerged as a transformative force, enabling organizations to derive critical insights, enhance customer experiences, and make data-driven predictions. However, operationalizing machine learning workflows presents significant challenges, especially for enterprises with complex, cloud-based infrastructures. Machine learning workflow… Read More
Achieving Optimal AI Performance with Tuning-as-a-Service
Tuning-as-a-Service (another TaaS but not to be confused with Training-as-a-service) is a cloud-based solution that optimizes AI models by automating the adjustment of hyperparameters to enhance model accuracy, efficiency, and overall performance. By leveraging advanced algorithms and scalable cloud resources,… Read More
Optimizing AI Deployments with Training-as-a-Service Platforms
As artificial intelligence continues to reshape industries, the demand for efficient, scalable training solutions has surged. Training-as-a-Service (TaaS) platforms are emerging as essential tools for developers, data architects, and platform engineering teams working in AI model development. By offering cloud-based,… Read More
Unlocking the Potential of MLOps as a Service: Streamlining AI and ML Pipelines
A New Era in AI and ML Operations Managing ML models effectively is more crucial than ever in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML). From healthcare to finance and retail, industries are leveraging machine… Read More
Training as a Service: Empowering AI Teams with Managed Model Training Solutions
Artificial intelligence is rapidly evolving, and the ability to efficiently train AI models is essential for competitive advantage. As applications scale, organizations face growing complexities around model training— from managing extensive datasets to securing infrastructure that supports continuous, high-performance training… Read More