Red Hat: a leader in driving sustainability efforts within the IT industry

Red Hat: a leader in driving sustainability efforts within the IT industry Red Hat's solutions for energy efficiency Supporting small language models (SLMs) for energy efficiency Business benefits for customers Partnership initiatives Conclusion Get started with AI for enterprise: A beginner’s guide About the author Dan Schnitzer More like this Blog post Blog post Blog post Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Red Hat makes it a strategic priority to offer energy-efficient products, addressing the growing demand of our customers for sustainable IT solutions. Our efforts are driven by minimizing the increase in energy consumption of AI, cloud computing, and IT infrastructure. Red Hat focuses on open source technologies designed to improve energy efficiency across IT environments. This includes: AI optimization : With Red Hat AI, you have access to Red Hat AI Inference Server to optimize model inference across the hybrid cloud for faster, cost-effective deployments. Powered by vLLM , the inference server maximizes GPU utilization and enables faster response times, thereby reducing the computational resources and energy required for AI workloads. Virtualization : Red Hat OpenShift Virtualization consolidates multiple virtual machines (VMs) onto fewer physical servers, directly translating to lower energy consumption and increased hardware utilization. System monitoring : Red Hat Enterprise Linux (RHEL) supports performance Co-Pilot (PCP), which provides detailed, real-time visibility into system performance and energy usage, enabling customers to identify and address inefficiencies. Power monitoring : Power monitoring for Red Hat OpenShift provides detailed insights into power consumption, improving adoption of energy-aware computing within cloud-native ecosystems. Intelligent automation : Red Hat Ansible Automation Platform boosts operational efficiency, reducing system down times, and intelligently optimizing resource utilization, which all contributes to a lower carbon footprint and enhanced energy efficiency. InstructLab is an open source project that enhances large language models (LLMs) used in generative AI (gen AI), upgrading an LLM with less human input and fewer resources than retraining. One of the key aspects of InstructLab is its focus on smaller, fine-tuned language models. This approach directly translates to improved energy efficiency compared to larger, more resource-intensive LLMs deployed by competitors.