Avesha

🌟 Boost Your AI Workloads with Smarter Orchestration by Avesha EGS!🌟 Is your team struggling with: 🚫 Inefficient GPU utilization 🚫 Lack of visibility across workloads 🚫 High costs due to resource overprovisioning Avesha’s #Elastic #GPU #Service (EGS) transforms these challenges into opportunities with: ✅ Real-Time Unified Observability: Monitor GPU status, costs, and usage anomalies, across clusters in one intuitive dashboard. ✅ Automated GPU Allocation: Eliminate manual ticketing and delays with dynamic, policy-driven automation. ✅ Multi-GPU Orchestration: Optimize parallel execution and cost efficiency with fractional and spot GPU allocation. ✅ Predictive Allocation: Utilize AI to forecast resource needs and minimize wastage, ensuring maximum ROI. Whether it's #training #LLMs or #finetuning or #real-#time #inferencing, EGS delivers agility, scalability, and cost savings for cutting-edge workloads. #GPUAndCPUOptimization #AveshaEGS

🚀 AI Workloads Made Smarter for 2025 Tackle AI’s oughest challenges with EGS: ✔️ Dynamic CPU & GPU allocation ✔️ Reduced operational costs ✔️ Seamless multi-cluster ML execution  #elasticgpuservice #egs  Cynthia Hsieh

Raj Nair and I wrote a vision paper on 'Optimize Your ML and Data Workloads' - exploring how to make ML infrastructure work smarter, not harder. We dive into ways to optimize GPU/CPU resource allocation for ML workloads, introduce the concept of Elastic GPU Service (EGS), and propose a new KPI called the Wastage Ratio to measure infrastructure efficiency. Check it out.

We're excited to share this latest paper from Cheng Wu and Raj Nair https://lnkd.in/gqfGzeRp on optimizing ML and data workloads using Elastic GPU Service (EGS). We're addressing key challenges in GPU/CPU resource management with a solution that has shown up to 44% improved throughput. The future of ML infrastructure lies in intelligent, dynamic resource allocation that adapts to your workload needs in real-time. #MLOps #AI #ResourceOptimization

🎄✨ Happy Holidays from Avesha! ✨🎄 As we celebrate this festive season, we’re happy to reflect on a year of innovation and achievements: 🎉 Launched #Elastic #GPU #Service (#EGS) – The smart and efficient GPU orchestration platform that optimizes costs and boosts AI performance. 🏆 Featured as a #Gartner #Cool #Vendor #2024, highlighting our commitment to transformative technology. 💡 Helped customers with solutions like #KubeSlice and #Smart #Scaler, driving performance and cost efficiency across multicloud environments. Thank you to our #customers, #partners, and #community for being part of our journey. Wish you an exciting 2025! #HappyHolidays #Avesha #Innovation #EGS #GPUOrchestration #KubeSlice #SmartScaler

Aligned with Gartner's insights on augmenting #DevOps with #AI, Avesha's Elastic GPU Service (EGS) product optimizes GPU usage through dynamic resource allocation, real-time observability, and intelligent optimization. It’s the perfect tool to balance performance, cost, and sustainability in AI operations. Learn more: https://lnkd.in/gEQ6Xini https://lnkd.in/grDTFHJs #AI #DevOps #PlatformEngineering #GPUOptimization #Sustainability

🌟 Introducing the Avesha Elastic GPU Service (EGS) SDK! 🌟 Designed to help developers harness the full potential of their GPU infrastructure for AI/ML workloads. With the Python SDK, you can streamline GPU resource management and seamlessly integrate GPUaaS capabilities into your applications. 🔧 Key Features of the EGS SDK: ⭐ Simplified Installation: Get started quickly with a streamlined setup process. Learn More: https://lnkd.in/gUpbJ653 ⭐ Team Workspaces: Manage and organize your GPU resources efficiently. Explore Workspaces: https://lnkd.in/g5Ezx8iN  ⭐ GPU Inventory Insights: Gain visibility into your GPU inventory and utilization. Check Inventory: https://lnkd.in/g74AiGfw ⭐ GPU Performance Metrics: Leverage SDK capabilities for optimal GPU scaling and resource allocation. Access metrics like temperature, power, memory usage, and more. Explore Performance Metrics: https://lnkd.in/g4UUNHrN 💡 Whether you're training large LLMs, using RAG pipelines, fine-tuning, running inference, or handling real-time data processing, the EGS SDK equips you with the tools to maximize GPU utilization while reducing costs. 📥 Ready to revolutionize your GPU workflow? Start exploring the SDK today and take your AI/ML workloads to the next level. 👉 Get Started: https://lnkd.in/gUpbJ653

Join us at Amazon Web Services (AWS) re:Invent https://lnkd.in/ghKya-BR to see how Avesha, a Gartner #Cool #Vendor and Cloud Native Computing Foundation (CNCF) #Sandbox project with #KubeSlice, is advancing innovations in GPU and cloud orchestration! 🌟 Meet Raj Nair, Bruce Lampert and Geoff Lunsford on-site and explore: --#Smart #Karpenter: AI-driven autoscaling to optimize performance and slash cloud costs by up to 70%. -#Elastic #GPU #Service(#EGS): An AI-powered GPU optimization solution with dynamic allocation, ability to create spot instances, fractional GPU sharing, MLOps integrations, and real-time observability for maximum efficiency and throughput.

KubeSlice: Migrate Kubernetes Services With Confidence! | Project Lightning Talk in #KubeCon 2025 by Prabhu Navali, VP of Product Architecture. #CNCF #KubeSlice #NoCode #Migration #MultiCloud Stuck with private endpoints and no public access for multi-cloud migration? KubeSlice simplifies secure service connectivity across clusters—no service mesh, no hassle. Watch this.

We're excited to announce G&L Systemhaus as a #KubeSlice customer! https://lnkd.in/g_3ap2gG G&L’s on-premises data centers handle live encoding, while Akamai Technologies’ #Linode cloud manages media metadata as the CMS and control plane. The hybrid cloud communication between services is enabled by #KubeSlice multi-cluster connectivity and workload management. Thanks to Alexander Leschinsky and his team! Avesha team Raj Nair Bruce Lampert Dheeraj Ravula