Experimental News Clipping Site

Tag: Google Kubernetes

  • Cloud Blog: Co-op mode: New partners driving the future of gaming with AI

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/gaming/co-op-mode-the-ai-partners-driving-the-the-future-of-gaming/ Source: Cloud Blog Title: Co-op mode: New partners driving the future of gaming with AI Feedly Summary: Leaders in the games industry are using Google Cloud’s AI to drive unprecedented advancements in game development, including smarter, faster, and more immersive gaming experiences. And just like any successful game studio is the work…

  • Cloud Blog: Meet Kubernetes History Inspector, a log visualization tool for Kubernetes clusters

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-history-inspector-visualizes-cluster-logs/ Source: Cloud Blog Title: Meet Kubernetes History Inspector, a log visualization tool for Kubernetes clusters Feedly Summary: Kubernetes, the container orchestration platform, is inherently a complex, distributed system. While it provides resilience and scalability, it can also introduce operational complexities, particularly when troubleshooting. Even with Kubernetes’ self-healing capabilities, identifying the root cause…

  • Cloud Blog: Guide: Our top four AI Hypercomputer use cases, reference architectures and tutorials

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/ai-hypercomputer-4-use-cases-tutorials-and-guides/ Source: Cloud Blog Title: Guide: Our top four AI Hypercomputer use cases, reference architectures and tutorials Feedly Summary: AI Hypercomputer is a fully integrated supercomputing architecture for AI workloads – and it’s easier to use than you think. In this blog, we break down four common use cases, including reference architectures and…

  • Cloud Blog: Optimizing image generation pipelines on Google Cloud: A practical guide

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/guide-to-optimizing-image-generation-pipelines/ Source: Cloud Blog Title: Optimizing image generation pipelines on Google Cloud: A practical guide Feedly Summary: Generative AI diffusion models such as Stable Diffusion and Flux produce stunning visuals, empowering creators across various verticals with impressive image generation capabilities. However, generating high-quality images through sophisticated pipelines can be computationally demanding, even with…

  • Cloud Blog: An SRE’s guide to optimizing ML systems with MLOps pipelines

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/devops-sre/applying-sre-principles-to-your-mlops-pipelines/ Source: Cloud Blog Title: An SRE’s guide to optimizing ML systems with MLOps pipelines Feedly Summary: Picture this: you’re an Site Reliability Engineer (SRE) responsible for the systems that power your company’s machine learning (ML) services. What do you do to ensure you have a reliable ML service, how do you know…

  • Cloud Blog: Introducing A4X VMs powered by NVIDIA GB200 — now in preview

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/new-a4x-vms-powered-by-nvidia-gb200-gpus/ Source: Cloud Blog Title: Introducing A4X VMs powered by NVIDIA GB200 — now in preview Feedly Summary: The next frontier of AI is reasoning models that think critically and learn during inference to solve complex problems. To train and serve this new class of models, you need infrastructure with the performance and…

  • Cloud Blog: With MultiKueue, grab GPUs for your GKE cluster, wherever they may be

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/using-multikueue-to-provision-global-gpu-resources/ Source: Cloud Blog Title: With MultiKueue, grab GPUs for your GKE cluster, wherever they may be Feedly Summary: Artificial Intelligence (AI) and large language models (LLMs) are experiencing explosive growth, powering applications from machine translation to artistic creation. These technologies rely on intensive computations that require specialized hardware resources, like GPUs. But…

  • Cloud Blog: Networking support for AI workloads

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/networking/cross-cloud-network-solutions-support-for-ai-workloads/ Source: Cloud Blog Title: Networking support for AI workloads Feedly Summary: At Google Cloud, we strive to make it easy to deploy AI models onto our infrastructure. In this blog we explore how the Cross-Cloud Network solution supports your AI workloads. Managed and Unmanaged AI options Google Cloud provides both managed (Vertex…