MLOps

  1. SageMaker AI Spaces on EKS brings IDEs into Kubernetes clusters

    SageMaker AI Spaces on EKS brings IDEs into Kubernetes clusters

    AWS puts managed ML workspaces inside EKS clusters AWS has detailed how its SageMaker AI Spaces add-on can run managed JupyterLab and Code Editor environments directly on Amazon EKS. The approach targets machine learning teams that already operate Kubernetes clusters for training, storage and...
  2. Google Vertex AI

    Google Vertex AI

    Overview Google Vertex AI is a managed cloud platform for building, training, evaluating, deploying and operating machine-learning and generative AI applications. It offers Google and partner models with integrated MLOps and agent tooling, but service selection, regional availability, quotas and...
  3. Anyscale

    Anyscale

    Overview Anyscale is a managed platform from the creators of Ray for developing, scaling and operating distributed AI and machine-learning workloads. It reduces cluster operations and adds observability, but compute cost and Ray architecture still require engineering discipline. Best for ML and...
  4. Hugging Face

    Hugging Face

    Overview Hugging Face is an AI development platform for discovering, sharing, evaluating and deploying models, datasets and applications. Its Hub, open-source libraries, Spaces and inference services support a wide range of workflows, but licensing, model quality, security and infrastructure...
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