Showing 4 open source projects for "big linux"

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  • 1
    Volcano

    Volcano

    A Cloud Native Batch System (Project under CNCF)

    Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with. Volcano builds upon a decade and a half of experience running a wide variety of...
    Downloads: 148 This Week
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  • 2
    CubeFS

    CubeFS

    cloud-native file store

    CubeFS is a new generation cloud-native storage that supports access protocols such as S3, HDFS, and POSIX. It is widely applicable in various scenarios such as big data, AI/LLMs, container platforms, separation of storage and computing for databases and middleware, data sharing and protection, etc. Compatible with various access protocols such as S3, POSIX, HDFS, etc., and the access between protocols can be interoperable. Support replicas and erasure coding engines, users can choose...
    Downloads: 0 This Week
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  • 3
    LOG HOUSE

    LOG HOUSE

    Ready to use log management solution for Kubernetes storing data

    Ready to use log management solution for Kubernetes storing data in ClickHouse and providing web UI. Ready to use log management solution for Kubernetes. Efficiently store big amounts of your logs (in ClickHouse database), process them using a simple query language and monitor them online through web UI. Easy and quick to deploy in an already functioning Kubernetes cluster. The status is alpha. However, we (Flant) use it in our production Kubernetes deployments since September 2017. Data...
    Downloads: 0 This Week
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  • 4
    CRFS

    CRFS

    CRFS: Container Registry Filesystem

    CRFS is a user-space filesystem that mounts container images directly from remote registries, exposing them as ordinary directories without a full “pull” step. Instead of downloading entire layers upfront, it fetches file ranges on demand and maintains a content-addressed cache, yielding fast startup and lower bandwidth for large images. The system speaks registry protocols and understands layered image formats, resolving whiteouts and overlays so the mounted view matches what a container...
    Downloads: 0 This Week
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