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Results 201 - 205 of 205 for workload (0.22 sec)

  1. CHANGELOG/CHANGELOG-1.5.md

      - [beta] StatefulSets allow workloads that require persistent identity or per-instance storage to be created and managed on Kubernetes. ([docs](http://kubernetes.io/docs/concepts/abstractions/controllers/statefulsets/)) ([kubernetes/features#137](https://github.com/kubernetes/enhancements/issues/137))...
    Registered: Fri Nov 01 09:05:11 UTC 2024
    - Last Modified: Thu Dec 24 02:28:26 UTC 2020
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  2. CHANGELOG/CHANGELOG-1.31.md

    - Added `/sys/devices/virtual/powercap` to default masked paths. It avoids the potential security risk that the ability to read these files may offer a power-based sidechannel attack against any workloads running on the same kernel. ([#125970](https://github.com/kubernetes/kubernetes/pull/125970), [@carlory](https://github.com/carlory))
    Registered: Fri Nov 01 09:05:11 UTC 2024
    - Last Modified: Wed Oct 23 12:18:32 UTC 2024
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  3. CHANGELOG/CHANGELOG-1.30.md

    ### Bug or Regression
    
    - Add `/sys/devices/virtual/powercap` to default masked paths. It avoids the potential security risk that the ability to read these files may offer a power-based sidechannel attack against any workloads running on the same kernel. ([#125970](https://github.com/kubernetes/kubernetes/pull/125970), [@carlory](https://github.com/carlory)) [SIG Node]
    - Fix a bug that Pods could stuck in the unschedulable pod pool 
    Registered: Fri Nov 01 09:05:11 UTC 2024
    - Last Modified: Wed Oct 23 04:40:14 UTC 2024
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  4. CHANGELOG/CHANGELOG-1.11.md

        * Default value for expendable pod priority cutoff in GCP deployment of Cluster Autoscaler changed from 0 to -10.
        * action required: users deploying workloads with priority lower than 0 may want to use priority lower than -10 to avoid triggering scale-up.
    
    ### Other notable changes
    
    Registered: Fri Nov 01 09:05:11 UTC 2024
    - Last Modified: Thu Feb 06 06:04:15 UTC 2020
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  5. RELEASE.md

    ## Major Features and Improvements
    
    *   Support for Python3.9 has been added.
    *   `tf.data`:
        *   `tf.data` service now supports strict round-robin reads, which is useful
            for synchronous training workloads where example sizes vary. With strict
            round robin reads, users can guarantee that consumers get similar-sized
            examples in the same step.
    Registered: Tue Nov 05 12:39:12 UTC 2024
    - Last Modified: Tue Oct 22 14:33:53 UTC 2024
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