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  • pdf文档 Handle Edge Cloud Network with KubeBus

    Handle Edge Cloud Network with KubeBus Yulin Sun, yulin.sun@huawei.com Seattle Cloud Lab, Huawei R&D USA, Bellevue WA Agenda • Edge sample user scenarios • Edge network characteristics • Related work Sample Scenarios HiLens Campus surveillance Huawei Hilens Edge network characteristics • Edge Nodes running at private network • Connect to Cloud behind NAT gateway • Mightn’t have direct connection Cluster Management • There is cloud cluster, edge cluster, i.e. multiple nodes running in private network • Edge nodes, Edge cluster and cloud cluster needs acting as a single cluster Edge Node Management
    0 码力 | 10 页 | 1.17 MB | 1 年前
    3
  • pdf文档 Handle Edge Cloud Network with KubeBus

    Handle Edge Cloud Network with KubeBus Yulin Sun, yulin.sun@huawei.com Seattle Cloud Lab, Huawei R&D USA, Bellevue WA Agenda • Edge sample user scenarios • Edge network characteristics • Related work Sample Scenarios HiLens Campus surveillance Huawei Hilens Edge network characteristics • Edge Nodes running at private network • Connect to Cloud behind NAT gateway • Mightn’t have direct connection Cluster Management • There is cloud cluster, edge cluster, i.e. multiple nodes running in private network • Edge nodes, Edge cluster and cloud cluster needs acting as a single cluster Edge Node Management
    0 码力 | 10 页 | 1.17 MB | 1 年前
    3
  • pdf文档 Identity Aware Threat Detection and Network Monitoring by using eBPF

    Identity Aware Threat Detection and Network Monitoring by using eBPF Natalia Reka Ivanko, Isovalent October 28, 2020 ● ● ○ ● ○ ○ ○ ○ ● ● ● ● ● ● ● ● ○ ● ○ ○ ○ ● ● ● ○ ● ○ ○ ● ●
    0 码力 | 7 页 | 1.35 MB | 1 年前
    3
  • pdf文档 Container Portfolio at VMware

    ©2018 VMware, Inc. Container Portfolio at VMware �� VMware������� 2 ©2018 VMware, Inc. Application Velocity and Customization Drive Competitive Advantage Software Customization Innovation/Disruption Innovation/Disruption 3 ©2018 VMware, Inc. Container Technology Key Enabler for Modern Application Development Fast Create Environments Rapidly Portable Moves from Dev/Test to Production Consistently Light Both Worlds vSphere Integrated Containers Docker compatible interface Container management portal Enterprise-class container registry Familiarity of vSphere No new tooling or technologies Full enterprise-grade
    0 码力 | 26 页 | 6.62 MB | 1 年前
    3
  • pdf文档 Kubernetes & YARN: a hybrid container cloud

    ������ �� ��� ���� �������� �� ����������� Scheduling Isolation Efficient placement of service container and tasks When placed together, don’t affect each other Resource contention ���� ������ ���������� state with control loops YARN Focus on scheduling jobs ���������� ���� Kubernetes Container centric – bottom up. Container is the primitive. Other primitives such as replicaset, deployment are built around application -> container request ������������� kubernetes Based on api-server watch mechanism Everything stored in etcd YARN Based on RPC Only application-level metadata persisted. Container data is not
    0 码力 | 42 页 | 25.48 MB | 1 年前
    3
  • pdf文档 OpenShift Container Platform 4.14 Operator

    OpenShift Container Platform 4.14 Operator 在 OpenShift Container Platform 中使用 Operator Last Updated: 2024-02-23 OpenShift Container Platform 4.14 Operator 在 OpenShift Container Platform 中使用 Operator All other trademarks are the property of their respective owners. 摘要 摘要 本文档提供有关在 OpenShift Container Platform 中使用 Operator 的信息。文中为集群管理员提供 了 Operator 的安装和管理说明,为开发人员提供了如何通过所安装的 Operator 创建应用程序的信 息。另外还提供了一些使用 OPERATOR 6.11. CLUSTER MACHINE APPROVER OPERATOR 6.12. CLUSTER MONITORING OPERATOR 6.13. CLUSTER NETWORK OPERATOR 6.14. CLUSTER SAMPLES OPERATOR 6.15. CLUSTER STORAGE OPERATOR 6.16. CLUSTER VERSION OPERATOR
    0 码力 | 423 页 | 4.26 MB | 1 年前
    3
  • pdf文档 OpenShift Container Platform 4.12 Serverless

    OpenShift Container Platform 4.12 Serverless OpenShift Serverless 的安装、使用与发行注记 Last Updated: 2024-02-16 OpenShift Container Platform 4.12 Serverless OpenShift Serverless 的安装、使用与发行注记 法律通告 法律通告 Copyright All other trademarks are the property of their respective owners. 摘要 摘要 本文档提供有关如何在 OpenShift Container Platform 中使用 OpenShift Serverless 的信息. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 目 目录 录 1 OpenShift Container Platform 4.12 Serverless 2 第 1 章 关于 SERVERLESS 1.1. {SERVERLESSPRODUCTNAME} 概述 OpenShift Serverless 提供 Kubernetes 原生构建块,供开发人员在 OpenShift Container Platform 中创 建和部署无服务
    0 码力 | 7 页 | 73.32 KB | 1 年前
    3
  • pdf文档 OpenShift Container Platform 4.8 Service Mesh

    OpenShift Container Platform 4.8 Service Mesh Service Mesh 的安装、使用和发行注记信息 Last Updated: 2023-04-07 OpenShift Container Platform 4.8 Service Mesh Service Mesh 的安装、使用和发行注记信息 法律通告 法律通告 Copyright © 2023 All other trademarks are the property of their respective owners. 摘要 摘要 本文档提供了有关如何在 OpenShift Container Platform 中使用 Service Mesh 的信息. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 目录 录 1 OpenShift Container Platform 4.8 Service Mesh 2 第 1 章 SERVICE MESH 2.X 1.1. 关于 OPENSHIFT SERVICE MESH 注意 注意 因为 Red Hat OpenShift Service Mesh 的发行节奏与 OpenShift Container Platform 不 同,且 Red
    0 码力 | 344 页 | 3.04 MB | 1 年前
    3
  • pdf文档 Apache Karaf Container 4.x - Documentation

    Apache Karaf Container 4.x - Documentation Apache Software Foundation Apache Karaf Container 4.x - Documentation 1. Overview 2. Quick Start 2.1. Prerequisites 2.2. Start the server 2.3. Shell console 11. Create container 4.15.12. Listing containers 4.15.13. Provision Docker container 4.15.14. Start container 4.15.15. Stop container 4.15.16. Restart container 4.15.17. Delete container 4.15.18. Pause container 4.15.19. Unpause container 4.15.20. Kill container 4.15.21. Rename container 4.15.22. Logs 4.15.23. Top 4.16. OBR 4.16.1. Features OBR resolver 4.16.2. Commands 4.16.3. obr:start
    0 码力 | 370 页 | 1.03 MB | 1 年前
    3
  • pdf文档 PyTorch Release Notes

    ...................................................................... 1 Chapter 2. Pulling A Container................................................................................................ Cython. Automatic differentiation is done with a tape-based system at both a functional and neural network layer level. This functionality brings a high level of flexibility and speed as a deep learning framework and provides accelerated NumPy-like functionality. PyTorch also includes standard defined neural network layers, deep learning optimizers, data loading utilities, and multi-gpu, and multi-node support.
    0 码力 | 365 页 | 2.94 MB | 1 年前
    3
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