parallelism Job Spec activeDeadlineSeconds completions Pod Template Expected maximum number of parallel build tasks Expected number of completed build tasks The timeout of the running build tasks, default: Volume PVC Task Template Task created from template Tasks in same stage can run sequentially or in parallel Logging, Monitoring, Autoscaling, High Availability Kubernetes Cluster Node Node Node Node Job code repository sidecar build task lifecycle - preStop - volumes storage config using secret Query artifact data DevOps Operator Manage the Job CI/CD Examples - Human/Manual Task system email

for a single experiment • Autoscaling capabilities: Pay for what you use, scale down when idle • Parallel training instead of sequential: huge time saver for large trainings Kubeflow • Machine Learning • Seldon Demo: Run TensorFlow Training with Kubeflow Demo: Scale and Test Experiments in Parallel using Kubernetes, TFJob, and Helm • Spin up pods for each variation of hyperparameters • One

A Kubernetes-based Scheduler Framework》 The IEEE ISPA 2018 (16th IEEE International Symposium on Parallel and Distributed Processing with Applications) 能力扩展：GPU支持 资源-访问代价树 四类通信方式分类中，通信开销最大的是SOC，其次是PXB，再次是PHB，PIX通信方式 发表论文：《GaiaGPU: Sharing GPUs in Container Clouds》 The IEEE ISPA 2018 (16th IEEE International Symposium on Parallel and Distributed Processing with Applications) 生态 Next Tencent Kubernetes Engine

Management（OrderedReady的Pod管理） OrderedReady Pod管理是StatefulSet的默认值。 它实现了上述 ⾏为。 Parallel Pod Management（并⾏ Pod管理） Parallel Pod管理告诉StatefulSet Controller 并⾏启动或终⽌所有Pod，并且不要等待Pod在启动或终⽌另⼀个Pod之 前变为“Running”和“Ready”或完全终⽌。 loadbalancer 获得 这些功能。随着时间的推移，我们计划将跨平台适⽤的负载均衡模式提取到Ingress资源中。 另外，尽管健康检查不直接通过Ingress暴露，但是在Kubernetes中存在parallel（并⾏）的概念，例如 readiness probes ，可让您实现相同的最终结果。请查看特定Controller的⽂档，以了解他们如何处理健康检查（ nginx 、 GCE ）。 Updating

& Priority Policy. Ø NodeResourceUsage Annotator scores node periodically. Ø Dynamic-Scheduler query node score directly from node to make decisions during predicate and priority stage. Dynamic Scheduler

creation spark-submit \ --master k8s://https://192.168.45.93:5443 \ --deploy-mode cluster \ --name query \ --class com.databricks.spark.sql.perf.BenchmarkQuery \ --conf spark.kubernetes.volcano.enable=true

Warehouse Factory Branch Augmented Services On-Prem Cloud Cloud Storage Cloud ML Big Query Jurisdictional / PII Europe Secure records US IT policy Interconnect Connect Peering + VPN