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2019-12-10 23:05:30 +08:00
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content/en/blog/_posts/2018-05-04-Announcing-Kubeflow-0-1.md
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@@ -75,16 +75,16 @@ Within just a few commands, data scientists and software engineers can now creat
# Community Contributions # Community Contributions
It’d be impossible to have gotten where we are without enormous help from everyone in the community. Some specific contributions that we want to highlight include: It’d be impossible to have gotten where we are without enormous help from everyone in the community. Some specific contributions that we want to highlight include:
* [Argo](https://github.com/kubeflow/kubeflow/tree/master/kubeflow/argo) for managing ML workflows * [Argo](https://github.com/kubeflow/kubeflow/tree/v0.7.0/kubeflow/argo) for managing ML workflows
* [Caffe2 Operator](https://github.com/kubeflow/caffe2-operator) for running Caffe2 jobs * [Caffe2 Operator](https://github.com/kubeflow/caffe2-operator) for running Caffe2 jobs
* [Horovod & OpenMPI](https://github.com/kubeflow/kubeflow/tree/master/components/openmpi-controller) for improved distributed training performance of TensorFlow * [Horovod & OpenMPI](https://github.com/kubeflow/kubeflow/tree/master/components/openmpi-controller) for improved distributed training performance of TensorFlow
* [Identity Aware Proxy](https://github.com/kubeflow/kubeflow/blob/master/docs/gke/iap_request.py), which enables using security your services with identities, rather than VPNs and Firewalls * [Identity Aware Proxy](https://github.com/kubeflow/kubeflow/blob/master/docs/gke/iap_request.py), which enables using security your services with identities, rather than VPNs and Firewalls
* [Katib](https://github.com/kubeflow/katib) for hyperparameter tuning * [Katib](https://github.com/kubeflow/katib) for hyperparameter tuning
* [Kubernetes volume controller](https://github.com/kubeflow/experimental-kvc) which provides basic volume and data management using volumes and volume sources in a Kubernetes cluster. * [Kubernetes volume controller](https://github.com/kubeflow/experimental-kvc) which provides basic volume and data management using volumes and volume sources in a Kubernetes cluster.
* [Kubebench](https://github.com/kubeflow/kubebench) for benchmarking of HW and ML stacks * [Kubebench](https://github.com/kubeflow/kubebench) for benchmarking of HW and ML stacks
* [Pachyderm](https://github.com/kubeflow/kubeflow/tree/master/kubeflow/pachyderm) for managing complex data pipelines * [Pachyderm](https://github.com/kubeflow/kubeflow/tree/v0.7.0/kubeflow/pachyderm) for managing complex data pipelines
* [PyTorch operator](https://github.com/kubeflow/pytorch-operator) for running PyTorch jobs * [PyTorch operator](https://github.com/kubeflow/pytorch-operator) for running PyTorch jobs
* [Seldon Core](https://github.com/kubeflow/kubeflow/tree/master/kubeflow/seldon) for running complex model deployments and non-TensorFlow serving * [Seldon Core](https://github.com/kubeflow/kubeflow/tree/v0.7.0/kubeflow/seldon) for running complex model deployments and non-TensorFlow serving
It’s difficult to overstate how much the community has helped bring all these projects (and more) to fruition. Just a few of the contributing companies include: Alibaba Cloud, Ant Financial, Caicloud, Canonical, Cisco, Datawire, Dell, GitHub, Google, Heptio, Huawei, Intel, Microsoft, Momenta, One Convergence, Pachyderm, Project Jupyter, Red Hat, Seldon, Uber and Weaveworks. It’s difficult to overstate how much the community has helped bring all these projects (and more) to fruition. Just a few of the contributing companies include: Alibaba Cloud, Ant Financial, Caicloud, Canonical, Cisco, Datawire, Dell, GitHub, Google, Heptio, Huawei, Intel, Microsoft, Momenta, One Convergence, Pachyderm, Project Jupyter, Red Hat, Seldon, Uber and Weaveworks.
@@ -93,7 +93,7 @@ It’s difficult to overstate how much the community has helped bring all these
If you’d like to try out Kubeflow, we have a number of options for you: If you’d like to try out Kubeflow, we have a number of options for you:
1. You can use sample walkthroughs hosted on [Katacoda](https://www.katacoda.com/kubeflow) 1. You can use sample walkthroughs hosted on [Katacoda](https://www.katacoda.com/kubeflow)
2. You can follow a guided tutorial with existing models from the [examples repository](https://github.com/kubeflow/examples). These include the [GitHub Issue Summarization](https://github.com/kubeflow/examples/tree/master/github_issue_summarization), [MNIST](https://github.com/kubeflow/examples/tree/master/mnist) and [Reinforcement Learning with Agents](https://github.com/kubeflow/examples/tree/master/agents). 2. You can follow a guided tutorial with existing models from the [examples repository](https://github.com/kubeflow/examples). These include the [GitHub Issue Summarization](https://github.com/kubeflow/examples/tree/master/github_issue_summarization), [MNIST](https://github.com/kubeflow/examples/tree/master/mnist) and [Reinforcement Learning with Agents](https://github.com/kubeflow/examples/tree/v0.5.1/agents).
3. You can start a cluster on your own and try your own model. Any Kubernetes conformant cluster will support Kubeflow including those from contributors [Caicloud](https://www.prnewswire.com/news-releases/caicloud-releases-its-kubernetes-based-cluster-as-a-service-product-claas-20-and-the-first-tensorflow-as-a-service-taas-11-while-closing-6m-series-a-funding-300418071.html), [Canonical](https://jujucharms.com/canonical-kubernetes/), [Google](https://cloud.google.com/kubernetes-engine/docs/how-to/creating-a-container-cluster), [Heptio](https://heptio.com/products/kubernetes-subscription/), [Mesosphere](https://github.com/mesosphere/dcos-kubernetes-quickstart), [Microsoft](https://docs.microsoft.com/en-us/azure/aks/kubernetes-walkthrough), [IBM](https://cloud.ibm.com/docs/containers?topic=containers-cs_cluster_tutorial#cs_cluster_tutorial), [Red Hat/Openshift ](https://docs.openshift.com/container-platform/3.3/install_config/install/quick_install.html#install-config-install-quick-install)and [Weaveworks](https://www.weave.works/product/cloud/). 3. You can start a cluster on your own and try your own model. Any Kubernetes conformant cluster will support Kubeflow including those from contributors [Caicloud](https://www.prnewswire.com/news-releases/caicloud-releases-its-kubernetes-based-cluster-as-a-service-product-claas-20-and-the-first-tensorflow-as-a-service-taas-11-while-closing-6m-series-a-funding-300418071.html), [Canonical](https://jujucharms.com/canonical-kubernetes/), [Google](https://cloud.google.com/kubernetes-engine/docs/how-to/creating-a-container-cluster), [Heptio](https://heptio.com/products/kubernetes-subscription/), [Mesosphere](https://github.com/mesosphere/dcos-kubernetes-quickstart), [Microsoft](https://docs.microsoft.com/en-us/azure/aks/kubernetes-walkthrough), [IBM](https://cloud.ibm.com/docs/containers?topic=containers-cs_cluster_tutorial#cs_cluster_tutorial), [Red Hat/Openshift ](https://docs.openshift.com/container-platform/3.3/install_config/install/quick_install.html#install-config-install-quick-install)and [Weaveworks](https://www.weave.works/product/cloud/).
There were also a number of sessions at KubeCon + CloudNativeCon EU 2018 covering Kubeflow. The links to the talks are here; the associated videos will be posted in the coming days. There were also a number of sessions at KubeCon + CloudNativeCon EU 2018 covering Kubeflow. The links to the talks are here; the associated videos will be posted in the coming days.