From fc7b05e10712946ca694e7d51260cb5fb43b51e2 Mon Sep 17 00:00:00 2001 From: Jenna Ritten Date: Fri, 22 Oct 2021 13:17:03 -0400 Subject: [PATCH] Update README.md typos. (#756) * Update README.md typos. Signed-off-by: Jenna Ritten * Update README.md typos. Signed-off-by: Jenna Ritten * Update README.md Co-authored-by: Tommy Li * Apply suggestions from code review Co-authored-by: Tommy Li --- README.md | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index d6c540e01f3..a711acb972e 100644 --- a/README.md +++ b/README.md @@ -1,32 +1,29 @@ # Kubeflow Pipelines on Tekton Project bringing Kubeflow Pipelines and Tekton together. The project is driven -according to this [design doc](http://bit.ly/kfp-tekton). The current code allows -you run Kubeflow Pipelines with Tekton backend end to end. +according to this [design doc](http://bit.ly/kfp-tekton). The current code allows you run Kubeflow Pipelines with Tekton backend end to end. -* Create your Pipeline using Kubeflow Pipelines DSL, and compile it to Tekton YAML. +* Create your Pipeline using Kubeflow Pipelines DSL, and compile it to Tekton + YAML. * Upload the compiled Tekton YAML to KFP engine (API and UI), and run end to end with logging and artifacts tracking enabled. -For more details about the project please follow this detailed [blog post](https://developer.ibm.com/blogs/kubeflow-pipelines-with-tekton-and-watson/). For latest information and supported offerings, please follow the [Kubeflow Pipelines on Tekton 1.0 release blog](https://developer.ibm.com/blogs/kubeflow-pipelines-and-tekton-advances-data-workloads/). Additionally, look at these [slides](https://www.slideshare.net/AnimeshSingh/kubeflow-pipelines-with-tekton-236769976) -as well as this [deep dive presentation](https://www.youtube.com/watch?v=AYIeNtXLT_k) -for demos. +For more details about the project please follow this detailed [blog post](https://developer.ibm.com/blogs/kubeflow-pipelines-with-tekton-and-watson/). For latest information and supported offerings, please follow the [Kubeflow Pipelines on Tekton 1.0 release blog](https://developer.ibm.com/blogs/kubeflow-pipelines-and-tekton-advances-data-workloads/). Additionally, look at these [slides](https://www.slideshare.net/AnimeshSingh/kubeflow-pipelines-with-tekton-236769976) as well as this [deep dive presentation](https://www.youtube.com/watch?v=AYIeNtXLT_k) for demos. **Note**: If you are interested in a sister project built on top of Kubeflow Pipelines with Tekton, please try [Machine Learning eXchange (MLX)](https://github.com/machine-learning-exchange), Data and AI Assets Catalog and Execution Engine. It introduces a 'Component Registry' for Kubeflow Pipelines, amongst other things. -## Architecture +## Architecture We are currently using [Kubeflow Pipelines 1.7.0](https://github.com/kubeflow/pipelines/releases/tag/1.7.0) and [Tekton >= 0.27.0](https://github.com/tektoncd/pipeline/releases/tag/v0.27.0) -for this project. +for this project. ![kfp-tekton](images/kfp-tekton.png) -Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows. More architectural details about the Kubeflow Pipelines can be found on [Kubeflow website](https://www.kubeflow.org/docs/components/pipelines/overview/pipelines-overview/) +Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows. More architectural details about the Kubeflow Pipelines can be found on the [Kubeflow website](https://www.kubeflow.org/docs/components/pipelines/overview/pipelines-overview/). The Tekton Pipelines project provides Kubernetes-style resources for declaring -CI/CD-style pipelines. Tekton introduces several [Custom Resource Definitions](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)(CRDs) including Task, Pipeline, TaskRun, and PipelineRun. A PipelineRun represents a single running instance of a Pipeline and is responsible for creating a Pod for each of its Tasks and as many containers within each Pod as it has Steps. Please -look for more details in [Tekton repo](https://github.com/tektoncd/pipeline). +CI/CD-style pipelines. Tekton introduces several [Custom Resource Definitions](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)(CRDs) including Task, Pipeline, TaskRun, and PipelineRun. A PipelineRun represents a single running instance of a Pipeline and is responsible for creating a Pod for each of its Tasks and as many containers within each Pod as it has Steps. Please look for more details in the [Tekton repo](https://github.com/tektoncd/pipeline). ### Get Started using Kubeflow Pipelines on Tekton