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argo-workflows

Workflow engine for Kubernetes

授权协议 Apache-2.0 License

开发语言 Python

所属分类神经网络/人工智能、机器学习/深度学习

软件类型开源软件

地区不详

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操作系统跨平台

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软件概览

What is Argo Workflows?

Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. ArgoWorkflows is implemented as a Kubernetes CRD (Custom Resource Definition).

Define workflows where each step in the workflow is a container.
Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclicgraph (DAG).
Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using ArgoWorkflows on Kubernetes.

Argo is a Cloud Native Computing Foundation (CNCF) hosted project.

Use Cases

Machine Learning pipelines
Data and batch processing
ETL
Infrastructure automation
CI/CD

Why Argo Workflows?

Argo Workflows is the most popular workflow execution engine for Kubernetes.
It can run 1000s of workflows a day, each with 1000s of concurrent tasks.
Our users say it is lighter-weight, faster, more powerful, and easier to use
Designed from the ground up for containers without the overhead and limitations of legacy VM and server-basedenvironments.
Cloud agnostic and can run on any Kubernetes cluster.

Read what people said in our latest survey

Try Argo Workflows

Access the demo environment (login using Github)

Ecosystem

SDKs

Check out our Java, Golang and Python SDKs.

Quickstart

kubectl create namespace argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/master/manifests/install.yaml

Who uses Argo Workflows?

Official Argo Workflows user list

Documentation

Features

UI to visualize and manage Workflows
Artifact support (S3, Artifactory, Alibaba Cloud OSS, HTTP, Git, GCS, raw)
Workflow templating to store commonly used Workflows in the cluster
Archiving Workflows after executing for later access
Scheduled workflows using cron
Server interface with REST API (HTTP and GRPC)
DAG or Steps based declaration of workflows
Step level input & outputs (artifacts/parameters)
Loops
Parameterization
Conditionals
Timeouts (step & workflow level)
Retry (step & workflow level)
Resubmit (memoized)
Suspend & Resume
Cancellation
K8s resource orchestration
Exit Hooks (notifications, cleanup)
Garbage collection of completed workflow
Scheduling (affinity/tolerations/node selectors)
Volumes (ephemeral/existing)
Parallelism limits
Daemoned steps
DinD (docker-in-docker)
Script steps
Event emission
Prometheus metrics
Multiple executors
Multiple pod and workflow garbage collection strategies
Automatically calculated resource usage per step
Java/Golang/Python SDKs
Pod Disruption Budget support
Single-sign on (OAuth2/OIDC)
Webhook triggering
CLI
Out-of-the box and custom Prometheus metrics
Windows container support
Embedded widgets
Multiplex log viewer

Community Meetings

We host monthly community meetings where we and the community showcase demos and discuss the current and future state ofthe project. Feel free to join us! For Community Meeting information, minutes and recordingsplease see here.

Participation in the Argo Workflows project is governed bythe CNCF Code of Conduct

Community Blogs and Presentations

Project Resources

Argo GitHub: https://github.com/argoproj
Argo Website: https://argoproj.github.io/
Argo Slack: click here to join

使用案例

argo workflows

一.Argo简介官网参考 1. Argo子项目 Argo Workflows：基于容器的任务编排工具 Argo CD：基于GitOps声明的持续交付工具 Argo Events：事件驱动工具 Argo Rollouts：支持金丝雀以及蓝绿发布的应用渐进式发布工具 2. argo CRD Argo Workflows是一个开源容器原生工作流引擎，用于在 Kubernetes 上编排并行作业。Ar
Argo workflows 归档以及 GC 功能

归档 Argo Workflow 支持将工作流执行记录（Workflow）的信息存储到 PostgreSQL 或 MySQL 中，以达到更长久地保存执行记录但又不会影响到 Kubernetes 集群的性能。这里，给出一个归档（ Archive ）数据到 PostgreSQL 的配置方法：首先，安装 PostgreSQL 。这里采用 Helm Chart 的方式来安装： helm repo ad
Argo Workflows 中文快速指南·

Argo Workflows 是一个云原生的通用的工作流引擎。本教程主要介绍如何用其完成持续集成（Continous Integration, CI）任务。本文全部内容来自：https://github.com/LinuxSuRen/argo-workflows-guide 如果您感觉本文对您或其他人有帮助，欢迎点赞、转发、分享。更加丰富、详细的内容也会在上面的 GitHub 仓库中更新，大家可
Argo Workflows 的 Golang SDK 使用介绍

公众号文章内的链接，请访问 https://github.com/LinuxSuRen/argo-workflows-guide#golang-sdk Argo Workflows 官方维护了 Golang、Java、Python 语言的 SDK。下面以 Golang 为例，讲解 SDK 的使用方法。在运行下面的示例前，有两点需要注意的： Argo Workflows Server 地址 Tok
Argo Workflows 的插件机制介绍

Argo Workflows 内置了几种类型的任务模板，这些任务类型或是方便解决特定问题，或是可以解决通用问题。此外，我们还可以通过执行器（Executor）插件扩展 Argo Workflows 的功能。执行器插件，会作为工作流 Pod 中 sidecar 的形式存在，通过 HTTP 提供服务。Argo Workflows 规定了 URI，以及 Request 和 Response。据此，我们
云原生 CICD 工作流引擎 Argo workflows 单点登录

基于 Kubernetes 的云原生 CICD 工作流引擎 Argo workflows 完整的教程请查看下面的地址 https://github.com/devops-ws/argo-workflows-guide 下面给出配置 Argo workflows 单点登录的说明：为了保证 Argo workflows 同时支持 SSO(Single Sign-On) 以及 webhook 的执行，
Argo Workflows概述，安装部署，服务的发布、加密方式

翻译整理自：【Github】：https://github.com/argoproj/argo-workflows/ 【Website】：https://argoproj.github.io/ 一、什么是Argo Workflows? Argo workflow是一个开源的容器本地工作流引擎，用于在Kubernetes上编排并行作业。Argo工作流被实现为Kubernetes CRD(自定义资源
k8s argo workflow获取登录token的命令

k8s argo workflow获取登录token的命令 kubectl exec -it argo-server-xxx-xxx -n argo-system -- argo auth token