5750 Open source projects that are alternatives of or similar to Kogito Runtimes

Kogito examples - Kogito is a cloud-native business automation technology for building cloud-ready business applications.

基于C#语言研发的Smartflow-Sharp工作流组件，该工作流组件的特点是简单易用、方便扩展、支持多种数据库访问、高度可定制化，支持用户按需求做功能的定制开发，节省用户的使用成本

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Workflow engine for Kubernetes

Data intensive science for everyone.

Reusable workflow library for Django

Integration between Micronaut and Camunda (Workflow Engine). We configure Camunda with sensible defaults, so that you can get started with minimum configuration: simply add a dependency in your Micronaut project to embed the workflow engine!

A BPMN 2.0 workflow engine for PHP

An integrated modeling solution for BPMN and DMN based on bpmn.io.

GLPI plugin that provides an interface with ProcessMaker (http://www.processmaker.com/)

Show your latest blog posts from any sources or StackOverflow activity or Youtube Videos on your GitHub profile/project readme automatically using the RSS feed

Activiti is a light-weight workflow and Business Process Management (BPM) Platform targeted at business people, developers and system admins. Its core is a super-fast and rock-solid BPMN 2 process engine for Java. It's open-source and distributed under the Apache license. Activiti runs in any Java application, on a server, on a cluster or in the…

Executable workflow elements based on BPMN 2.0

PacBot (Policy as Code Bot)

🚀 A shiny admin interface for django-river built with DRF, Vue & Vuetify

Easy Wordpress development with Docker and Docker Compose

Leading Open Source Container Attached Storage, built using Cloud Native Architecture, simplifies running Stateful Applications on Kubernetes.

Robust, flexible and resource-efficient pipelines using Go and the commandline

A powerful workflow engine implemented in pure Python

HyperFlow: a scientific workflow engine

A distributed workflow runner focusing on performance and simplicity.

We do Open Source ERP - Fast, Flexible & Free Software to scale your Business.

Integration between Cloudfoundry and the Spring Cloud APIs

Machine is a workflow/pipeline library for processing data

CLI for searching Rego policies

The Prefect API and backend

nFlow is a battle-proven solution for orchestrating business processes. It can be used as microservices orchestrator (Saga-pattern), as business process engine or as persistent finite-state machine.

微服务(Microservices)和云原生架构教学案例项目，基于Spring Boot和Kubernetes技术栈

Titanoboa makes complex workflows easy. It is a low-code workflow orchestration platform for JVM - distributed, highly scalable and fault tolerant.

🚥 Petrinet framework for PHP

基于django的工作流引擎,工单(a workflow engine base on django python)

Workflows for automation of AWS services setup from Github CI/CD

JetLinks 基于Java8,Spring Boot 2.x ,WebFlux,Netty,Vert.x,Reactor等开发, 是一个全响应式的企业级物联网平台。支持统一物模型管理,多种设备,多种厂家,统一管理。统一设备连接管理,多协议适配(TCP,MQTT,UDP,CoAP,HTTP等),屏蔽网络编程复杂性,灵活接入不同厂家不同协议等设备。实时数据处理,设备告警,消息通知,数据转发。地理位置,数据可视化等。能帮助你快速建立物联网相关业务系统。

Distributed tracing for spring cloud

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Reflow automatically creates pull requests, ensures the code review is approved, and squash merges finished branches to master with a great commit message template.

Develop your applications directly in your Kubernetes Cluster

Workflow Server is a ready-to-use Workflow Engine-based application that you can deploy into your infrastructure. It can be integrated with NodeJS, PHP, Ruby, .NET, or Java applications via a REST API. Workflow Server is a key component for managing the lifecycle of business objects within your enterprise.

External configuration (server and client) for Spring Cloud

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Spring Cloud CLI features

审批王，华炎魔方内置BPM工作流引擎，低代码快速开发平台。

Litmus helps SREs and developers practice chaos engineering in a Cloud-native way. Chaos experiments are published at the ChaosHub (https://hub.litmuschaos.io). Community notes is at https://hackmd.io/a4Zu_sH4TZGeih-xCimi3Q

The free Zapier/IFTTT alternative for developers to automate your workflows based on Github actions

BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.