This project is a containerized build automation system and self-hosted DevOps platform provided as a Docker image. It serves as a distributed build orchestrator and a Dockerized continuous integration and delivery server, ensuring consistent execution environments across different infrastructure.
Las características principales de jenkinsci/docker son: Containerized Build Systems, Containerized Server Deployments, Build Tool Integrations, CI/CD Automation Servers, CI/CD Workflows, Build Execution, Containerized Tooling, Continuous Integration Servers.
Las alternativas de código abierto para jenkinsci/docker incluyen: maiot-io/zenml — ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data… zenml-io/zenml — ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning… jenkinsci/pipeline-examples — This project is a library of version-controlled workflow definitions and a collection of Groovy scripts and… jenkins-x/jx — jx is a GitOps delivery platform and Kubernetes CI/CD orchestrator designed to automate the building and deployment of… jenkinsci/jenkins — Jenkins is a CI/CD automation server and build automation tool used to orchestrate software build, test, and… home-assistant/home-assistant.io — Home Assistant is a local home automation platform and server that acts as an IoT device orchestrator. It integrates…
ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself
ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented
This project is a library of version-controlled workflow definitions and a collection of Groovy scripts and configuration snippets for implementing continuous integration and delivery automation in Jenkins. It serves as a reference for building automated pipelines using both declarative syntax and scripted logic. The repository provides template collections and implementation patterns for creating software build and deployment workflows. It includes reusable functions and logic patterns designed to standardize pipeline behavior and eliminate code duplication across multiple projects through t
jx is a GitOps delivery platform and Kubernetes CI/CD orchestrator designed to automate the building and deployment of applications. It functions as a cloud native pipeline manager that executes container-based build and deployment sequences using a catalog of reusable tasks. The project distinguishes itself through the automated orchestration of preview environments, which are created and destroyed based on pull request activity to enable validation before merging. It employs a GitOps-based state synchronization model to maintain the desired state of clusters by polling git repositories and