Container-Native CI/CD Pipelines

This project is a comprehensive, community-driven directory that serves as a centralized discovery hub for the container ecosystem. It functions as a structured knowledge base, aggregating a wide array of software tools, educational materials, and technical resources designed to assist developers and operators in mastering containerization technologies. The repository distinguishes itself through a meticulously organized taxonomy that maps the entire container lifecycle, from initial development and image building to orchestration, security, and infrastructure operations. By curating disparate external links and documentation into a single, version-controlled collection, it provides a clear navigation path for users seeking specialized utilities, ranging from runtime engines and registry tools to advanced supply chain security and observability solutions. Beyond its role as a tool index, the directory supports professional growth by offering a broad surface of learning resources, including tutorials, best practices, and community-vetted guides. It covers essential operational domains such as multi-container workload management, image hardening, and workflow optimization, ensuring that both newcomers and experienced practitioners have access to a reliable reference for modern containerized systems.

This tool is a command-line runner that executes automation workflows locally within isolated container environments. By parsing workflow definition files and translating them into executable shell scripts, it allows developers to validate pipeline logic and configuration changes directly on their machines before committing code to a remote repository. The runner distinguishes itself by providing a simulation engine that mimics remote CI triggers and event payloads, enabling the testing of complex conditional logic without requiring cloud infrastructure. It supports granular control over the execution environment, allowing users to specify custom container images, inject secrets, and map local directory structures to ensure consistent module resolution. Furthermore, it facilitates integration with private enterprise infrastructure by supporting secure authentication and custom container engine configurations. The project provides operational controls for troubleshooting, such as the ability to isolate and execute individual workflow tasks by name. It manages the lifecycle of ephemeral runner instances through standard socket interfaces, ensuring that local development environments remain synchronized with the requirements of production pipelines.

Zeroclaw is a modular framework for building and deploying autonomous agents that integrate AI models, messaging platforms, and hardware interfaces. It functions as a multi-agent orchestrator and embedded systems controller, providing a unified runtime for managing agent lifecycles, memory, and security policies across diverse environments. The system distinguishes itself through its focus on secure, verifiable hardware and software orchestration. It enforces strict security boundaries, including command allowlisting, resource throttling, and interactive human-in-the-loop approval for sensitive operations. Agents operate within isolated, containerized runtimes and can perform verifiable tool execution by generating cryptographic proofs for every action, ensuring integrity in both digital and physical tasks. The platform supports a wide range of operational capabilities, including cross-platform messaging, real-time voice integration, and low-level hardware control via serial protocols and GPIO pins. It features a pluggable architecture that allows for automatic provider failover, model routing, and persistent memory storage, all managed through a centralized configuration system. The project provides comprehensive tooling for development and deployment, including containerized build orchestration, hardware simulation, and native support for declarative infrastructure management. It is designed to run as a persistent background service, with built-in observability tools for auditing execution states and monitoring system health.

Awesome Compose is a collection of resources designed to demonstrate the orchestration of multi-container applications. It serves as a practical reference for using declarative configuration files to define, manage, and deploy complex software stacks, ensuring that services run consistently across development, testing, and production environments. The project highlights the capabilities of container lifecycle management by providing examples of how to bundle software with its dependencies into isolated, portable units. It emphasizes the use of multi-stage build pipelines to optimize image sizes and the integration of environment variables to decouple application logic from host-specific settings. By leveraging these patterns, users can standardize development workspaces and automate the maintenance of interconnected service architectures. Beyond basic orchestration, the repository covers the broader surface of container infrastructure, including the management of image registries, network configurations, and storage drivers. It also demonstrates how to execute build-time commands and embed complex scripts directly into configuration files to streamline the assembly of containerized environments.

Kubero is a self-hosted Platform as a Service (PaaS) that simplifies the deployment, scaling, and management of containerized applications on Kubernetes. It functions as an application manager, CI/CD orchestrator, and multi-tenant manager, allowing users to run workloads without writing manual configuration files. The platform distinguishes itself through automated image synthesis, transforming source code from Git repositories into deployable containers via buildpacks, Dockerfiles, or nixpacks. It implements a GitOps delivery model with automated pipelines that trigger builds on push events and provision ephemeral review environments for pull requests. Beyond deployment, it provides integrated infrastructure management for provisioning databases and caches through a graphical interface. The system includes multi-tenant isolation using namespaces, role-based access control with OAuth2 authentication, and automated SSL certificate management. Additional capabilities cover resource scaling, application health monitoring, and the attachment of persistent storage volumes. The platform can be installed on local Kubernetes clusters or provisioned on supported cloud providers using a dedicated CLI and web-based management console.

Podman is a container engine designed for managing containerized applications and images without the need for a persistent background daemon. By utilizing a fork-exec process model, it executes container management commands as direct child processes of the host system, ensuring that container lifecycles are handled through standard host-level process control. The project distinguishes itself through a focus on rootless security and cross-platform compatibility. It employs user namespace mapping to allow unprivileged users to manage isolated workloads without requiring administrative system access. On non-Linux operating systems, it integrates with lightweight virtual machines to provide a native command-line experience for container development. The engine supports the full container lifecycle, including image management, registry interaction, and orchestration of background or interactive services. It adheres to open industry standards for container runtimes and includes capabilities for checkpointing and restoring the memory and process state of running containers to facilitate workload migration.

Hadolint is a static analysis tool designed to validate container build configurations. It functions as a security scanner and configuration auditor, parsing build instructions into a structured format to identify deviations from security and efficiency standards. The tool distinguishes itself by performing deep inspection of embedded shell commands. By tokenizing and analyzing these scripts, it detects common scripting errors and security vulnerabilities that might otherwise persist within a container image. It integrates external analysis tools to provide specialized validation for these inline commands, ensuring that both the container structure and the execution logic are evaluated. Beyond basic syntax checking, the utility supports automated workflows by identifying inefficient layer creation and insecure configuration settings. It is designed for integration into continuous integration and deployment pipelines to catch configuration issues before images are built. The project provides a command-line interface for executing these audits across container definitions.

Watchtower is a container-based solution designed to automate the lifecycle management of Docker applications. It functions as a background service that monitors running containers, detects when new base image versions are available in registries, and automatically redeploys the containers to ensure they remain synchronized with the latest builds. The project distinguishes itself through its ability to orchestrate complex deployment workflows and maintain service availability during updates. It interacts directly with the container runtime to manage service dependencies and restart sequences, ensuring that dependent containers are handled in the correct order. Users can further customize the update process by defining lifecycle hooks that execute shell commands before or after a container is replaced, allowing for tailored initialization and cleanup tasks. Beyond automated updates, the tool provides extensive infrastructure observability and flexible management options. It supports event-driven updates via HTTP webhooks, declarative filtering to target specific containers, and secure remote management through encrypted communication and private registry authentication. Operational statistics can be exported to external monitoring systems, and the service can be configured to run in a passive observation mode to track image changes without performing automated redeployments.

KubeSphere is a distributed operating system for cloud-native application management that provides a centralized control plane for Kubernetes clusters. It functions as a comprehensive DevOps portal, enabling teams to orchestrate containerized workloads, manage CI/CD pipelines, and enforce security policies across hybrid cloud, datacenter, and edge environments. The platform distinguishes itself through its multi-cluster federation capabilities and robust multi-tenancy model, which allow for logical resource isolation and granular access control across shared infrastructure. It integrates a modular plugin architecture that supports platform extensibility, enabling users to customize observability, storage, and security components to meet specific operational requirements. Beyond core management, the platform provides a unified observability suite that aggregates metrics, logs, and distributed traces to visualize system health and microservice topology. It also includes advanced traffic governance tools, such as service mesh integration and automated release strategies, to maintain stability during application updates. The project offers a web-based dashboard and a flexible installer to simplify the provisioning and administration of container platforms. It supports diverse infrastructure needs, ranging from bare metal load balancing to hardware accelerator management, through a unified graphical interface.

Sherlock is a command-line automation tool designed to orchestrate software build, execution, and deployment workflows. It functions as an ephemeral runtime orchestrator that executes applications directly from source code, bypassing the need for persistent system-wide installations or manual dependency management. By providing a unified, containerized development environment, it ensures that application dependencies and infrastructure configurations remain consistent across diverse host operating systems. The project distinguishes itself through its ability to synthesize container images declaratively, translating source code and configuration manifests into immutable artifacts. It utilizes documentation-driven discovery to parse technical guides and reference materials, allowing it to map command-line interfaces to automated execution routines. This approach enables the provisioning of short-lived, reproducible environments that maintain consistent behavior throughout the application lifecycle. Beyond its core orchestration capabilities, the tool provides a comprehensive infrastructure-as-code workflow for managing service dependencies and build processes. It abstracts low-level container runtime operations to handle networking, resource constraints, and lifecycle management, while offering integrated access to project documentation to assist with operational requirements.

This project is a Docker educational resource and a collection of practical examples designed for learning containerization technologies. It serves as a guide for understanding container fundamentals, including the creation and management of custom images and the use of registries. The repository provides specialized references for container security hardening, such as managing kernel privileges and implementing supply chain security. It also includes tutorials for multi-container orchestration and a DevOps guide focused on CI/CD automation and image optimization. The material covers a broad range of operational capabilities, including cloud-native architecture, the deployment of Kubernetes clusters, and the configuration of container networking and persistent storage. It further extends into advanced areas such as serving local AI models and analyzing blockchain architectures within containerized environments.

Dive is a command-line tool designed for the analysis and optimization of container images. It functions as a layered storage inspector, allowing users to decompose image manifests to examine individual filesystem layers and identify opportunities to reduce total image size. The tool features a filesystem diffing engine that calculates net changes between sequential layers to highlight redundant data and storage inefficiencies. Users interact with this data through a terminal-based dashboard that provides keyboard-driven navigation of complex file structures and layer metadata. By abstracting the underlying container runtime, the tool maintains compatibility across various storage formats and engine environments. Beyond manual inspection, the software supports automated quality gates for continuous integration pipelines. It evaluates image metadata against user-defined performance thresholds to validate efficiency and prevent the deployment of suboptimal builds. Configuration files allow for the adjustment of logging levels, interface layouts, and engine preferences to suit specific development workflows.

This project is a comprehensive collection of tutorials and guided laboratories designed to teach containerization, networking, and security using Docker. It serves as a learning path for building portable images and executing isolated processes. The materials provide specific guides for managing container clusters and scaling services through Docker Swarm and overlay networks. It includes a security handbook for implementing image scanning and secret management, as well as laboratories dedicated to modernizing legacy applications by wrapping older software installers into containers. The content covers a broad range of capabilities including the configuration of continuous integration pipelines, the deployment of cloud-native applications, and the setup of private image registries. It also provides instructional workflows for performing live debugging of applications within containerized environments.

This project is a self-hosted platform-as-a-service that provides a centralized management interface for deploying, configuring, and monitoring containerized applications and databases on private infrastructure. It functions as a visual control plane, automating the end-to-end lifecycle of services from source code to production. By managing container orchestration, networking, and resource allocation, it allows users to maintain full control over their own hardware while streamlining the delivery of software. The platform distinguishes itself through its agentless architecture, which uses secure shell connections to execute administrative tasks and manage remote servers without requiring persistent local software. It integrates directly with version control systems to trigger automated build and deployment pipelines, including the creation of temporary, isolated preview environments for every pull request. This workflow is supported by a declarative engine that uses templates to standardize the deployment of complex multi-container architectures and persistent database engines. Beyond core orchestration, the system handles the operational requirements of hosted services by managing dynamic reverse-proxy routing and automated SSL certificate lifecycles. It provides a comprehensive suite of infrastructure management tools, including browser-based terminal access for debugging, automated system dependency installation, and persistent state management via a central database. These capabilities ensure that infrastructure remains synchronized and consistent across multiple remote environments.

CapRover is a self-hosted platform-as-a-service that provides a centralized dashboard for managing containerized applications and databases. It functions as a container orchestration platform, simplifying the deployment, scaling, and networking of services across server environments. By leveraging a reverse-proxy-based architecture, the platform handles domain mapping, traffic routing, and automated SSL certificate lifecycle management to ensure secure, encrypted access for hosted web services. The platform distinguishes itself through its integrated automation capabilities, which include automated deployment pipelines that trigger builds directly from version control repositories. It supports zero-downtime deployments by routing traffic to new containers only after successful health checks. Additionally, the system provides declarative service definitions and template-driven configuration management, allowing users to standardize deployments and inject environment variables or secrets at runtime. Beyond core orchestration, the platform includes tools for persistent storage management, database connectivity, and system monitoring. It offers extensibility through dashboard customization and asset injection, while maintaining operational safety via automated system backups and configuration archiving. Administrative access is secured through authentication mechanisms and firewall configuration to maintain network isolation.

Docker Compose is a tool for defining and running multi-container applications through declarative configuration files. It functions as an application lifecycle manager, coordinating the startup, shutdown, and scaling of interconnected services within isolated environments. By using a standardized configuration format, it enables infrastructure as code, allowing developers to manage complex application stacks and their dependencies in a single, repeatable file. The project distinguishes itself by integrating directly with the broader Docker platform, leveraging a client-server architecture where a command-line interface communicates with a persistent daemon to manage container lifecycles. It supports advanced development workflows by providing specialized AI agent frameworks, microVM-based sandboxing for secure code execution, and cloud-based offloading for container builds. These capabilities allow for consistent development environments that mirror production configurations while providing integrated security analysis and supply chain guardrails. Beyond core orchestration, the platform encompasses a comprehensive suite of tools for image distribution, automated builds, and enterprise-grade administration. It provides extensive support for managing container runtimes, storage drivers, and registry interactions, ensuring compatibility with standardized container interfaces. The project is supported by a wide range of documentation, including guides, API references, and interactive workshops designed to assist with local development and scalable deployment.

Dagger is a programmable CI/CD engine and containerized task runner designed to orchestrate build and test pipelines. It functions as an incremental build system that manages containers, filesystems, and secrets through a typed API to ensure consistent execution across local and cloud environments. The engine utilizes a language-agnostic client-server API to allow multi-language pipeline orchestration, enabling the sharing of typed artifacts and state across different SDKs without manual serialization. It optimizes execution through content-addressable caching and a directed acyclic graph to run only the pipeline steps affected by specific changes. The platform covers OCI container orchestration and image management, including pulling and publishing images. It provides integrated secret management, version control integration, and network service coordination with automated liveness probes. Observability is handled through telemetry-driven execution tracing and interactive shell debugging for real-time pipeline state inspection.

Dokku is a self-hosted platform as a service that automates the deployment and management of web applications on your own infrastructure. It functions as an infrastructure automation tool, providing a git-driven engine that triggers container builds, service orchestration, and release workflows directly from source code repositories. The platform distinguishes itself by using buildpack-based image construction to detect project structures and automate container creation without manual configuration. It manages the full application lifecycle through a simplified interface that abstracts low-level container runtime commands, while dynamically handling reverse-proxy routing and environment-variable-driven configuration to map traffic and decouple settings from the underlying host. Beyond core deployment, the system provides comprehensive infrastructure lifecycle management, including the automated setup of system dependencies and the configuration of administrative access controls. The platform is designed for modular expansion, allowing users to extend core functionality through a plugin system that hooks into lifecycle events. It is installed on Linux distributions using automated scripts to ensure consistent environment preparation.

This is a command line tool for building and managing isolated development environments based on the Development Container Specification. It functions as an OCI container image builder and a provisioner for instantiating standardized containers within automated continuous integration workflows. The tool includes a system for injecting pre-configured software and toolsets into containers using a registry of reusable installation modules. This allows for the creation of shareable features and the installation of specific languages, CLI tools, and software dependencies. It covers the automation of environment bootstrapping, the generation of prebuilt images to reduce startup time, and the execution of commands and lifecycle scripts within running containers. It also handles the mapping of workspace folders to ensure consistent setups across different machines.

Drone is a container-based continuous integration and delivery platform, source control management system, and artifact registry. It functions as a hosted workspace provider for cloud-based developer environments and a system for hosting and versioning code repositories. The platform executes build and deployment pipelines within isolated containers, using declarative configurations to automate software delivery. It includes a centralized registry for managing and versioning compiled binaries and build outputs to ensure consistent deployments across environments. The system covers a broad capability surface including event-driven workflow triggering via source control integration, administrative management through a command line interface, and orchestration via a REST API.