6 مستودعات
Libraries and SDKs for programmatically interacting with container engine remote APIs.
Distinguishing note: No existing candidates; focuses on programmatic integration with container runtimes.
Explore 6 awesome GitHub repositories matching devops & infrastructure · Container API Clients. Refine with filters or upvote what's useful.
Moby is an OCI container engine and runtime manager designed for building, running, and managing isolated containers based on Open Container Initiative standards. It functions as a container daemon and image builder, providing a core engine to orchestrate the full lifecycle of containers and the packaging of source code into portable images. The project provides a standardized HTTP interface that allows for programmatic container management, enabling external clients to control daemon settings and container operations. It supports a rootless security model, allowing the engine daemon to execu
Ships programmatic clients that allow external applications to execute container lifecycle operations.
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 disparat
Provides programmatic interfaces for interacting with container engine APIs.
Libpod is a container management library for running and controlling the lifecycle of Open Container Initiative compliant containers and images across different storage backends. It provides a programmatic interface for the remote control and automation of container environments. The project enables the coordination of multiple containers into pods that share network namespaces and other shared resources. It supports rootless container execution by using user namespaces to launch containers without administrative privileges. The library covers a broad range of system operations, including im
Exposes a socket-based management interface that translates API requests into low-level container operations.
Containerd is a daemon-based container runtime that manages the complete lifecycle of containers on a host system. It functions as a core orchestration backend, handling image distribution, storage, and process execution while adhering to industry-standard specifications for container execution and configuration. The project is distinguished by its modular, plugin-based architecture, which allows for the extension of storage, runtime, and networking capabilities without requiring a full daemon recompile. It utilizes a shim-based execution model to delegate low-level operations, ensuring isola
Provides a programmatic client package for direct infrastructure control by external applications.
Komodo is a remote server orchestrator and container deployment platform. It provides a centralized interface for managing multiple remote hosts through lightweight agents, coordinating Docker Swarm and Kubernetes clusters, and automating software delivery via integrated CI/CD pipelines. The system distinguishes itself with a TypeScript-based automation engine that executes typed scripts against the system API for complex operational workflows. It supports infrastructure-as-code through TOML-based declarative configuration synchronization and provides ephemeral build infrastructure that provi
Provides programmatic clients and SDKs to integrate container management into external scripts.
kubectl-ai is a natural language cluster operator and AI command assistant that translates plain-text prompts into executable Kubernetes commands. It serves as an interface between large language models and the Kubernetes API to enable cluster management through conversational text. The project implements a Model Context Protocol server to expose cluster operations as standardized tools for external AI clients. It uses a provider-agnostic model interface to support both cloud-based and local AI backends. The system covers natural language infrastructure control and AI-assisted DevOps through
Maps high-level AI tool requests to specific Kubernetes operations via the standard command line interface.