Container maintenance tools

Dry is a container lifecycle manager and cluster orchestrator designed to control groups of containers, services, and stacks across multiple nodes. It functions as a resource manager for inspecting and cleaning up images, persistent volumes, and network configurations, while providing a terminal-based dashboard for monitoring system events and resource usage. The project enables the coordination of distributed workloads through service-stack grouping and cluster orchestration. It provides a centralized control plane to synchronize the deployment and scaling of complex application architecture

docker-gc is a garbage collection tool for Docker hosts designed to reclaim disk space by automatically removing exited containers, unused images, and dangling volumes. It functions as a resource cleaner that optimizes host storage through the lifecycle management of orphaned or inactive container resources. The utility manages image retention by preserving a minimum number of the most recent images per repository while deleting older versions. It employs configurable grace periods to determine when images and containers become eligible for deletion and supports pattern-based exclusion to pre

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

Lazydocker is a terminal-based command-line utility that provides an interactive dashboard for monitoring and controlling containerized environments. It functions as a text-based user interface, allowing users to manage containers, images, and volumes directly within a terminal emulator through keyboard-driven navigation. The tool distinguishes itself by replacing manual command-line sequences with a unified workspace that communicates directly with the Docker daemon via the local Unix domain socket. It maintains state synchronization by listening to real-time container events and utilizes co

Docker cleanup volumes is a containerized system maintenance tool and shell script designed to scan host systems and delete unused Docker storage volumes. It reclaims disk space by identifying leftover data assets that are no longer attached to any active containers. The utility inspects container-graph dependencies to distinguish between active and orphaned storage items. It supports dry-run preview execution to simulate cleanup operations and review target volumes before any actual data deletion occurs. The software can be executed directly as a command-line shell script or run as a contai

Slim is a comprehensive suite for container lifecycle management, providing tools for image inspection, optimization, security hardening, and service troubleshooting. It functions as a platform for analyzing containerized applications through both static metadata review and dynamic behavioral probing, enabling users to understand image composition and runtime dependencies. The project distinguishes itself by automating the creation of minimal, production-ready container images. It achieves this by removing unnecessary files and components, flattening image layers, and synthesizing restrictive

Ofelia is a recurring job scheduler designed to run commands inside Docker containers or directly on the host system using a defined timetable. It functions as a configuration engine that reads job schedules and commands from container labels, a concurrency guard to prevent overlapping task executions, and a log router for reporting job outcomes. The system distinguishes itself by using a label-based configuration model, allowing job schedules and execution logic to be defined within container metadata rather than external configuration files. It employs a lock-based concurrency control mecha

Whenever is a Ruby-based cron job manager and background task scheduler that translates a high-level domain-specific language into standard cron-formatted schedule entries. It provides a configuration layer for defining and deploying recurring scripts and binaries into the system crontab using human-readable syntax. The project distinguishes itself by automating the deployment of schedules through environment-based namespacing and role-based task distribution. This allows specific scheduled jobs to be assigned to different server groups based on their roles during the deployment process, with

Qinglong is a containerized task scheduler and automation platform designed to orchestrate recurring background jobs. It provides a centralized dashboard for managing, scheduling, and executing scripts across multiple programming languages, ensuring consistent environments through isolated container-based execution. The platform distinguishes itself by integrating remote repository synchronization, allowing users to clone and update external script collections directly within the system. It combines this with comprehensive environment variable management, enabling the secure storage of creden

gocron is a task scheduling library for Go designed to automate recurring tasks using crontab expressions, fixed durations, and specific calendar dates. It functions as a concurrent job manager and execution monitor that tracks task lifecycles and performance. The project provides distributed task scheduling through leader election and distributed locking to prevent duplicate job execution across multiple nodes. It further distinguishes itself with a concurrency management system that implements singleton constraints and global execution quotas to protect system resources. The scheduler cove

Hangfire is a background job scheduler and distributed task queue for .NET applications. It serves as a job orchestration framework that offloads heavy processing to background workers using a SQL-backed processor to manage job state across multiple servers. The framework distinguishes itself through reliable task scheduling, where job metadata and arguments are persisted in an external database to ensure tasks survive application restarts. It supports advanced orchestration patterns, including the ability to chain dependent tasks so that a child job triggers automatically upon the successful

This project is a Node.js process manager, runtime environment, and production deployment orchestrator. It provides the foundational system components required to run, monitor, and restart applications in the background to ensure continuous service availability. The system distinguishes itself through a built-in load balancer that distributes network traffic across multiple process instances to utilize all available CPU cores. It includes a real-time process monitor with a terminal-based dashboard for tracking server health, CPU and memory usage, and aggregated logs. The tool covers a broad