Runtipi is a self-hosted homeserver orchestrator: a web-based control plane for installing, updating, backing up, and managing Docker Compose applications on a single server. In production it runs as a NestJS backend, a React frontend, and a shared TypeScript schema package, with PostgreSQL as the primary datastore, RabbitMQ for asynchronous job queues, Dockerode for container control, and Traefik as the reverse proxy and TLS/forward-auth gateway. The app-store model clones external git repositories containing app manifests and compose definitions, then validates and renders them through a dynamic form system. The architecture is a monolithic backend organized around modules for app lifecycle, marketplace, app stores, backups, auth, links, settings, and i18n; long-running operations are executed through a command/handler pattern with per-app async mutexes and schema-validated RabbitMQ event queues.
This repository provides a Docker Compose-based setup for running WordPress, designed for both local development and production environments. It orchestrates MySQL and WordPress services with optional WP-CLI access, using environment variables for configuration and named volumes for persistent storage. The production configuration includes resource limits, restart policies, and integration with reverse proxy networks (via VIRTUAL_HOST/LETSENCRYPT variables) for HTTPS support. Key components include environment-specific compose files (docker-compose.yml for production, docker-compose-local.yml for local dev), helper scripts for backup/restore/setup, and WP-CLI wrappers. The setup follows Docker best practices: separating concerns via networks, using volumes for data persistence, and leveraging environment-specific configuration. While not innovative, it implements a solid, maintainable pattern for deploying WordPress with Docker. The codebase demonstrates basic but correct usage of Docker Compose features, with clear separation between local and production configurations. Helper scripts automate common tasks like database dumps and file backups/restores using Docker exec and cp commands. There's no evidence of technical debt or outdated practices; the configuration aligns with current Docker and WordPress ecosystem standards.
PullPreview is a GitHub Action implemented in Go that provisions ephemeral preview environments for pull requests. It manages cloud instances (AWS Lightsail or Hetzner), installs Docker or Kubernetes (k3s), and deploys applications using Docker Compose or Helm. The action integrates deeply with GitHub PR workflows: it reacts to labels, synchronizes SSH keys from repository collaborators, updates PR comments with deployment status and preview URLs, and performs scheduled cleanup of dangling instances. The codebase is organized around a provider abstraction pattern, with concrete implementations for Lightsail and Hetzner that share common orchestration logic for instance lifecycle, SSH access, and deployment. It is a self-contained CLI binary that runs as a composite action step, bundling all dependencies into a single executable.
This repository provides a comprehensive Docker Compose configuration for building a self-hosted NAS (Network Attached Storage) system. It orchestrates over 20 services including media management (Sonarr, Radarr, Lidarr, Bazarr, Prowlarr, qBittorrent, Jellyfin, Jellyseer), a WireGuard VPN (PIA), reverse proxy (Traefik with Let's Encrypt), a homepage dashboard (Homepage), automatic updates (Watchtower), and optional services like AdGuard Home, Home Assistant, Immich, Vaultwarden, Paperless, and more. The architecture is a multi-container Docker stack with a shared network, designed to run on any Docker-capable Linux box. The primary data flow involves downloading media via qBittorrent through a VPN, managing it with *arr applications, and serving it via Jellyfin. The repository includes automation scripts for initial configuration (update-config.sh) and port forwarding updates (pia-shared/portupdate-qbittorrent.sh). It is not a software application with custom code but rather a well-documented, opinionated deployment template. The codebase is primarily configuration files (docker-compose.yml, environment files, nginx configs) with a few bash and JavaScript scripts. The quality is good for its purpose: it is organized, documented, and widely used, but it lacks reusable software components that could be extracted into a new project with minimal modification.
ScaleTail is a curated collection of Docker Compose configurations for self-hosting 80+ services with a consistent Tailscale sidecar pattern. Each service directory contains a `compose.yaml` that defines a `tailscale` container (using `tailscale/tailscale:latest`) and an application container using `network_mode: service:tailscale`, enabling secure HTTPS access via Tailscale Serve or MagicDNS. The repository provides environment-driven configuration (`.env` files), health checks, and per-service READMEs. It is not a standalone application or library but a deployment template repository. The dominant character is 'application' as it facilitates deploying applications, though it is purely configuration and documentation. The pattern is highly reusable for any Docker-based self-hosted service wanting Tailscale integration.
This repository provides a fully automated, one-command deployment of a self-hosted Supabase stack. The setup script (`setup.sh`) orchestrates the entire process: it installs dependencies, clones the repository, generates cryptographic secrets and JWT tokens, configures environment variables, and layers optional docker-compose overrides for Authelia 2FA, Nginx or Caddy reverse proxy, and SSL via Let's Encrypt. The architecture is a Docker Compose multi-service deployment including Supabase Studio, Kong API gateway, GoTrue auth, PostgREST, Realtime, Storage, Edge Functions, and a custom Postgres image. The code is production-grade with robust error handling, CI/CD pipelines (GitHub Actions) that test every configuration matrix (caddy/nginx, basic auth/authelia/redis), and comprehensive integration tests covering CRUD operations, storage, realtime subscriptions, and edge functions. The repository also includes advanced utilities for key management (asymmetric JWTs, opaque API keys) and a sophisticated Postgres 15-to-17 upgrade script (`upgrade-pg17.sh`) that handles binary extraction, pg_upgrade, and post-migration patches. While primarily a deployment tool, the scripts demonstrate high craftsmanship and are safely reusable as templates for similar self-hosting scenarios.
This repository provides Docker Compose and Kubernetes configuration files for deploying a variety of self-hosted applications and system services. It serves as a template repository for deploying services like AdGuard Home, Bitwarden, MinIO, Traefik, and others, as well as system tools like Fail2ban and acme.sh for certificate management. The architecture is modular, with each application having its own directory containing deployment configurations (docker-compose.yml, Helm charts, Kubernetes manifests). There is no single unified application; instead, it offers reusable deployment patterns for individual services. Key entry points are the docker-compose.yml or Helm chart files within each application's directory. The repository relies on external dependencies like Docker, Kubernetes, and Helm for deployment, and the applications themselves depend on their respective upstream container images.
Container Tool Kit (CTK) is a web application that provides a visual editor for Docker Compose and Kubernetes manifest files. Users can create and manage projects by dragging and dropping services, volumes, and networks onto a canvas, editing node configurations through detailed forms, and viewing the resulting YAML/JSON in a synchronized code editor. The backend is built with FastAPI and PostgreSQL, handling project persistence, user authentication (JWT-based), manifest generation (including calling kompose for Kubernetes), and project import from remote YAML URLs. The frontend is a React/TypeScript single-page application using jsPlumb for the interactive canvas, Formik for form management, and Monaco Editor for code editing. The application supports both anonymous and authenticated usage, with features like autosave, visibility toggles, and pagination for project lists.
This repository is a monorepo of self-contained demo applications showing how to build and deploy multi-agent AI systems using Docker Compose, Docker Model Runner, and the MCP Gateway. It contains 12+ independent examples spanning Google ADK, A2A, Agno, CrewAI, LangGraph, Langchaingo (Go), Spring AI, Akka, and a Next.js agent UI. Each subproject is a standalone composition with its own compose.yaml, Dockerfile, and README, designed to run with a single `docker compose up --build` after creating a `.mcp.env` file. The demos are reference architectures rather than a single product, emphasizing local LLM inference, MCP tool integration, and switching between local and cloud models via compose override files.
This repository is a Docker Compose-based node operator stack for running an Ink L2 rollup node on the OP Stack. It wires together op-node (rollup/consensus client), op-geth (execution client), a one-shot bedrock-init container, Prometheus, and Grafana. The primary entry point is `docker compose up`, with per-network environment files under `envs/<network>/` and a `progress.sh` script for checking sync status. It does not yet ship an op-reth Compose path; op-geth is the current execution client.
This repository is a hybrid collection centered around an n8n workflow search engine. The core application is a Python/FastAPI server that indexes and serves ~4,300 n8n workflow JSON files via a SQLite FTS5-backed API, with a static GitHub Pages frontend for browsing. The workflows directory contains a large collection of n8n automation templates covering hundreds of integrations (Slack, Telegram, GitHub, Airtable, etc.), most structured as simple trigger-to-action pipelines. Beyond the main search engine, the repo includes an AI-stack sub-project (Docker Compose for n8n + Agent Zero + ComfyUI), a medical education Next.js app (medcards-ai), Kubernetes/Helm deployment configs, and various utility scripts. The codebase is functional but largely boilerplate — the FastAPI server implements standard CRUD/search patterns with basic security (path traversal protection, rate limiting, CORS), while the workflow JSON files are community-contributed examples of varying complexity. The sub-projects (ai-stack, medcards-ai) appear aspirational rather than production-ready, with the medcards-ai being a well-documented but untested Next.js application.
This repository is a comprehensive collection of infrastructure-as-code configurations for self-hosting a wide variety of services, primarily aimed at homelab enthusiasts and followers of the Jim's Garage YouTube channel. It contains Docker Compose files, Kubernetes manifests, Ansible playbooks, and shell scripts that deploy services such as Traefik, PiHole, Plex, Jellyfin, Immich, Vaultwarden, Gitea, and many more. The central architectural pattern is a reverse proxy (Traefik or Caddy) with Cloudflare DNS-01 certificate challenges, with all services attached to a shared Docker network. The repository is not a single application but a set of modular, copy-paste-friendly deployment blueprints that can be adapted to different environments by changing IP addresses, domain names, and secrets. The codebase demonstrates strong organizational patterns—consistent Traefik labels, Kubernetes IngressRoutes with security middleware, and Ansible roles for cluster provisioning. However, the repository displays technical drift: some scripts pin outdated versions (e.g., kube-vip v0.6.3, MetalLB v0.12.1), and many files use `:latest` image tags, reducing reproducibility. Hardcoded IPs and dummy secrets (annotated with `# gitleaks:allow`) are present throughout, which is acceptable for a tutorial but requires careful sanitization before production use. The inclusion of multiple orchestration options (Docker Compose, Swarm, K3S, RKE2, Ansible) provides flexibility but can confuse users about which path to follow. As a learning resource, the repository is well-structured and actively maintained, with pre-commit hooks, GitHub Actions linting, and gitleaks integration. It is not a reusable library or service but a collection of reference configurations that can be extracted and adapted. The most reusable components are the Ansible roles for RKE2 deployment, the Traefik reverse proxy configuration, and the Kubernetes defaults-headers middleware pattern. Overall, the repository serves its educational purpose effectively while offering practical templates for homelab automation.
This is the umbrella monorepo for Evo CRM Community, an open-source AI-powered customer support platform. The repository itself does not contain application source code; it orchestrates seven independent microservices (auth, CRM, frontend, AI processor, core service, bot runtime, and event flow) via Git submodules and Docker Compose/Swarm configurations. The primary function of this repo is to provide a single entry point for cloning, building, seeding, and deploying the full stack. It includes a nginx API gateway for path-based routing to backend services, CI/CD workflows for building and publishing Docker images, migration version collision guards, and extensive release documentation. The actual business logic, AI agent execution, conversation management, and user interface reside in the submodules.
This repository is a curated collection of Docker Compose samples demonstrating how to integrate various services (web frameworks, databases, proxies, etc.) using Docker Compose. It serves as a reference for developers to quickly set up development environments. The samples cover a wide range of stacks including Angular, Django, Flask, Go, Rust, and more. Notable examples include WebAssembly-based microservices using WasmEdge. The repository is not a single application but a library of examples, each with its own compose.yaml and application code. It is actively maintained by Docker.
Samarium is a modular, all-in-one business management system (ERP/CMS) built with Laravel 11 and Livewire 3. It provides a comprehensive admin dashboard for small to medium businesses, covering sales invoicing, purchase orders, expense tracking, inventory management, accounting (double-entry ledger, trial balance, income statement), customer/vendor relationship management, and a full content management system (webpages, posts, galleries, navigation menus, themes). It also includes e-commerce capabilities (product catalog, shopping cart, online orders), appointment booking, team management, calendar with Nepali date support, and additional modules like vacancies, testimonials, newsletters, and document/URL link management. The system is configurable via a module toggle in config/app.php and supports both a dashboard interface and a public-facing website. The architecture follows a standard Laravel MVC pattern with Livewire components handling all interactive UI. Each business domain has its own set of Livewire components (e.g., SaleInvoiceEditor, ProductDisplay) that use a shared ModesTrait for state management. A service layer provides pagination and CRUD logic, though many service methods are incomplete. The frontend uses Bootstrap 4, Font Awesome, and Chart.js for reporting. The system is Dockerized for easy deployment and includes seeders for demo data. While the codebase is functional and covers a wide feature set, it exhibits several quality issues: mixed namespaces (some models under App\, others under App\Models\), hardcoded values (VAT 13%, Nepali month arrays), incomplete features (many TODO comments, empty service methods), and code duplication (multiple similar Livewire components for editing fields). The Nepali calendar support is a distinctive feature but requires manual maintenance of hardcoded date ranges. Overall, Samarium is a solid, feature-rich ERP for its target audience but would benefit from refactoring and stricter coding standards.
BeaKer is a self-contained threat-hunting deployment for Windows network beacon detection. It provisions an Elasticsearch/Kibana backend with Docker Compose, configures Windows endpoints via a PowerShell agent installer, and ships prebuilt index templates, ingest pipelines, and Kibana dashboards for Sysmon event data. The dominant character is an application/infrastructure project: the core artifacts are deployment scripts, Ansible playbooks, and ELK configuration rather than a library or data analysis framework. A secondary data-pipeline nature is visible in the Elasticsearch ingest pipelines that normalize Windows Security/PowerShell/Sysmon events into ECS, and in the export/import tooling for dashboards and indices.
This repository is an educational Docker tutorial centered on a functional Django REST API application. The core implementation uses Docker Compose to orchestrate two services: a Django web container (DRF) and a PostgreSQL container, with explicit health checks, JSON-file logging limitations, named volumes, and user-defined networks. The Django API itself is a basic music CRUD service with endpoints under /api/musics, secured behind authentication, and housed in a straightforward project structure that demonstrates the typical pattern of a containerized Python microservice. Beyond the main tutorial, the repo provides stand-alone Docker Compose examples covering advanced patterns: YAML anchors to reduce configuration repetition, docker-compose override to batch operate multiple databases, environment variable substitution with .env files, profiles for selective service boot, and cAdvisor for container resource monitoring. Each subfolder includes a README and ready-to-run configuration, making the entire repository a one-stop teaching resource for Docker Compose patterns and best practices. The code is not intended as a production tool but rather as a self-contained, reproducible learning blueprint that shows how to build and manage containerized stacks with modern features. While the application layer is deliberately simple, the Docker-compose layer embodies several good practices around health and logging, and the advanced usage of YAML anchors and overrides exemplifies high-quality configuration craftsmanship that is directly reusable in other projects.
This repository provides deployment configurations and scripts for self-hosting the UI Bakery low-code platform. It contains Docker Compose files for local, Azure, and external database setups, Kubernetes manifests for orchestration, and shell scripts for installation, setup, and updates. The repository does not include the application source code but rather orchestrates pre-built Docker images of UI Bakery's services (gateway, frontend, backend, etc.). The installation script guides users through environment configuration, secret generation, and service startup via Docker Compose. While functional and demonstrating good practices in input validation and cryptographic secret generation, the update script contains a bug in the external database handling section, and the scripts lack modularity, limiting reusability beyond this specific deployment context.
This repository is the central index and deployment configuration for the trace.moe anime scene search engine. It contains no application code; the actual functionality is implemented in separate repositories (trace.moe-api, trace.moe-www, etc.). The primary artifact is a Docker Compose file that orchestrates the entire stack, including PostgreSQL, Milvus vector database, and the API server. This repo is useful for operators who want to deploy the trace.moe system, but developers looking for reusable code should look at the sub-repositories. The documentation provides clear, step-by-step deployment instructions. The system itself is an image-based scene search service that uses vector similarity search to identify anime scenes from screenshots.