This repository provides a single, well-tested Bash script (`ecs-deploy`) that automates blue/green deployments on AWS ECS. It fetches the current task definition, creates a new revision with an updated Docker image tag, registers it, updates the ECS service (or directly runs a task), and waits for the deployment to complete. The script handles various edge cases: image name parsing (including domain, port, repository, tag, digest, and ECR-style URLs), role assumption, rollback, and cleaning up old task definition revisions. It is packaging-ready as a Docker image and includes a GitHub Action for CI/CD pipelines. The codebase is in maintenance-only mode but remains fully functional and widely used. Its primary reuse pattern is the standalone shell script itself—downloadable and integrable into any deployment pipeline. A hidden gem is the `parseImageName` function, which implements robust Docker image name parsing via regex and environment variable overrides, and the test suite (`test.bats`) demonstrates a clean pattern for unit-testing Bash functions while mocking external dependencies.
Bash-my-AWS is a CLI toolset designed to manage AWS resources using Bash functions and aliases. It wraps the AWS CLI with convenience functions for listing, filtering, and manipulating resources like EC2, S3, and CloudFormation. The architecture is a monolithic Bash library sourced into the user's shell environment, with modularized logic in `lib/*-functions`. It relies heavily on `awscli`, `jq`, and standard Unix utilities. The tool implements a pipe-skimming pattern (`skim-stdin`) that allows chaining commands (e.g., `instances | instance-stop`), enhancing usability for shell scripting. It includes a Python-based caching proxy (`bin/cachews`) to reduce API latency. While well-structured for Bash, it carries inherent risks due to the language's limitations, including security vulnerabilities in SSH handling and reliance on `eval` for argument inference. The repository is actively maintained with recent commits and a comprehensive test suite using a custom BDD-style framework. However, technical drift is moderate due to the rapid evolution of AWS APIs and Bash-specific security concerns. The codebase is suitable for engineers comfortable with Bash scripting who need a robust set of AWS management utilities.
This repository is a collection of shell scripts for installing, upgrading, and managing MagicMirror², an open-source smart mirror platform. The scripts automate the setup of Node.js, npm, pm2, and the MagicMirror application on Raspberry Pi and other Linux systems, as well as macOS. They handle tasks such as initial installation, version upgrades, pm2 process management, screensaver disabling, disk cleanup, and switching to browser-over-server mode. The scripts are designed to be executed via curl pipe to bash, ensuring users always run the latest version. While primarily operational, the cleanup.sh script stands out as a well-structured, reusable utility for reclaiming disk space on any system.
envbuilder is a CLI tool written in Go that builds and runs Dev Containers (as defined by devcontainer.json) inside Docker containers, using a forked version of Kaniko for image building. In production, it clones a Git repository, locates a devcontainer.json or Dockerfile, compiles a Dockerfile with requested features, builds the image via Kaniko (with layer caching), and then executes lifecycle scripts (onCreate, postCreate, etc.) before running an init command as a specified user. It is designed to integrate with Coder workspaces for log forwarding but can operate standalone. The architecture is a single binary with modular components: options parsing (options/), Git operations (git/), devcontainer spec handling (devcontainer/), Kaniko build orchestration (envbuilder.go), and logging (log/). It relies on system calls for user switching (setuid), execution (exec), and filesystem mounts. External dependencies include Git, Docker daemon, and the Kaniko fork. The tool supports extensive configuration via CLI flags and environment variables, with legacy variable support. Key entry points are cmd/envbuilder/main.go (CLI) and envbuilder.go (Run function). The primary data flow is: input options -> clone repo -> parse devcontainer -> compile Dockerfile -> Kaniko build -> execute lifecycle scripts -> setuid -> exec init. The tool also includes a cache probe mode for checking layer availability without full build.
This repository implements a GitHub Action that triggers AWS CodeBuild builds. It starts a build using the AWS SDK, streams CloudWatch Logs to the GitHub Action output, and waits for the build to complete. The action handles rate limiting with exponential backoff and jitter, and supports cancelling builds via signal handling. The core logic is in `code-build.js`, which exports functions for building, waiting for completion, and processing inputs. The action is designed to be used in GitHub workflows but can also be run locally via the `local.js` script.
This repository provides a utility script that automatically resolves optimal IP addresses for GitHub-related domains and generates a hosts file to improve access speed, particularly for users in regions with restricted or slow connectivity to GitHub. The core logic is implemented in two Python scripts: `fetch_ips.py` performs DNS resolution via DoH (DNS over HTTPS) and asynchronous DNS queries, then measures TCP latency on port 443 to select the fastest IP for each domain. `update_ips.py` is a lighter variant used in the GitHub Actions CI pipeline, which fetches pre-computed IPs from a remote JSON source and updates the README with the latest hosts content. The project is not a traditional application but a scheduled data-generation pipeline that runs every two hours via GitHub Actions, committing the updated hosts file and README back to the repository. The architecture is monolithic, with shared utility functions in `common.py` handling file I/O and template rendering. External dependencies include `requests`, `aiodns`, and `retry`. While the code is straightforward and lacks tests, it demonstrates practical network programming patterns such as TCP-based latency measurement without root privileges and multi-source DNS resolution.
This is the umbrella repository for the cdk8s project, an open-source software development framework for defining Kubernetes applications using familiar programming languages (TypeScript, Python, Java, Go). The repository itself does not contain the core cdk8s library code—those live in separate packages (cdk8s-core, cdk8s-cli, cdk8s-plus). Instead, this repo coordinates documentation (MkDocs site for API reference, Hugo website for marketing), RFCs for feature proposals, research on high-level abstractions, Kubernetes schema definitions (version 1.14.0 through 1.37.0), and CI/CD infrastructure. It also includes scripts for schema import, version rotation, and build automation. The repository is a CNCF Sandbox project developed primarily at AWS and follows the constructs programming model (App → Chart → resources). While the repo serves as the project's documentation and coordination hub, it demonstrates strong engineering practices: a well-defined RFC process, projen-based project configuration, versioned documentation targeting multiple Kubernetes versions, and automated upgrade workflows. The actual application logic for defining and synthesizing Kubernetes manifests resides in the companion packages. Researchers and engineers looking for reusable Kubernetes abstractions should refer to the separate cdk8s-plus libraries, which provide hand-crafted high-level constructs for resources like Pods, Deployments, and Services. This umbrella repo is best suited for understanding the project's architecture, contributing via RFCs, or consuming the documentation and schema definitions.
This repository, microsoft/WhatTheHack, is a comprehensive collection of hackathon challenge content focused on Microsoft Azure technologies. It contains over 70 individual 'hacks' covering topics such as Kubernetes, AI, DevOps, serverless, infrastructure-as-code, and more. Each hack includes student challenge instructions, coach solutions, and often starter code and infrastructure templates. The repository serves as a reusable library for running hands-on workshops and self-paced learning. While not a single application, it provides a structured framework for creating and delivering technical training events. The code quality varies across challenges, but the overall organization and documentation are strong, with reusable patterns like GitHub Actions workflows and hack authoring templates.
This repository provides an xontrib (plugin) for the Xonsh shell that adds a `cheatsheet` command to open the project's README.md in a web browser. The README.md serves as a comprehensive cheat sheet for the Xonsh shell, covering installation, basics, and advanced topics. The repository also includes an example script demonstrating how to make web requests, process output, and use colored output in Xonsh.
This repository is a self-paced learning roadmap for algorithmic trading, structured as a hierarchical collection of markdown files. It curates resources, certifications, and project ideas across artificial intelligence, computer science, mathematics, finance, cloud engineering, and software engineering. The repository is entirely documentation-driven; there are no executable applications, data pipelines, or machine learning models. Its primary value lies in its organized curriculum, reusable topic templates, and role-based learning paths (e.g., quant developer, algorithmic trader). While not a software project, it demonstrates high organizational craftsmanship through consistent documentation structure, templates, and CI/CD for link checking and diagram rendering.
This repository contains a full-stack web application deployed on AWS ECS with a CI/CD pipeline. The frontend is a Vue.js application that retrieves product data from a backend Node.js/Express API. The backend scans a DynamoDB table and returns product information, including image URLs stored in S3. Infrastructure is provisioned via Terraform, including networking, ECS cluster/services, ECR repositories, IAM roles, CodePipeline/CodeBuild/CodeDeploy for Blue/Green deployments, autoscaling, and supporting resources (S3, DynamoDB, SNS). The architecture separates concerns with modular Terraform modules and implements production-grade practices like health checks, Swagger documentation, and stress testing.
This repository contains educational materials for learning Docker, specifically designed to prepare for the Docker Certified Associate (DCA) certification. It consists of markdown-formatted chapters covering Docker fundamentals, images, volumes, networking, docker-compose, swarm, monitoring, tools, Kubernetes, and enterprise topics. The repository also includes a lab environment setup using Vagrant to provide hands-on experience with Docker in a multi-node cluster configuration. The primary value of this repository lies in its comprehensive documentation rather than executable code. It serves as a structured learning resource that explains Docker concepts with practical examples and setup instructions. The lab directory contains reusable infrastructure-as-code components for provisioning a Docker swarm cluster using Vagrant and VirtualBox, enabling users to create a consistent learning environment.
docker-copyedit is a CLI tool for editing Docker image metadata, including removing/adding volumes, ports, environment variables, labels, and modifying image configuration like user, workdir, entrypoint, and cmd. The tool works by saving a Docker image to a tarball, extracting and modifying the metadata JSON files (manifest.json and config files), then re-packaging and loading the modified image. It supports both Docker and Podman via command-line flags. The architecture is a monolithic Python application with a clear separation between the CLI wrapper and core implementation. Key functions include parsing Docker image names, executing shell commands with proper error handling, and a custom command-line DSL for specifying image modifications.
NixBSD is a declarative system configuration framework that ports NixOS infrastructure to BSD kernels (FreeBSD and OpenBSD). It functions as a complete operating system distribution definition, managing bootloaders, init systems, services, and user configurations through Nix expressions. The architecture is modular, leveraging the NixOS module system to define system state, with specific adaptations for BSD-specific tools like rc.d, jails, and ZFS. The system relies heavily on custom build logic to generate disk images, installers, and bootloader configurations that are compatible with BSD hardware constraints. It includes a portable init abstraction layer to unify service management across Linux, FreeBSD, and OpenBSD, though this introduces significant complexity. Security features like PAM, ACME certificates, and setuid wrappers are implemented as declarative modules. While the codebase demonstrates high craftsmanship in system integration and Nix expression patterns, it suffers from high technical drift due to the inherent divergence between NixOS (systemd-based) and BSD (rc-based) ecosystems. Upstream NixOS changes frequently require manual merging, and BSD-specific logic (e.g., initware, stand-freebsd) creates maintenance bottlenecks. It is a robust infrastructure tool for users requiring declarative BSD management but requires significant expertise to maintain.
Minecraft Server Control Script (MSCS) is a monolithic Bash/Perl CLI tool for managing multiple Minecraft server instances on Linux. It provides a comprehensive set of actions: starting/stopping/restarting worlds, creating/deleting/enabling/disabling worlds, backing up (via rdiff-backup), mapping (via Minecraft Overviewer), updating server software, sending commands, and querying server status. The architecture is a single large shell script (msctl) with a wrapper (mscs) for system integration. Configuration is done via INI-style defaults files and per-world properties. The script relies on external tools: Java, Perl, Python, wget, rdiff-backup, rsync, socat, and flock. It integrates with systemd via provided service files and supports LSB init scripts. The codebase is functional and well-documented internally, but tightly coupled and monolithic, making extraction of individual components non-trivial.
Arx is a Haskell CLI tool and library that archives execution contexts (source code, command, environment) into a self-extracting POSIX shell script. The generated script sets up a temporary directory, unpacks archives, sets environment variables, and executes the command with trap-based cleanup. The system is designed for reliable, reproducible remote execution via SSH/sudo piped to sh. The Haskell library provides a clean type-class based interface (ARX, SHDAT, TMPX) for building such scripts, with sub-modules for shell variable validation, tar format detection, and a novel scheme for encoding arbitrary binary data into shell HEREDOCs with minimal overhead (handling NUL bytes and escape characters). The CLI uses a custom combinator parser built with Parsec. This is a well-architected, focused tool demonstrating deep knowledge of both Haskell and shell scripting.
This repository provides a Docker image for Apache Superset, a data exploration and visualization platform. It is not an application itself but a containerization layer that packages Superset with its dependencies, including helper scripts for initialization and demo data loading. The Dockerfile is well-structured with proper environment variables, healthcheck, non-root user, and multi-architecture build support via CI/CD. The repository includes example configurations for MySQL, PostgreSQL, SQLite, and Celery backends, along with a Makefile for building and pushing images. The codebase is minimal and focused on the Docker build process; there is no application logic beyond the packaging. The dependencies are pinned and up-to-date, and the repository is actively maintained with recent commits and automated workflows.
This repository contains the Docker packaging and optional Docker Swarm deployment recipes for JumpServer, an open-source bastion host / privileged access management system. It does not contain the JumpServer application source code; instead it composes upstream component images (core, koko, chen, web, kael) into a single all-in-one image and provides the runtime scripts to initialize and supervise them. The all-in-one deployment is explicitly a B/S web-only package and does not support client-related features. The core architecture is the allinone multi-stage Dockerfile, which copies runtime trees from each component image onto the core image, then uses Supervisor to run the Django core service, Koko (SSH/terminal access), guacd, Chen, Kael AI service, and the nginx web frontend. The entrypoint script prepares environment defaults, deterministically derives a service-to-service signing key from BOOTSTRAP_TOKEN when no explicit secret is supplied, migrates per-component data directories into a shared volume via symlinks, waits for database and Redis readiness, and runs the JumpServer schema migration before starting services. The swarm/ directory provides a separate deployment path using Docker Swarm stacks, external MySQL/Redis, healthchecks, and a one-shot init-db job. The code is generally careful within its narrow scope: database initialization is idempotent, local vs external dependency startup is handled cleanly, and the multi-stage image build is a non-trivial composition of separately published images. Maintenance appears active, and the build pipeline watches v5.* tags. Drift is medium: the GitHub Actions workflow uses the deprecated/archived actions/create-release@v1 action, image tags are mutable rather than digest-pinned, and a version string inside allinone/readme.txt lags behind the current default Dockerfile version. There are no tests, but this is deployment glue rather than application logic.
This repository provides a collection of Nix development shell environments for a variety of open-source projects, including Arduino, Firefox, Git, OpenWRT, Yocto, and others. Each environment is defined by a `shell.nix` file that specifies the dependencies, environment variables, and sometimes FHS sandboxing (via `buildFHSEnv`) needed to build or develop that project. The codebase acts as a library of reusable Nix expressions—users can drop into any environment using `nix-shell` or `nix develop`. While not a traditional application, it serves as a practical tool for developers using Nix/NixOS to set up reproducible, self-contained build environments that isolate project-specific dependencies from the host system. The environments vary in complexity from simple `mkShell` wrappers to sophisticated FHS chroots with custom linker settings and variable passthrough (e.g., Yocto). The repository also demonstrates advanced Nix patterns like overriding `stdenv` for LTO (Firefox) and creating wrapper scripts for C standard enforcement (Buildroot).
CacheCloud is a production-grade Redis cluster management platform designed for large-scale operations. It provides full lifecycle management for Redis instances (standalone, sentinel, cluster, twemproxy, pika), including provisioning, deployment, scaling, migration, monitoring, alerting, and diagnostics. The system ingests metrics from Redis INFO, slow logs, latency, client reports, and machine stats, storing them in MySQL and Redis for trend analysis and alerting. It supports automated task workflows for deployment, configuration changes, data migration (via redis-shake/redis-migrate-tool), and key analysis (big keys, hot keys, idle keys, slot distribution). The platform also offers a web UI for administrators and application owners, with role-based access control, audit trails, and email/WeChat notifications. The architecture is a monolithic Spring MVC web application (Java, MyBatis, Quartz scheduler) with a MySQL database and Redis used as a coordination/cache layer. SSH is used for remote command execution and file transfer to managed machines. The frontend uses AdminLTE, Bootstrap, and Highcharts for dashboards. Key entry points include RESTful controllers for app/instance management, a task engine for asynchronous operations, and scheduled jobs for periodic data collection and cleanup. External dependencies include MySQL, Redis, SSH, email/WeChat services, and external tools like redis-shake and redis-migrate-tool. The codebase demonstrates a solid understanding of Redis operations at scale, with extensible alert strategies, a step-based task flow engine, and SSH connection pooling. However, it shows signs of technical debt: hardcoded configurations, deprecated library usage (commons-collections, fastjson), security concerns (SSH passwords in config), and some incomplete or commented-out code. The project is actively maintained with regular SQL migrations and feature additions, but the monolithic structure and environment-specific assumptions limit reusability without adaptation.