thehardwarestore.ai

This repository is primarily an open-source technical book and architecture knowledge base written in Chinese, rendered as a heavily customized VuePress static site. The core deliverable is the book itself — chapters spanning architecture history, distributed systems foundations, transactions, security, observability, service mesh, containers, and cloud-native infrastructure — rather than a runnable software service. It is best classified as a documentation/application hybrid: the only application code is the VuePress site infrastructure, custom plugins, CI/CD scripts, and an embedded resume slide-deck framework. The repository also links to external companion demo projects (Spring Boot, Spring Cloud, Kubernetes, Istio, serverless) rather than hosting them in-tree.

ClawManager is a full-stack, Kubernetes-native control plane for managing AI agent runtimes (OpenClaw, Hermes, OpenCode, DeepSeek Harness, Workbuddy). It provides instance lifecycle management, secure AI gateway proxying with governance and cost tracking, skill management (import, versioning, hub), team collaboration with leader-mediated orchestration, and a comprehensive security protection platform (SecPlane) covering runtime behavior, egress policy, intrusion detection, and compliance reporting. The backend is built in Go with Gin, uses MySQL for persistence, Redis for real-time events, and the Kubernetes client-go library for orchestration. The frontend is a React 19 SPA with TypeScript, Vite, Tailwind CSS, and i18n support for five languages. The repository also includes Playwright-based E2E tests, Docker Compose local development stacks, and a Hermes desktop web component with its own build pipeline. While the codebase demonstrates solid architecture (repository pattern, service layer, middleware), some areas show drift (many SQL migrations, hardcoded dev secrets, incomplete feature flags) and the sheer number of runtime types and configurations introduces complexity.

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.

RBAC Lookup is a CLI tool for Kubernetes that enables users to find all RoleBindings and ClusterRoleBindings associated with a specific user, service account, or group. The tool connects to a Kubernetes cluster via kubeconfig, queries the RBAC API, and presents the results in a tabular format. It includes optional GKE integration to show Google Cloud IAM roles alongside native Kubernetes RBAC roles. The architecture follows a standard Cobra-based CLI pattern with command definitions in cmd/, core lookup logic in lookup/, and data structures defined in lookup/rbac_subject.go. The tool requires access to a Kubernetes cluster and optionally Google Cloud credentials for GKE features.

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.

Apache Dubbo for Kubernetes is a service mesh control plane that extends Apache Dubbo's capabilities to Kubernetes-native environments. It provides an xDS-based control plane (dubbod) for dynamic configuration of gRPC proxies, sidecar injection via a mutating webhook and CNI plugin, mTLS with a built-in certificate authority, and integration with the Kubernetes Gateway API for traffic management. The system also includes a KEDA-based activation mechanism for scale-to-zero workloads, multi-cluster support, and an operator for lifecycle management. The codebase is heavily inspired by Istio, with many packages adapted from that project, and includes a reactive collections framework (krt) for building incremental state from Kubernetes resources. It is in an active development phase with some incomplete features and generated code dependencies.

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.

Diffgram is a full-stack data annotation platform designed for creating, managing, and reviewing annotations on images, video, audio, text, 3D point clouds, and geospatial data. The system is composed of multiple microservices: a Flask-based REST API (`default`), a background processing service (`walrus`) for media ingestion, export generation, and project migration, an event-driven action runner service (`eventhandlers`) that executes automated workflows (e.g., ML model inference, webhooks, exports), and a Vue 2 + Vuetify single-page application frontend. The backend uses PostgreSQL with SQLAlchemy ORM, RabbitMQ for async messaging, and supports multiple cloud storage backends (AWS S3, GCP, Azure, MinIO). Authentication supports OAuth2/Keycloak, API keys, and session cookies with fine-grained role-based permissions. The platform's core domain includes label schemas, attribute groups, instance templates, task/job management with review workflows, discussions/issues, and a custom query engine for filtering files by labels and attributes. It integrates with external AI services (HuggingFace, Vertex AI, Azure Text Analytics) and labeling vendors (Labelbox, Scale AI). The frontend provides rich annotation tools including 2D canvas (boxes, polygons, keypoints), 3D point cloud annotation with Three.js, audio waveform annotation, text token annotation, and geospatial tile annotation. A command pattern enables undo/redo for annotation actions. The codebase demonstrates solid engineering practices with clear separation of concerns, reusable patterns (strategy, observer, command, policy enforcer), and extensive test coverage (Cypress E2E, Jest unit tests, Python unittest). However, there are signs of technical drift: some outdated dependencies, mixed JavaScript/TypeScript in the frontend, and a few legacy modules marked as deprecated. The open-core model is evident from `OPENCORE - ADD` markers, suggesting proprietary extensions. Overall, Diffgram is a mature, actively maintained annotation platform suitable for teams building training data pipelines.

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.

secretgen-controller is a Kubernetes operator that automates the generation and sharing of secrets within a cluster. It defines custom resources (Certificate, Password, RSAKey, SSHKey) that produce corresponding Kubernetes secrets, and provides cross-namespace secret export/import via SecretExport and SecretImport CRDs. Additionally, a SecretTemplate CRD allows constructing secrets from data in arbitrary Kubernetes resources using JSONPath expressions. The controller is part of the Carvel tool suite and is built with controller-runtime, using generated clientsets and informers for both the original secretgen.k14s.io API group and the newer secretgen.carvel.dev group. The architecture follows the standard Kubernetes operator pattern: a single controller binary (cmd/controller/main.go) registers multiple reconcilers for each CRD, plus a SecretReconciler that handles image pull secret merging from exported secrets. Reconcilers use a thread-safe tracker to watch input resources and a generic status helper to update conditions. Secret generation relies on the cloudfoundry/config-server library for cryptographic operations, with FIPS 140-3 support added for SSH key fingerprints and certificate SubjectKeyId. The sharing subsystem maintains an in-memory cache of secret exports with sorting and weight logic to resolve conflicts. The codebase is well-structured with clear separation of concerns, comprehensive end-to-end tests, and a robust CI/CD pipeline. However, it carries some technical debt: two API groups that may diverge, heavy reliance on code generation, and potential performance issues from listing all resources on every relevant event. The use of panic statements in shared code and the custom fork of cloudfoundry/config-server introduce maintenance risks. Overall, it is a production-grade operator suitable for managing secrets in Kubernetes environments.

This repository hosts the documentation and tutorials for Kuboard, a Kubernetes management interface. It is built with VuePress 1.x and serves as a static site via Nginx. The site includes Markdown-based guides covering Kubernetes concepts, Kuboard installation and usage, and practical tutorials for deploying applications. Additionally, it provides version-specific installation scripts for setting up Kubernetes clusters and deploying Kuboard in various configurations (standalone, HA, etc.). The documentation is organized into sections such as Overview, Installation, Learning, Guide, and Support, making it a comprehensive resource for Kubernetes users.

This repository is the official Helm chart distribution hub for Grafana's observability stack, containing over 20 charts for deploying Loki, Tempo, Mimir, Promtail, Grafana Agent, enterprise metrics/logs, and supporting components (rollout-operator, pdc-agent, snyk-exporter, etc.) on Kubernetes. The codebase is entirely Helm templates, values files, CRDs, and CI/CD scripts—no application source code. The architecture follows standard Helm patterns with per-component subdirectories, shared helpers, and extensive use of conditional logic for enterprise features, scaling, and storage backends. Many charts are deprecated or have their source maintained in separate product repositories (e.g., grafana/loki, grafana/tempo), with releases still published here. The repository shows signs of technical drift (old API versions, duplicated template logic, legacy dependencies) but remains actively maintained for the remaining non-deprecated charts with recent CI updates and release automation. It serves as both a legacy archive and an active distribution point.

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 repository provides documentation and automation scripts for setting up a Kubernetes cluster from scratch using VirtualBox. It includes shell scripts for creating and configuring VM images with cloud-init, configuration files for various Kubernetes components (etcd, control plane, worker nodes, HAProxy load balancers), and detailed documentation explaining the setup process. The repository serves as an educational guide for understanding Kubernetes infrastructure components and how they interact, rather than a deployable application itself. The main value lies in the well-structured automation scripts and comprehensive documentation that walk users through building a complete Kubernetes cluster with high availability features.

kubectl-df-pv is a kubectl plugin that displays disk usage (like the Unix `df` command) for Kubernetes Persistent Volumes. It retrieves storage metrics from each node's kubelet stats/summary endpoint and presents them in a color-coded, human-readable table. The tool handles concurrent node queries using goroutines and channels, supports filtering by namespace, and allows users to select which columns to display (including inode information). It auto-converts byte sizes to IEC binary prefixes (Ki, Mi, Gi, Ti) and colorizes usage percentages (red > 75%, yellow < 25%, green otherwise). The codebase is a single Go binary using Cobra for CLI parsing, client-go for Kubernetes API interaction, and go-pretty for table rendering. It is a well-structured, focused utility that solves a specific operational need for Kubernetes administrators. While the core logic is solid, the project is relatively simple and does not exhibit exceptional architectural depth or highly reusable components beyond basic byte formatting.

This repository hosts the source code for '深入高可用系统原理与设计' (Deep dive into high availability system principles and design), a technical book covering system architecture, networking, distributed systems, and cloud-native technologies. The content is organized as a VuePress documentation site, transforming markdown files into a navigable web book with features like dark mode toggle, star tracking, and comment integration. The application architecture follows a standard VuePress static site generator pattern: markdown content is processed through VuePress with custom plugins and styling to produce a deployable static website. Key components include a customized layout that adds book-specific elements (purchase QR code, star counter) and implements reactive dark mode detection using MutationObserver. The site is built and deployed via GitHub Actions to an Aliyun server. While the repository excels in content organization and documentation clarity, the underlying VuePress implementation shows some technical drift due to reliance on outdated release-candidate versions of core dependencies. Nevertheless, it demonstrates solid engineering practices in its customizations, particularly in the reusable styling enhancements found in .vuepress/styles/index.scss which address documentation-specific needs like image centering, responsive content width, and print optimization.

This repository is a collection of hands-on practice labs for the Certified Kubernetes Administrator (CKA) exam. It is not a software application or data pipeline but a study resource consisting of bash scripts and Kubernetes YAML manifests. Each lab (Question-*) contains a LabSetUp.bash that creates a realistic cluster scenario, a Questions.bash describing the task, and a SolutionNotes.bash with step-by-step solutions. The scripts/run-question.sh orchestrates setup and display. The code is straightforward and functional, with no complex architecture or reusable components beyond the lab context. It relies on a running Kubernetes cluster (e.g., Killercoda) and standard tools like kubectl and helm. The repo is actively maintained (last commit dated 2026-05-12, though this may be a data anomaly) and has low technical drift, using recent Kubernetes versions and practices.

This repository is a curated list of OpenTelemetry resources, maintained as a static markdown file (readme.md). It serves as a reference for developers and engineers seeking to learn about OpenTelemetry, including books, videos, blogs, instrumentation guides, and vendor solutions. The repository does not contain any executable code or data processing logic; instead, it organizes external links into thematic sections for easy consumption. The project is actively maintained, with recent commits and community engagement (as indicated by stars, forks, and open issues). It follows standard open-source practices with a license, code of conduct, and contributing guidelines. Technically, there is no drift to assess as the repository consists solely of documentation and configuration files without external dependencies. While the repository lacks reusable software components, its value lies in the curation and presentation of OpenTelemetry knowledge. The markdown structure is clean and navigable, making it a useful starting point for anyone exploring the OpenTelemetry ecosystem.

This repository is a comprehensive collection of example applications for the Apache KIE ecosystem, specifically Kogito, Drools, and jBPM. It demonstrates how to build cloud-native business automation services using DMN decision models, PMML predictive models, DRL rules, and BPMN process orchestration. The examples are structured as runnable microservices for both Quarkus and Spring Boot runtimes, covering a wide range of capabilities including event-driven messaging with Kafka, persistence with PostgreSQL/MongoDB/Infinispan, security with Keycloak OIDC, monitoring with Prometheus/Grafana, and deployment on Kubernetes/OpenShift. The repository serves primarily as a learning and demonstration resource, not as a production library. It features high duplication across the two runtime stacks, with many near-identical examples maintained in parallel. The code is functional and follows standard Kogito patterns, but the emphasis is on showcasing features rather than providing reusable, production-grade components. Some examples use snapshot versions and older infrastructure configurations, indicating active development but also potential drift.