Kubernetes Cluster Backup and Recovery

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 disparate external links and documentation into a single, version-controlled collection, it provides a clear navigation path for users seeking specialized utilities, ranging from runtime engines and registry tools to advanced supply chain security and observability solutions. Beyond its role as a tool index, the directory supports professional growth by offering a broad surface of learning resources, including tutorials, best practices, and community-vetted guides. It covers essential operational domains such as multi-container workload management, image hardening, and workflow optimization, ensuring that both newcomers and experienced practitioners have access to a reliable reference for modern containerized systems.

ToolJet is a low-code development platform designed for building and deploying internal business applications. It provides a visual interface where users can drag and drop components to design layouts, connect to various data sources, and execute custom logic. The platform is built on a containerized architecture, ensuring that applications remain portable and consistent across different cloud and server environments. The platform distinguishes itself through integrated artificial intelligence capabilities that assist in the generation of user interfaces, database schemas, and data queries from natural language requirements. Beyond interface design, it includes a backend orchestration engine that automates complex business processes by chaining together API calls, database operations, and conditional logic. Developers can also manage the entire application lifecycle, including version control, multi-environment deployments, and granular role-based access security. The system supports a broad range of operational needs, including built-in relational database management, external service integrations, and observability tools for monitoring performance. It also offers mechanisms for embedding interactive tools into third-party websites and managing user authentication through identity provider synchronization. The platform is designed for containerized deployment and provides comprehensive documentation for installation, infrastructure configuration, and version upgrades.

This project is a command-line utility designed for secure, content-addressable data archiving. It functions as an encrypted backup tool that stores data as deduplicated chunks, ensuring that every piece of information is identified by a cryptographic hash to maintain integrity across all backups. By applying strong encryption and message authentication codes to both data and metadata, the software prevents unauthorized access and detects potential tampering. The tool distinguishes itself through a backend-agnostic storage abstraction that allows users to maintain repositories across diverse environments, including local filesystems, network-attached storage, and various cloud object storage providers. It optimizes storage efficiency and network performance by aggregating small data chunks into structured pack files and utilizing index-based metadata lookups. To further improve performance, the system maintains a local cache of repository indexes, which accelerates search operations and reduces latency during backup analysis. Beyond its core storage capabilities, the software supports automated backup orchestration and disaster recovery planning through versioned snapshots. It provides a comprehensive set of management tools for inspecting repository objects and configuring secure connections to remote backends via standard protocols. The software is distributed as a portable binary, with support for installation through native package managers, containerized execution, and cross-compilation from source.

h2o-3 is a distributed machine learning platform and automated machine learning framework designed for training and deploying predictive models using distributed in-memory computing. It functions as a deep learning framework and a distributed model scoring engine, capable of operating as a Kubernetes ML cluster to process large datasets in parallel. The platform distinguishes itself through automated machine learning capabilities that automatically select the best algorithms and hyperparameters to optimize model performance. It provides specialized deep learning toolkits for tasks including image classification, anomaly detection, and image reconstruction and clustering. The system covers a broad range of capabilities including large-scale data processing via map-reduce and distributed key-value stores, and model explainability analysis to interpret predictions. Its model management suite supports the serialization of trained models into standalone artifacts for high-performance production scoring, alongside a registry for model logging and lifecycle orchestration. Deployment and orchestration are supported via Kubernetes stateful sets, Hadoop integration, and a web-based management interface.

K3s is a lightweight Kubernetes distribution designed for resource-constrained environments, edge computing, and simplified deployment across diverse hardware architectures. It functions as a container orchestration engine that automates the deployment, scaling, and management of containerized applications. By bundling all necessary control plane components and dependencies into a single binary, it minimizes the system footprint and streamlines the installation process. The project distinguishes itself through a flexible architecture that supports both high-availability clustering and minimal, single-node setups. It provides options for using an embedded SQLite datastore for small deployments or external databases for larger, resilient environments. Security is integrated into the core, featuring token-based node authentication, encrypted communication between nodes, and support for mandatory access control policies like SELinux. The platform covers a broad operational surface, including automated cluster version upgrades, manifest-based resource deployment, and integrated Helm chart management. It offers extensive configuration capabilities for networking, certificate management, and storage backends, allowing administrators to tailor the environment to specific infrastructure requirements. The system is designed to maintain consistent operational standards across distributed locations, ensuring that management remains centralized even when hardware resources are limited.

MinIO is a software-defined, cloud-native object storage server designed to manage large volumes of unstructured data. It functions as a distributed storage cluster that aggregates multiple independent nodes into a unified, scalable pool, providing a high-performance infrastructure compatible with standard cloud storage protocols and application programming interfaces. The system utilizes a shared-nothing architecture that eliminates central metadata servers, relying instead on a decentralized hash table to map objects across the cluster. Data availability and resilience are maintained through erasure coding, which distributes data fragments across multiple drives to protect against hardware failure. To ensure long-term data integrity, the system performs continuous background scanning to detect and repair silent corruption. It also supports multi-tenant environments by providing logical isolation for buckets and user credentials, allowing for secure, self-hosted data management across private or hybrid cloud deployments. Beyond its production capabilities, the software provides a consistent environment for local development and testing of data-intensive applications. Administrative tasks, cluster monitoring, and data operations are managed through a unified command-line client or an embedded web-based browser. The software can be deployed by building container images or by compiling the source code directly.

proot-distro is a rootless container runtime and Linux distribution manager that allows users to install and run isolated guest environments without requiring administrative root privileges. It utilizes PRoot to simulate root access and filesystem redirection, enabling the deployment of full Linux distributions in a non-root space. The project functions as an OCI container image handler, capable of building, pulling, and pushing OCI-compatible images and manifests. It further serves as a cross-architecture execution layer, utilizing user-mode emulation to run binaries and containers built for different CPU architectures. The tool covers a broad range of container lifecycle capabilities, including session monitoring and process-tree management to ensure clean shutdowns. It also provides data storage utilities for backing up, restoring, and synchronizing files between the host and guest environments.

TiDB is a horizontally scalable, distributed SQL database designed to provide consistent transactional storage and high-performance analytical processing within a single unified architecture. It utilizes a decoupled compute-storage design and a distributed key-value storage layer to ensure horizontal scalability and efficient range-based queries. By employing a consensus-based replication algorithm, the system maintains high availability and automatic failover across multiple nodes and geographical regions. The platform distinguishes itself through its hybrid transactional and analytical processing capabilities, which allow complex SQL queries to run against replicated columnar data without disrupting primary transactional workloads. It also integrates high-dimensional vector search functionality, enabling semantic similarity queries directly alongside traditional relational data. To support diverse operational needs, the system provides native tools for real-time data streaming, seamless migration from external database systems, and multi-region disaster recovery. The database is built for cloud-native environments, offering comprehensive lifecycle management through Kubernetes operators that automate deployment, scaling, and rolling upgrades. It maintains compatibility with standard SQL interfaces, allowing applications to connect using common drivers while managing complex concurrency through pessimistic transaction handling. Detailed documentation and command-line utilities are available to assist with cluster orchestration, performance troubleshooting, and the configuration of production-grade topologies.

kops is a Kubernetes cluster provisioner and lifecycle manager designed to automate the creation, maintenance, and destruction of production-grade clusters on cloud infrastructure. It functions as a declarative infrastructure manager, synchronizing the live state of a cluster with versioned manifests stored in remote object storage to ensure idempotent operations. The project distinguishes itself by offering comprehensive automation for the entire cluster lifecycle, including high-availability control plane deployment, incremental rolling updates, and automated version upgrades. It also serves as an infrastructure-as-code exporter, capable of generating Terraform configurations from the current state of a deployed cluster. Beyond provisioning, it covers a broad operational surface including automated node and pod scaling, etcd data store management, and complex networking configurations such as dual-stack IPv6 and CNI integration. It also manages identity and security through OIDC authentication integration, cloud IAM role mapping, and x509 certificate lifecycle management. The tool provides a command-line interface with support for shell autocompletion.

Kubernetes is a distributed container orchestration platform that automates the deployment, scaling, and management of containerized applications across clusters of computing nodes. It functions as a declarative infrastructure controller, utilizing a control loop architecture that continuously monitors the current system state against user-defined configurations to ensure desired operational outcomes. The system relies on a centralized API-driven interface and a replicated key-value store to maintain a consistent source of truth for all cluster objects. The platform distinguishes itself through a highly extensible design that allows users to define domain-specific objects using the same native API and control loop infrastructure. It employs a standardized abstraction layer for container runtimes, enabling modular execution engines, and utilizes a pluggable controller pattern that supports third-party integrations without requiring modifications to the core codebase. An algorithmic bin-packing engine further optimizes hardware utilization by dynamically matching workload requirements with available cluster capacity. Beyond core orchestration, the system provides comprehensive operational support for distributed environments, including automated lifecycle management, horizontal and vertical scaling, and self-healing mechanisms that maintain service availability. It encompasses integrated solutions for networking, persistent storage orchestration, and secure secret management. Diagnostic utilities for monitoring performance metrics, aggregating logs, and troubleshooting infrastructure-level issues are also included to support cluster health and reliability.

AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster engine for horizontal scalability and synchronous replication with automatic failover. It also provides an integrated high-availability solution through InnoDB Cluster, combining Group Replication, MySQL Router, and MySQL Shell for deploying fault-tolerant clusters. Additional differentiators include support for vector similarity search using HNSW indexing, a NoSQL document store API for JSON collections, and the HeatWave in-memory columnar query accelerator. Beyond these core differentiators, AliSQL covers the full breadth of MySQL capabilities: comprehensive API integration across .NET, C, C++, Java, Node.js, ODBC, PHP, and Python; data backup and restore with incremental, online, and cloud storage options; data replication and sync via Group Replication and GTID-based replication; and security features including encryption, authentication (LDAP, Kerberos, PAM), data masking, and auditing. It also includes tools for database administration, monitoring, performance optimization, and Kubernetes-based deployment and orchestration. The project is documented through the standard MySQL documentation surface, covering installation, configuration, and administration of the server and its associated tools.

Minikube is a command-line tool designed for local Kubernetes development, enabling users to provision and manage full-featured container clusters directly on a workstation. It serves as a local orchestrator that automates the lifecycle of isolated environments, allowing developers to start, stop, pause, and delete clusters to support testing and integration workflows. The project distinguishes itself through its flexible architecture, which supports multiple virtualization drivers and container runtimes to accommodate diverse host environments. It provides deep integration between the host and the cluster, including bidirectional filesystem mounting, service tunneling for local access, and the ability to build or load container images directly into the cluster runtime. Furthermore, it supports multi-node cluster management and profile-based configuration, allowing users to maintain separate, isolated environments for different projects. Beyond core orchestration, the tool covers a broad range of operational capabilities including dynamic storage provisioning, network policy enforcement, and hardware acceleration for specialized workloads like artificial intelligence. It also includes administrative features such as audit logging, secure authentication, and a web-based dashboard for monitoring cluster health and resource status. The project is distributed as a command-line utility that provides versioning to ensure compatibility between the management interface and the running cluster.

Duplicati is a self-hosted backup server designed to perform encrypted, incremental, and compressed backups to a wide range of local, network, and cloud-based storage providers. It functions as a background service that automates recurring data protection tasks, ensuring that only changed data blocks are stored to maximize efficiency and minimize bandwidth usage. The project distinguishes itself through a centralized management console that allows for the orchestration of multiple distributed backup agents from a single web-based dashboard. It supports multi-tenant management, enabling the organization of users and resources into hierarchical structures for delegated access and data isolation. Furthermore, it provides robust security features, including AES-256 encryption for data at rest, support for OIDC and SAML2 authentication, and provider-level immutability protections to prevent unauthorized modification of backup archives. Beyond its core backup capabilities, the system includes comprehensive tools for data lifecycle management, such as automated retention policies, versioning, and integrity verification. It offers flexible configuration through both a graphical interface and a command-line utility, supporting automation scripting and dry-run simulations to verify workflows before execution. The software also handles complex environments by managing locked files and providing metadata indexing to ensure rapid restoration even if the primary configuration database is unavailable. Duplicati is available through various installation formats, including native system packages, portable archives, and containerized deployments, allowing it to run in diverse operating environments.

Immich is a self-hosted media management platform designed to provide a centralized, private repository for photos and videos. It functions as a comprehensive system for organizing, backing up, and viewing personal media collections across mobile devices, web browsers, and external storage locations. By maintaining full control over data ownership and storage infrastructure, the platform ensures that users retain sovereignty over their digital assets. The system distinguishes itself through a distributed architecture that coordinates background media synchronization, real-time filesystem monitoring, and automated deduplication. It leverages an integrated machine learning pipeline to perform intelligent asset organization, including facial recognition, object detection, and metadata extraction. These processes are executed through containerized service orchestration, which manages complex dependencies and hardware-accelerated tasks within isolated environments. Beyond core management, the platform provides extensive tools for disaster recovery and library maintenance. Users can configure automated database backups, manage external storage volumes, and define granular synchronization policies for mobile devices. The system also includes command-line utilities for secure remote operations, such as authenticated asset uploading and server version verification, ensuring compatibility and consistency across distributed deployments.

Dokploy is a self-hosted platform-as-a-service designed to simplify the deployment and management of containerized applications and databases. It provides a centralized control plane that decouples administrative management from application workloads, allowing users to oversee infrastructure across multiple server nodes through a unified web interface or a command-line tool. The platform distinguishes itself through an extensive library of pre-configured application templates, enabling the rapid deployment of databases, identity providers, and various productivity or development tools. It supports complex orchestration by allowing users to define multi-container services using standard configuration files, which can be managed through automated build pipelines, Git integration, and real-time performance monitoring. Beyond core deployment, the system includes robust infrastructure management capabilities such as automated backups to external object storage, horizontal and vertical scaling, and granular access control. It also provides secure configuration management, including environment variable synchronization, HTTPS certificate handling, and zero-downtime deployment strategies to ensure application stability and security. The platform is designed for ease of use, offering an interactive API documentation interface and instructional resources to guide users through installation and configuration. It supports a wide range of modern web frameworks and runtimes, providing a flexible environment for hosting and maintaining services on private server hardware.

Colima is a command-line utility that provides lightweight container runtimes and local Kubernetes orchestration by managing isolated virtual machine environments. It functions as a virtualization manager that abstracts the underlying container engine, allowing users to run containerized applications and system workloads on non-native operating systems without the overhead of heavy desktop software. The project distinguishes itself through its support for hardware-accelerated workloads, enabling direct GPU passthrough to virtual machines for high-performance machine learning tasks. It offers robust profile-based configuration management, which allows users to maintain multiple independent runtime instances with dedicated resources, and supports seamless switching between different container engines to suit specific development requirements. Beyond core container and orchestration management, the tool provides comprehensive control over virtual machine lifecycles, including persistent volume mapping and resource optimization for CPU, memory, and disk usage. It facilitates secure interaction with these environments through socket forwarding and direct shell access, ensuring that developers can monitor and debug isolated instances effectively. Colima is distributed as a command-line tool that automates the initialization and configuration of virtualized environments through simple flags and configuration files.

Angel is a distributed machine learning framework and graph computation engine designed to train predictive models and execute algorithms across a cluster of servers. It functions as a distributed parameter server that synchronizes model weights and gradients across multiple machines to handle massive datasets. The system provides a production environment for model inference deployment to provide real-time predictions for end users. It integrates with Spark to run machine learning workflows and data processing pipelines through a compatible interface. The framework covers distributed graph computation for tasks such as PageRank and community detection, as well as automatic hyperparameter optimization to improve model accuracy. It includes capabilities for coordinating distributed training, partitioning model data, and orchestrating cluster resources via container-based scheduling.

This project is a command-line storage manager that provides a unified interface for performing file operations across local filesystems and diverse cloud storage providers. It functions as a cross-platform storage abstraction, utilizing a modular backend architecture to map heterogeneous cloud storage APIs into a standard set of file system operations. This allows for consistent data management and movement regardless of the underlying storage service. The tool serves as a network data transfer engine designed for automated data migration and cloud storage synchronization. It distinguishes itself by offering granular control over transfer behavior, allowing users to manage bandwidth, logging, and file handling rules through global command-line flags. Furthermore, it includes a metadata transformation pipeline that intercepts and modifies file attributes during transit to ensure compatibility and consistency between disparate storage environments. Beyond core synchronization, the software provides secure remote file management by enforcing strict authentication and encrypted network communication protocols. It includes diagnostic instrumentation to monitor system performance, enabling users to analyze resource usage and identify bottlenecks during large-scale data operations. Users can configure and persist storage backend credentials through an interactive command-driven utility.

This project is a reference implementation of a distributed system built using Spring Cloud Alibaba, Spring Boot, and JDK 17. It serves as a comprehensive model for implementing a microservices architecture. The system integrates a wide range of distributed patterns, including global transaction coordination for data consistency, OAuth2 and JWT for identity management, and Kubernetes-based container orchestration. It features a dedicated observability stack for distributed request tracing, log aggregation, and service health monitoring. The implementation covers several functional domains, including e-commerce operations such as product inventory management, order processing, and marketing campaign execution. It also incorporates technical capabilities for asynchronous message queuing, distributed data caching, full-text search, and cloud object storage. The project provides deployment templates for Kubernetes to manage the scaling and reliability of the microservices cluster.

Alist is a unified cloud storage gateway that aggregates disparate remote storage providers into a single, navigable virtual file system. By acting as a remote file system proxy, it decouples file operations from specific provider implementations, allowing users to browse, download, and manage files across heterogeneous backends through a standardized interface. The platform utilizes a driver-based storage abstraction that translates generic file system operations into provider-specific API calls. This architecture supports a wide range of cloud storage services, S3-compatible object storage, and software release assets, presenting them as a cohesive directory structure. To ensure data privacy, the system includes an encrypted data vault that provides transparent, password-based obfuscation for file and directory names across remote platforms. The system operates as a stateless gateway, dynamically fetching metadata without maintaining persistent local copies of the underlying content. It employs a modular middleware layer to handle on-the-fly data transformations, such as the encryption and decryption of file metadata, while maintaining a consistent interaction model across all connected storage backends.