12 repository-uri
Configurations for running containerized applications on managed cloud orchestration services.
Distinguishing note: Specific to managed cloud container services rather than generic container orchestration.
Explore 12 awesome GitHub repositories matching devops & infrastructure · Cloud Container Deployments. Refine with filters or upvote what's useful.
Infisical is a centralized secrets management platform designed to store, synchronize, and control access to sensitive credentials and configuration data across distributed development, staging, and production environments. It employs client-side encryption to ensure that secrets remain unreadable to the underlying storage infrastructure, while providing a hierarchical permission model to govern both user and machine access. The platform distinguishes itself through dynamic credential provisioning, which generates short-lived access tokens that are automatically revoked after use. It supports
Runs the application on managed container services with production-ready traffic routing.
This project is a Docker educational resource and a collection of practical examples designed for learning containerization technologies. It serves as a guide for understanding container fundamentals, including the creation and management of custom images and the use of registries. The repository provides specialized references for container security hardening, such as managing kernel privileges and implementing supply chain security. It also includes tutorials for multi-container orchestration and a DevOps guide focused on CI/CD automation and image optimization. The material covers a broad
Provides configurations for running containerized workloads on managed cloud orchestration services.
This project is a recommendation system framework designed for building, evaluating, and operationalizing personalized item suggestion engines. It provides a comprehensive toolkit for implementing collaborative filtering and content-based algorithms, supported by an end-to-end machine learning pipeline for preparing datasets and deploying predictive models. The framework distinguishes itself through the integration of knowledge graphs to provide richer context for recommendations and the use of industry-specific patterns to accelerate system deployment. It also includes a specialized model ev
Supports the deployment of recommendation models to production using container orchestration and cloud databases.
Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep
Executes tasks within isolated Azure container instances.
Datasette is a tool for publishing and sharing SQLite databases as public websites. It functions as a data publishing system that provides searchable interfaces and JSON APIs to expose the contents of SQLite files. The project enables both server-side and client-side execution. It can operate as an API server or as a database browser that runs entirely within a web browser using WebAssembly, allowing for serverless database access. The system supports a variety of deployment strategies, including containerized images for cloud hosting and a local development server for testing. It includes c
Packages databases and the application into container images optimized for cloud platform deployment.
SD.Next is an all-in-one web interface and multi-backend inference engine for generating, editing, and processing images and videos using diffusion models. It functions as a comprehensive tool for diffusion model management and an automated image processing pipeline for bulk operations. The project is distinguished by its hardware-backend abstraction layer, which provides automatic detection and acceleration for NVIDIA CUDA, AMD ROCm, Intel OpenVINO, and DirectML. It features a headless generative API and a programmatic command interface, allowing users to trigger tasks via REST API or CLI wi
Supports running the application in containers on managed cloud orchestration services with public hostname exposure.
This is a step-by-step tutorial that teaches Docker from the ground up, covering how to build images from Dockerfiles, run and manage containers, and connect them on user-defined networks. The guide walks through packaging applications into portable containers and using Docker Compose to define and orchestrate multi-service applications with a single YAML configuration. The curriculum extends into cloud deployment, explaining how to push images to registries like Docker Hub and deploy single-container applications to AWS Elastic Beanstalk as well as multi-container setups to AWS ECS. It also
Explains deploying containerized applications to AWS Elastic Beanstalk and ECS.
Acest proiect este o bibliotecă de referință și o colecție de tipare de cod exemplificative pentru implementarea infrastructurii cloud folosind AWS CDK. Oferă un set de proiecte eșantion care demonstrează cum să definești resurse de calcul, stocare și rețea folosind limbaje de programare de uz general. Biblioteca include implementări de referință pentru diverse tipare arhitecturale, inclusiv backend-uri serverless cu API-uri GraphQL și WebSocket, orchestrarea containerelor cu load balancers și auto-scaling, și găzduirea globală de site-uri web statice prin rețele de livrare a conținutului (CDN). De asemenea, oferă design-uri pentru topologii de rețea izolate și automatizarea fluxurilor de lucru bazate pe evenimente folosind mașini de stare. Capabilitățile acoperite se extind la gestionarea bazelor de date relaționale, configurarea serverelor de transfer securizat de fișiere și implementarea autorizării granulare. În plus, exemplele demonstrează tehnici de personalizare a infrastructurii, cum ar fi suprascrierea proprietăților resurselor și integrarea resurselor personalizate.
Demonstrates the deployment of containerized applications on managed cloud orchestration services.
This project provides a collection of official base images for building and running .NET applications across various operating systems and hardware architectures. It includes standardized runtime environments, containerized development kits, and specialized images designed for isolated application execution. The collection is distinguished by its focus on image optimization and security hardening. It offers distroless images that remove shells and package managers to reduce the attack surface, as well as composite layering and ahead-of-time compilation to improve startup performance and lower
Enables launching optimized container images into managed cloud-hosting environments for scalable application hosting.
Google Cloud Go Client Library este un set de pachete Go și un kit de dezvoltare software utilizat pentru a interacționa cu serviciile și API-urile platformei Google Cloud. Acesta oferă mijloacele principale pentru ca aplicațiile Go să se integreze cu endpoint-urile serviciilor cloud prin modele de limbaj simplificate și gestionarea automată a cererilor API. Proiectul include biblioteci specializate pentru gestionarea identității și accesului prin conturi de serviciu, chei API și rezoluția acreditărilor bazată pe mediu. Include SDK-uri dedicate pentru orchestrarea programatică a resurselor și implementarea și gestionarea funcțiilor serverless, job-urilor containerizate și serviciilor web scalabile. Suprafața de capabilități a bibliotecii acoperă gestionarea datelor în cloud pe baze de date relaționale, NoSQL și stocare de obiecte, precum și orchestrarea infrastructurii pentru mașini virtuale și containere. De asemenea, oferă instrumente pentru dezvoltarea AI generativ, analiza datelor la scară largă și monitorizarea aplicațiilor cloud prin capturarea log-urilor și urmărirea erorilor.
Facilitates the deployment and scaling of containerized applications on managed cloud orchestration services.
Practicalnode is a comprehensive educational resource and backend development framework for mastering server-side programming with Node.js. It provides a structured approach to building scalable network services, REST APIs, and real-time applications using asynchronous JavaScript. The project serves as a detailed implementation guide for several core backend patterns, including MongoDB data modeling and the construction of REST API development kits. It emphasizes a specific workflow for Docker containerization and offers a variety of strategies for managing user identity through stateless tok
Provisions and scales cloud-based compute clusters to host and monitor containerized services in production.
This project is a comprehensive library of reference implementations and patterns for building web applications using the Go Fiber framework. It provides curated templates and implementation guides for creating REST APIs, web servers, and structured backend services. The repository serves as a practical resource for applying architectural patterns, including Clean and Hexagonal architectures, as well as port-and-adapter decoupling. It offers detailed examples for integrating common web features such as OAuth2 authentication, JWT verification, WebSockets for real-time communication, and server
Provides configurations and manifests for deploying containerized applications to managed cloud orchestration services.