9 dépôts
Utilities for packaging and exporting application functions to managed cloud environments.
Distinct from Local Function Execution: Distinct from Local Function Execution: focuses on the deployment and export process to cloud providers rather than local simulation.
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Quarkus is a Kubernetes-native Java framework designed for building high-performance, memory-efficient applications. It utilizes ahead-of-time native compilation to transform Java code into standalone, optimized binaries that eliminate the need for a virtual machine, enabling rapid startup and reduced memory consumption. By performing code augmentation during the build phase, it shifts heavy processing tasks away from runtime, ensuring that applications are optimized for cloud-native environments. The framework distinguishes itself through a unified approach to reactive and imperative program
Packages and exports application functions for execution within the AWS Lambda environment using standard or native runtimes.
This repository provides a comprehensive library of code examples for implementing event-driven, serverless backend architectures. It serves as a practical guide for building scalable cloud-native applications that execute logic in isolated environments, triggered by infrastructure events or HTTP requests rather than persistent server processes. The collection demonstrates how to leverage managed infrastructure to automate backend workflows, including the use of asynchronous task queuing to maintain system stability during high traffic. It highlights patterns for secure API hosting, enabling
Offers a collection of code examples demonstrating how to implement event-driven logic and serverless backend tasks.
Nango is an open-source platform that connects applications to external APIs by managing authentication, data synchronization, and custom function execution. It provides a managed runtime for TypeScript integration functions, handling OAuth flows, credential storage, and token refresh for hundreds of external APIs while keeping secrets isolated from application code. The platform distinguishes itself by exposing integration functions as discoverable tools for AI agents through an MCP server or API, with per-user credential isolation that keeps provider secrets out of the agent loop. It offers
Uploads TypeScript integration functions to a managed runtime for synchronous or asynchronous execution.
This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ
Enables the creation, testing, and deployment of Python functions from local environments to remote cloud workspaces.
AngularFire is a set of tools for connecting applications to Firebase services. It provides a library of client-side interfaces for managing authentication, object storage, NoSQL databases, and serverless functions. The project utilizes observables and dependency injection to integrate cloud services into the application hierarchy. It features a reactive interface for streaming real-time data, managing document-based databases, and tracking authentication state as a continuous stream of tokens. The platform covers a broad range of cloud capabilities, including identity verification, binary f
Provides utilities for packaging and deploying serverless functions to cloud providers.
Laf is a serverless backend platform that provides an integrated environment for cloud functions, a document database, and file storage. It serves as a complete infrastructure for developing and deploying backend logic, data persistence, and real-time communication without the need for manual server management. The platform features a browser-based IDE that allows developers to write, test, and deploy serverless functions directly within a web editor, removing the requirement for local environment setup. It also includes a WebSocket communication platform for maintaining persistent bidirectio
Provides utilities for writing and pushing backend code directly to a managed cloud environment for serverless execution.
opennextjs-aws est un adaptateur d'infrastructure serverless et un outil de déploiement qui transforme les artefacts de build Next.js en paquets compatibles pour l'hébergement sur AWS Lambda et S3. Il fonctionne comme un adaptateur de déploiement qui mappe les sorties spécifiques au framework vers des fonctions serverless et du stockage d'objets. Le projet se distingue par l'implémentation d'optimisations spécifiques au serverless, y compris un gestionnaire de cache qui synchronise la régénération statique incrémentale et les caches de récupération (fetch) via S3 ou DynamoDB. Il dispose d'un optimiseur de démarrage à froid (cold start) qui utilise la minification de bundle et le réchauffement programmé des fonctions pour réduire la latence, ainsi qu'un pipeline d'optimisation d'images dédié pour récupérer les fichiers sources depuis S3 et les distribuer via CDN. Le système couvre un large éventail de capacités, y compris l'intégration de middleware edge, la revalidation en arrière-plan basée sur des files d'attente et la distribution de routes multi-cibles. Il gère également le trafic via le routage CDN, l'injection de données de géolocalisation et le streaming de réponses serveur pour améliorer le temps jusqu'au premier octet (TTFB). L'outil fournit des options de personnalisation étendues pour les pipelines de build, les comportements des adaptateurs et la logique serveur afin de prendre en charge des besoins architecturaux variés et des structures monorepo.
Transforms build artifacts into deployable packages compatible with serverless functions, edge workers, or Node.js servers.
This project is a set of hands-on labs for practicing cloud development, focusing on implementing web apps, functions, storage solutions, and containerized workloads. It provides a practical framework for developing solutions within the Azure ecosystem. The content covers a wide range of specialized cloud capabilities, including serverless development with HTTP and timer triggers, container orchestration using apps and instances, and API management for routing and transforming traffic. It also emphasizes identity and access management through OpenID Connect and managed identities. Additional
Provides tools and workflows for publishing local serverless function projects to cloud environments.
L'AWS Lambda Runtime Interface Emulator est un serveur proxy conçu pour répliquer l'environnement d'exécution serverless basé sur le cloud au sein d'un conteneur local. Il fonctionne comme une interface légère qui permet aux développeurs de vérifier la logique de la fonction, les performances et l'intégration API en simulant le plan de contrôle distant et le modèle d'invocation d'événements sur une machine locale. L'outil opère en interceptant les requêtes HTTP et en les traduisant en charges utiles d'événements JSON structurées attendues par les gestionnaires de fonctions serverless. Il gère le cycle de vie de la fonction via une boucle d'événements synchrone et mappe les paramètres de configuration locaux, incluant les identifiants de sécurité et les métadonnées, directement dans l'espace de processus du conteneur pour assurer la parité avec les environnements de production. Au-delà des tests de fonctions standard, l'émulateur prend en charge la validation d'extensions et d'agents personnalisés en fournissant une implémentation fonctionnelle de l'interface runtime. Cela permet de tester des applications serverless conteneurisées et leurs composants associés avant qu'ils ne soient déployés dans le cloud.
Proxies requests to a local container to simulate cloud runtime environments for verifying function logic and performance.