Search Results for "project code for cloud computing"
Sort By:
71 projects for "project code for cloud computing" with 1 filter applied:
-
IT Asset Management (ITAM) SoftwareDrowning in misplaced IT assets, compliance headaches, and shadow IT? Navigate to clarity with an intuitive IT Asset Management solution. Experience crisp visibility, effortless control, and unshakable security – all while freeing up your budget with optimized software licenses. The best part? It’s easy.
-
Modernize Your Lab with the #1 Rated LIMSNothing is more critical to a lab’s success than the quality, security, and traceability of samples. The Lockbox LIMS system provides robust sample management functionality to laboratory professionals, giving them full visibility on every aspect of a sample’s journey, from accessioning to long-term storage.
-
1
Cloud CLI
Use Claude Code, Cursor CLI or Codex on mobile and web with CloudCLI
ClaudeCodeUI, also known as CloudCLI, is an open-source web and mobile interface that enables developers to control Claude Code and similar AI coding tools through a graphical environment. The project provides a browser-based dashboard that allows users to manage coding sessions, projects, and prompts remotely from virtually any device. It is designed to bridge the gap between terminal-first AI coding workflows and more accessible visual interfaces, improving usability without sacrificing... -
2
Cloud Foundation Toolkit Project
The Cloud Foundation toolkit provides GCP best practices as code
Cloud Foundation Toolkit is a best-practices-as-code project intended to help teams build and manage Google Cloud environments in a more standardized, production-ready way. At its core, it combines a comprehensive set of Terraform blueprints with developer tooling that supports the creation and management of those blueprints. The repository is aimed at infrastructure teams that want reusable, policy-aligned starting points instead of assembling foundational cloud environments from scratch every time. ... -
3
Google Cloud Java Client Libraries
Google Cloud Client Library for Java
The Cloud Client Libraries are the recommended way to access Google Cloud APIs programmatically. The Cloud Client Libraries support accessing Google Cloud services in a way that significantly reduces the boilerplate code you have to write. The libraries provide high-level API abstractions so they're easier to understand. They embrace idioms of the language, work well with the standard library, and integrate better with your codebase. -
4
Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
...The project is designed to accelerate cloud adoption by offering opinionated yet flexible patterns aligned with Google Cloud best practices, helping organizations bootstrap their environments quickly while maintaining governance and scalability. It supports complex multi-project and multi-environment setups, making it suitable for large enterprises that require consistent infrastructure provisioning across teams. -
Intelligent Retail ManagementQuant offers a wide range of solutions for retail. Within one integrated software system, it allows you to efficiently combine the management of retail space, shelf labels and marketing materials with task management, reporting and automatic replenishment.
-
5
PHP Docs Samples
A collection of samples on how to call Google Cloud services
PHP Docs Samples repository is a broad collection of PHP examples that demonstrate how to call and work with Google Cloud services from PHP applications. It is designed as a companion to Google Cloud documentation, giving developers ready-to-run code patterns they can study, adapt, and integrate into their own projects. Rather than focusing on a single product, the repository spans many services and use cases, making it useful for developers who need a central reference point for PHP-based cloud integrations. ... -
6
Google Cloud Platform Node.js Samples
Node.js samples for Google Cloud Platform products
Google Cloud Platform Node.js Samples repository is a large set of Node.js code examples that demonstrate how to build, deploy, and manage applications using Google Cloud Platform services. It mirrors the structure and purpose of the Python and Go sample repositories, providing developers with practical implementations that complement official documentation. -
7
HolmesGPT
CNCF Sandbox Project
...Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. The project is developed by Robusta and has been accepted as a Cloud Native Computing Foundation Sandbox project, highlighting its relevance to the cloud-native ecosystem. It is designed to operate as an automated troubleshooting assistant that can analyze incidents continuously and support on-call engineers during outages. -
8
KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
KubeEdge is built upon Kubernetes and extends native containerized application orchestration and device management to hosts at the Edge. It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image... -
9
Ploomber
The fastest way to build data pipelines
Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. Ploomber... -
Queue Management System for Busy Service Providers | WaitWellThe queue management system that perfectly adapts to your workflows. Improve operational efficiency in weeks with the most configurable enterprise queue system.
-
10
OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
...OpenSandbox is particularly useful for AI agents, code execution services, and any scenario where untrusted code must be executed safely. Its architecture emphasizes flexibility, security boundaries, and operational consistency across environments. Overall, the project aims to standardize sandbox execution for modern AI and cloud native workflows. -
11
Clippy
Clippy, now with some AI
Clippy is an open-source desktop assistant that allows users to run modern large language models locally while presenting them through a nostalgic interface inspired by Microsoft’s classic Clippy assistant from the 1990s. The project serves as both a playful homage to the early days of personal computing and a practical demonstration of local AI inference. Clippy integrates with the llama.cpp runtime to run models directly on a user’s computer without requiring cloud-based AI services. It supports models in the GGUF format, which allows it to run many publicly available open-source LLMs efficiently on consumer hardware. ... -
12
PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
...This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources. -
13
QA-Pilot
QA-Pilot is an interactive chat project that leverages LLMs
QA-Pilot is an interactive chat-based application designed to help users understand and navigate GitHub repositories using large language models. It enables users to clone repositories locally and then interact with them through a conversational interface, allowing for rapid exploration of codebases without manual searching. The system supports both local and cloud-based LLM providers, making it flexible for different environments and privacy requirements. It includes features such as chat... -
14
Apache Seata
High-performance, open source distributed transaction solution
Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and... -
15
Unikraft
A next-generation cloud native kernel designed to unlock performance
Unikraft powers the next generation of cloud-native, containerless applications by enabling you to radically customize and build custom OS/kernels; unlocking best-in-class performance, security primitives, and efficiency savings. Unikraft optimizes resource utilization, leading to smaller footprints (meaning higher server saturation) and improved efficiency in resource-constrained environments. Unikraft is an open-source project driven by a vibrant community of over 100 developers, fostering... -
16
AutoTrain Advanced
Faster and easier training and deployments
AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence embedding training, and large language model fine-tuning. ... -
17
E2B Cookbook
Examples of using E2B
E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. ... -
18
MirageOS
MirageOS is a library operating system that constructs unikernels
A programming framework for building type-safe, modular systems. MirageOS is a library operating system that constructs unikernels for secure, high-performance network applications across a variety of cloud computing and mobile platforms. Code can be developed on a normal OS such as Linux or macOS, and then compiled into a fully standalone, specialized unikernel that runs under a Xen or KVM hypervisor. This lets your services run more efficiently, securely and with finer control than with a full conventional software stack. -
19
Autoskills
One command. Your entire AI skill stack. Installed
...The system is designed to work across a wide range of ecosystems, including frontend, backend, mobile, cloud, and AI tooling stacks. It also supports integration with environments like Claude Code by generating structured summaries of installed skills. By removing the need for manual configuration, it streamlines the onboarding process for AI-assisted workflows. Overall, autoskills functions as an intelligent automation layer that bridges project context with AI tooling capabilities. -
20
GitMCP
Turn any GitHub repository into an MCP documentation server for AI
GitMCP is an open source remote Model Context Protocol (MCP) server designed to transform GitHub repositories into structured documentation hubs that AI assistants can query directly. It enables developer-focused AI tools to access up-to-date project documentation and source code so that responses are grounded in real repository content rather than outdated training data. By exposing repository documentation and code through standardized MCP tools, GitMCP helps reduce incorrect or fabricated... -
21
llama.vscode
VS Code extension for LLM-assisted code/text completion
...The extension supports common AI development features such as code completion, conversational chat assistance, and AI-assisted code editing directly within the IDE. Developers can select and manage models through a configuration interface that automatically downloads and runs the required models locally. The extension also supports agent-style coding workflows, where AI tools can perform more complex tasks such as analyzing project context or editing multiple files. -
22
DeployStack
Centralized credential vault, governance, and token optimization
...The project emphasizes repeatability and clarity, enabling teams to follow best practices for scalability, security, and operational reliability without hand-crafting deployment scripts for every new service. It supports integration with popular cloud providers and infrastructure tooling, streamlining workflows that span local development through staging and production environments. -
23
Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
Unsloth-MLX offers developers the power of Unsloth’s efficient large language model fine-tuning experience on Apple Silicon Macs by wrapping Apple’s native MLX framework with an API fully compatible with Unsloth workflows. This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs. It supports loading and training Hugging Face models with fine-tuning strategies like SFT, DPO, ORPO, and GRPO and even handles exporting models to formats like GGUF for downstream use, although some limitations apply with quantized models. ... -
24
Crossplane Kubernetes
The Cloud Native Control Plane
Build control planes without needing to write code. Crossplane has a highly extensible backend that enables you to orchestrate applications and infrastructure no matter where they run, and a highly configurable frontend that lets you define the declarative API it offers. Upbound built Crossplane to help organizations build their platforms like the cloud vendors build theirs—with control planes. -
25
MLOps Zoomcamp
Free MLOps course from DataTalks.Club
MLOps Zoomcamp is an open-source educational repository that contains the materials for a free course focused on machine learning operations and production machine learning systems. The course is designed to teach data scientists and engineers how to move machine learning models from experimentation environments into scalable production services. The repository provides lessons, code examples, and assignments that cover the entire MLOps lifecycle, including model training, experiment...
