Search Results for "edge computing"
Sort By:
Showing 52 open source projects for "edge computing"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
1
EVE OS
EVE is Edge Virtualization Engine
EVE is an open-source, secure, and container-optimized operating system for edge computing, developed by the LF Edge foundation. It enables enterprises to deploy and manage edge applications on heterogeneous hardware platforms using a zero-trust architecture. EVE supports virtual machines, containers, and unikernels while being hardware-agnostic, making it suitable for industrial gateways, edge clusters, and IoT devices. -
2
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... -
3
OpenYurt
Extending your native Kubernetes to edge(project under CNCF)
OpenYurt is built based on upstream Kubernetes and is now hosted by the Cloud Native Computing Foundation(CNCF) as a Sandbox Level Project. OpenYurt has been designed to meet various DevOps requirements against typical edge infrastructures. It provides a consistent user experience for managing the edge applications as if they were running in the cloud infrastructure. It addresses specific challenges for cloud-edge orchestration in Kubernetes such as unreliable or disconnected cloud-edge networking, edge autonomy, edge device management, region-aware deployment, and so on. ... -
4
ExecuTorch
On-device AI across mobile, embedded and edge for PyTorch
ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
MicroK8s
Single-package Kubernetes for developers, IoT and edge
Low-ops, minimal production Kubernetes, for devs, cloud, clusters, workstations, Edge and IoT. MicroK8s automatically chooses the best nodes for the Kubernetes datastore. When you lose a cluster database node, another node is promoted. No admin needed for your bulletproof edge. MicroK8s is small, with sensible defaults that ‘just work’. A quick install, easy upgrades and great security make it perfect for micro clouds and edge computing. -
6
ObjectBox Java Database
Java and Android Database - fast and lightweight without any ORM
High-performance NoSQL database with integrated Data Sync for decentralized Edge Computing. Get fast access to the data you need across Embedded Devices, IoT, and Mobile. ObjectBox is 10x faster than any alternative, with high-speed data ingestion that increases response times. Check out our benchmarks. ObjectBox’ out-of-the-box synchronization makes data available when needed where needed, eliminating data islands and improving data flow. -
7
NATS
Server for NATS.io, the cloud and edge native messaging system
With flexible deployments models using clusters, superclusters, and leaf nodes, optimize communications for your unique deployment. The NATS Adaptive Edge Architecture allows for a perfect fit for unique needs to connect devices, edge, cloud or hybrid deployments. With true multi-tenancy, securely isolate and share your data to fully meet your business needs, mitigating risk and achieving faster time to value. Security is bifurcated from topology, so you can connect anywhere in a deployment... -
8
Zvec
A lightweight, lightning-fast, in-process vector database
...Because it runs in-process, developers can embed it in native apps, microservices, or edge computing scenarios where traditional server-based vector databases might be overkill. -
9
sebastian/diff
Diff implementation
...Internally, the library splits input into hunks and manages edge cases such as whitespace-only changes and end-of-line variations. Its abstractions make it straightforward to plug custom output styles or colorizers without reimplementing diff logic. Because it’s the diff engine under PHPUnit, it has been exercised across countless projects and edge cases. -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
10
PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
...The runtime is capable of running language models with billions of parameters on devices with only a few hundred megabytes of memory, which is significantly lower than typical LLM infrastructure requirements. This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources. -
11
mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies such as ARM NEON and x86 AVX2 instructions. ... -
12
Tau
Open source distributed Platform as a Service (PaaS)
tau is the core runtime and orchestration engine of the Taubyte platform, an event-driven, distributed computing framework for building and running decentralized applications. tau handles the dynamic deployment of code, services, and data across edge and cloud environments based on real-time events. It abstracts infrastructure and simplifies application delivery by combining GitOps principles with a secure, multi-tenant execution model. tau enables seamless scalability, event-based routing, and on-demand execution without managing underlying servers. -
13
ElatoAI
Realtime AI Voice Agents with SoTA Multimodal AI models on Arduino ESP
ElatoAI is a real-time AI voice agent platform built around IoT hardware (ESP32) that enables continuous speech-to-speech conversations using state-of-the-art multimodal voice models with minimal latency and global performance via edge computing. The system integrates voice synthesis and recognition by connecting an ESP32 device through secure WebSockets to edge server functions written in Deno, allowing users to speak naturally with AI agents hosted through cloud APIs including OpenAI’s Realtime API, Gemini’s Live API, xAI’s Grok Voice Agent API, and others. It includes a web client (built with Next.js) for managing devices, controlling volume, and viewing conversation transcripts, while the hardware runs optimized firmware to deliver responses in near real time — even supporting >15-minute uninterrupted conversations. -
14
OSMO
The developer-first platform for scaling complex Physical AI workloads
OSMO is a developer-first orchestration platform designed to scale complex physical AI workflows across heterogeneous computing environments, including cloud GPUs, simulation clusters, and edge devices. It was originally built internally at NVIDIA to support robotics and embodied AI systems, where workflows span multiple stages such as data generation, training, simulation, and hardware testing. The platform addresses what NVIDIA refers to as the “three computer problem” by unifying these stages into a single pipeline defined through simple YAML configurations. ... -
15
ObjectBox Go Database
Embedded Go Database, the fast alternative to SQLite, gorm, etc.
ObjectBox Go is a lightweight and high-performance embedded NoSQL database designed for Go applications, providing efficient data storage and retrieval with minimal overhead. -
16
nndeploy
An Easy-to-Use and High-Performance AI Deployment Framework
...The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different stages of the inference process. The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed. -
17
Neboa
Type-safe NoSQL with Node & SQLite
Neboa is a lightweight, decentralized NoSQL database designed for distributed applications. It offers peer-to-peer synchronization and ensures data integrity across multiple nodes without relying on centralized servers, making it ideal for edge computing and offline-first applications. -
18
ReductStore
The fastest time series object store for Edge AI
...Store billions of time-stamped blobs with AI labels and access them with low latency. Outperform other databases with a customized solution for time-series object data. Capture and access blob data as time series, tailored for edge computing, computer vision, and IoT. ReductStore handles blob data without size limits; your disk capacity is the only boundary. Ensure optimal storage management with FIFO quotas, preventing disk space shortages in real-time. Manage your time-series blob data with ease: annotate, filter, and save AI labels or meta-data. Integrate and communicate with ReductStore using our feature-rich and secure API. -
19
rpm-ostree
Hybrid image/package system with atomic upgrades and package layering
...This approach enables atomic upgrades and rollbacks, ensuring system stability and consistency across deployments. rpm-ostree is particularly suited for scenarios where reliable and reproducible system states are critical, such as in containerized or edge computing environments. -
20
Bun
Incredibly fast JavaScript runtime, bundler, test runner
...Bun is a new JavaScript runtime built from scratch to serve the modern JavaScript ecosystem. Bun starts fast and runs fast. It extends JavaScriptCore, the performance-minded JS engine built for Safari. As computing moves to the edge, this is critical. Bun provides a minimal set of highly optimized APIs for performing common tasks, like starting an HTTP server and writing files. Bun is a complete toolkit for building JavaScript apps, including a package manager, test runner, and bundler. Bun is designed as a drop-in replacement for Node.js. ... -
21
RuleGo
Component orchestration rule engine framework for Go
...It’s lightweight, embeddable, orchestration-ready, and built for flexible composition of business logic into reusable components. No external middleware dependencies, efficient data processing and linkage on low-cost devices, suitable for IoT edge computing. Embedded and Standalone Deployment modes. Supports embedding RuleGo into existing applications. It can also be deployed independently as middleware, providing rule engine and orchestration services. -
22
Project MINI RACK
Miniature rack builds, for portable or compact Homelabs
Project MINI RACK is a project dedicated to designing, documenting, and showcasing compact, portable rack-mount or small-form factor “mini” labs, suitable for home labs, edge deployments, or mobile network stacks. The repository contains build guides, hardware lists, layout ideas (10” wide racks, 1U/2U modules, custom shelves), 3D printable components, and real-world examples of mini homelab rigs. Its goal is to help hobbyists, devops engineers, or tinkerers understand how to build... -
23
Gramine
A library OS for Linux multi-process applications
Gramine is a lightweight library-operating system (Library OS) designed to run unmodified Linux applications with minimal dependencies on the host OS, and to offer enhanced isolation and portability. It was formerly known as Graphene, but the project renamed to Gramine to avoid naming conflicts and to reflect its broader ambition beyond the original research prototype. The idea is that instead of running a full guest OS in a VM, you embed your application inside Gramine, which handles the... -
24
TinyGo
Go compiler for small place
...You can compile and run TinyGo programs on over 60 different microcontroller boards such as the BBC micro:bit and the Arduino Uno. TinyGo can also produce WebAssembly (WASM) code which is very compact in size. You can compile programs for web browsers, as well as for server and edge computing environments that support the WebAssembly System Interface (WASI) family of interfaces. TinyGo is a Go compiler intended for use in small places such as microcontrollers, WebAssembly (Wasm), and command-line tools. It reuses libraries used by the Go language tools alongside LLVM to provide an alternative way to compile programs written in the Go programming language. ... -
25
AssemblyScript
A TypeScript-like language for WebAssembly
...AssemblyScript integrates with the WebAssembly ecosystem, enabling seamless interaction with JavaScript through standard APIs. It is widely used in scenarios where performance and portability are essential, such as gaming, data processing, and edge computing.
