Best Edge Computing Software are AWS IoT Greengrass, Microsoft Azure IoT Edge, Node-RED, Eclipse ioFog, Foghorn Lightning Edge AI, and Balena. Below we will look at all of these software in detail.
Learning edge computing opens doors to exciting fields like IoT (Internet of Things), AI, robotics, and cloud computing. But with so many tools available, where should you start? Below, I will tell you everything.
Edge Computing Software
Here are Best Edge Computing Software Platforms:
1. AWS IoT Greengrass
AWS IoT Greengrass is a popular edge computing tool from Amazon. It lets you run cloud-like functions on local devices. This edge computing software is best for students who want to connect edge devices to Amazon Web Services (AWS).
Key Features:
- Runs machine learning (ML) models locally.
- Works with Raspberry Pi and other small computers.
- Free tier available for learning.
Difficulty: Medium (requires basic coding knowledge).
Pricing: Free for small projects. Paid plans for advanced use.
Why Students Should Try It: If you want to learn cloud-connected edge computing, AWS IoT Greengrass is a great start.
2. Microsoft Azure IoT Edge
Azure IoT Edge is Microsoft’s solution for edge computing. It works well with Windows and Visual Studio. This software is for students familiar with Microsoft tools.
Key Features:
- Supports AI and offline processing.
- Free access for students via Azure for Education.
- Good for school projects.
Difficulty: Medium (some coding needed).
Pricing: Free tier available.
Why Students Should Try It: If your school uses Microsoft products, this is a smooth way to learn edge computing.
3. Node-RED
Node-RED is a simple, visual tool for edge computing. You connect nodes (blocks) to create workflows without coding. This software is best option for beginners who want a no-code option.
Key Features:
- Drag-and-drop interface.
- Works with Raspberry Pi and Arduino.
- Large community for support.
Difficulty: Easy (no coding required).
Pricing: Free and open-source.
Why Students Should Try It: If you’re new to programming, Node-RED is the easiest way to start.
4. Balena (formerly Resin.io)
Balena helps manage IoT devices remotely. It uses Docker containers for easy deployment. It is best for students working on IoT projects.
Key Features:
- Supports Docker (a tool for running apps in containers).
- Remote updates for devices.
- Works with Raspberry Pi.
Difficulty: Medium (requires some setup).
Pricing: Free for small projects.
Why Students Should Try It: If you’re building smart devices, Balena makes updates and management easy.
5. Foghorn Lightning Edge AI
Foghorn brings AI to edge devices. It’s used in industrial IoT but is good for learning. Best for Advanced students interested in AI at the edge.
Key Features:
- Real-time data processing.
- Works with industrial sensors.
- Good for robotics projects.
Difficulty: Hard (best for students with some AI knowledge).
Pricing: Free trial available.
Why Students Should Try It: If you want to explore AI in edge computing, Foghorn is a powerful tool.
6. Eclipse ioFog
Eclipse ioFog is an open-source edge computing platform. It supports microservices and Kubernetes. It is for students who want to learn open-source edge development.
Key Features:
- Modular and flexible.
- Works with many IoT devices.
- Good for learning edge architecture.
Difficulty: Medium (requires some technical knowledge).
Pricing: Free.
Why Students Should Try It: If you like open-source software, Eclipse ioFog is a great choice.
7. ClearBlade IoT Edge
ClearBlade offers fast deployment for edge applications. It has a drag-and-drop interface. This software is good for students who want a quick setup.
Key Features:
- Easy-to-use interface.
- Scalable for school projects.
- Good documentation.
Difficulty: Easy-Medium.
Pricing: Free tier available.
Why Students Should Try It: If you need a simple yet powerful tool, ClearBlade is a good option.
8. Zededa (EVE-OS)
Zededa provides virtualized edge computing. It’s secure and Linux-based. It is best for students working on secure edge projects.
Key Features:
- Remote device management.
- Works with multiple hardware types.
- Good for learning edge security.
Difficulty: Medium-Hard.
Pricing: Free trial available.
Why Students Should Try It: If security interests you, Zededa is worth exploring.
9. EdgeX Foundry
EdgeX Foundry is an open-source framework for edge computing. It standardizes edge development. It is best for students who want to learn industry standards.
Key Features:
- Vendor-neutral (works with many devices).
- Good for learning edge computing principles.
- Active developer community.
Difficulty: Medium.
Pricing: Free.
Why Students Should Try It: If you want to understand how edge computing works in real-world systems, EdgeX is a great learning tool.
10. NVIDIA Fleet Command
NVIDIA Fleet Command brings GPU power to edge computing. It’s used in AI and robotics. This software is best for Advanced students working on AI-driven projects.
Key Features:
- GPU-accelerated edge computing.
- Good for robotics and autonomous systems.
- Free trial available.
Difficulty: Hard (requires AI/ML knowledge).
Pricing: Free trial, then paid.
Why Students Should Try It: If you’re into AI and robotics, NVIDIA’s tools are industry leaders.
How Students Can Get Started with Edge Computing
Ready to try edge computing? Follow these steps:
- Pick Beginner-Friendly Software – Start with Node-RED or ClearBlade if you’re new.
- Follow Tutorials – YouTube and official docs help you learn fast.
- Build a Small Project – Try a smart sensor with Raspberry Pi.
- Join Communities – Ask questions on GitHub, Reddit, or Discord.