Advantages of AWS Greengrass
- Edge Computing: It is a method of optimizing cloud computing systems by performing data processing at the edge of the network, closer to the source of the data. With AWS Greengrass, you can run Lambda functions on devices, enabling them to process and analyze data locally. This eliminates the need to send data to the cloud, reducing latency and increasing the reliability of your application.
- Cost-Effective: AWS Greengrass allows you to perform edge computing on low-cost devices, which can help you save on costs. As all AWS services follow the same pay-as-you-use kind of billing pattern for their users throughout the globe.
- Security: AWS Greengrass provides built-in security features such as device authentication, encryption, and access control, ensuring that your data is secure at all times.
- Scalability: With AWS Greengrass, you can easily scale your application to meet the needs of your users.
- Integration: AWS Greengrass is fully integrated with other AWS services, making it easy to build, test, and deploy your application on the AWS cloud. The ability to integrate with other AWS services, makes it easy to store, process, and analyze data from connected devices.
Introduction to AWS Greengrass
Pre-requisite: AWS
Amazon Web Services (AWS) Greengrass is software that enables local execution of AWS Lambda functions and messaging capabilities on connected devices. It allows you to run AWS Lambda functions and a message broker on local devices, such as edge gateways and industrial equipment while maintaining seamless integration with the AWS Cloud.
AWS Greengrass is software that allows you to run AWS Lambda functions and a message broker on local devices while maintaining seamless integration with the AWS Cloud. This enables you to build and deploy internet of things (IoT) applications that can function even when disconnected from the internet. With Greengrass, you can run AWS Lambda functions locally, update and debug them remotely, and take advantage of the entire AWS ecosystem.