$192 billion

Global connected home forecast by 2023


SkyBell issued patents

$1.4 billion

Global doorbell camera market size in 2018



TensorIoT helped SkyBell improve their cloud infrastructure and create a scalable DevOps pipeline.


How can we make SkyBell’s current system more efficient, more scalable, and more cost effective?


By switching IoT protocols from CoAP to MQTT, the team was able to optimize SkyBell’s codebase. Following the transition, the team continued to provide support.


SkyBell, a leading provider of IoT enabled smart video doorbells, has been an IP leader since 2013. With it’s large fleet of doorbells and loyal customer base, SkyBell was looking to the future and planning ways to keep ahead of the competition. They identified a need to improve their cloud infrastructure and create a scalable DevOps pipeline for managing and monitoring the technology stack. They were also looking for direct support in supporting the deployed solution.

The Challenge

Skybell needed an updated cloud infrastructure capable of handling their existing devices and data along with incorporating a robust DevOps pipeline to improve development, making AWS the obvious choice for the project. When TensorIoT was building the backend system for Skybell, one of the challenges was improving speed and scaling. TensorIoT switched Skybell's IoT protocols from CoAP to MQTT, creating a faster system that could be easily scaled. Another major challenge was the lack of a subject matter expert for Skybell's previous codebase and limited documentation, meaning that the TensorIoT team needed to carefully review the existing code piece by piece to gain a thorough understanding during the process of building the AWS solution.

The Solution

To build an updated cloud infrastructure using AWS, TensorIoT evaluated and documented SkyBell’s existing code to come up with an optimization plan, as well as determine what additional automation and deployment scripts could be added. Along with AWS IoT Core and IoT events for doorbell connectivity, TensorIoT used Amazon Kinesis for data streaming, Amazon Sagemaker for cutting-edge machine learning models, and AWS Lambda for serverless computing functionality along with other AWS
After completing the build out, TensorIoT provided round-the-clock L2/L3 monitoring and support. With this solution, SkyBell was able to modernize and automate their infrastructure using AWS Cloud to ensure that the entire backend of the application is optimized.