We’ve published previous posts on the birth of Chrysalis Cloud and how the platform works. In this article, we compare the process of (1) streaming, (2) analyzing, and (3) storing video using AWS Kinesis Video Streams vs. the Chrysalis Cloud. Read on to learn how you can save up to 70% on your cloud costs, while also reducing latency, and speeding up development/ deployment timelines.
Keep reading for the longer story:
We know the headlines: “Companies surprised by AWS bills,” “Cloud cost control becoming a leading issue for businesses.” AWS Cloud services for streaming, analyzing and storing video are expensive and can be very complicated to use. At Chrysalis Cloud, our goal is to make this process far simpler and cheaper, enabling new use cases for video and more advanced ML and AI in the cloud.
First, the basics of what we are comparing. Stream processing in the cloud has three phases:
- Ingestion (getting the data from the camera to the cloud),
- Processing (doing computation such as video analytics), and
- Storage/ Retrieval (keeping the stream for later use and accessing it when needed).
We are going to walk through each of these phases, comparing the process using AWS Kinesis Video Streams vs. the process using Chrysalis Cloud.
We’ll start with Ingestion.
Kinesis Ingestion: Even though Kinesis is a “streaming video service,” for many camera types it’s fairly difficult to get video data from the camera into a Kinesis stream.