Hands-on lab to demo how to store, process, and read video on Streaming Data Platform
Components
- Streaming Data Platform: Streaming Data Platform allows for harnessing their real-time and historical data in a single, auto-scaling infrastructure and programming model.
- Pravega: Pravega provides a new storage abstraction - a stream - for continuous and unbounded data. A Pravega stream is a durable, elastic, append-only, unbounded sequence of bytes that has good performance and strong consistency. Pravega provides dynamic scaling that can increase and decrease parallelism to automatically respond to changes in the event rate.
- Flink: Apache Flink® is an open-source stream processing framework for distributed, high-performing, always-available, and accurate data streaming applications.
- Docker: This demo uses Docker and Docker Compose to greatly simplify the deployment of the various components on Linux and/or Windows servers, desktops, or even laptops.
Demo environment
Workload Flow
- Camera recorder collects video feed and sends it into a stream
- Video Data Generator Job creates randomized data as additional video streams
- Video Stream, Multi-Video Grid Job and Grid Stream combine the video feeds, resize the images, align by time and join
- Video Player displays all the video feeds in a grid system
