Streaming and Real-Time Analytics
summary
Covers concrete streaming stacks and outcomes: uses Amazon Kinesis Data Streams, Firehose, Kinesis Data Analytics, MSK, Lambda, S3, DynamoDB, Redshift, Elasticsearch and QuickSight to build real pipelines; Epic Games example stores 14 petabytes and grows 2 PB/month while serving 1.25M players; demo sends 20,000 requests (0.5s delay) into a beacon, Firehose archives to S3, Kinesis Analytics transforms and pushes to Lambda → DynamoDB and a real‑time dashboard, and a WebRTC KVS demo shows low‑latency video playback.
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chapters (13)
- 0:00Introduction to streaming analytics
- 1:25Real-time gaming analytics example
- 3:13Why real-time analytics matters
- 6:46Principles of data streaming
- 9:14Challenges and AWS solutions
- 10:40Amazon Kinesis family overview
- 13:50Analyzing streaming data
- 14:32Demo: Real-time clickstream analytics
- 23:05Visualizing insights with QuickSight
- 25:11Demo: QuickSight integration
- 29:04Video streaming with Kinesis
- 31:29Demo: WebRTC video chat
- 33:01Use cases and next steps
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