Analytics
CoreAmazon Kinesis
AWS streaming services for collecting, processing, and analyzing data streams; DVA-C02 focuses on application and Lambda stream integration.
Key points
- Kinesis Data Streams preserves records in shards for ordered stream processing and replay within retention.
- Lambda event source mappings poll stream shards and invoke functions with batches.
- Consumers must handle batching, checkpoint progress, retries, duplicate delivery, and partial failures.
Best-known use cases
- Near-real-time event ingestion and transformation.
- Ordered per-shard processing with multiple stream consumers.
What candidates often confuse it with
- Kinesis Data Streams retains an ordered stream; SQS buffers discrete queue messages.
- Kinesis streaming differs from SNS fanout because consumers process retained ordered records rather than topic deliveries.
Key takeaway
Choose Kinesis when continuous retained stream processing and ordering are decisive, then make the consumer batch- and retry-aware.
Related services
- AWS Lambda
- Amazon CloudWatch
- Amazon S3
Relevant exam tasks
- D1.1 — Develop code for applications hosted on AWS
- 1.1.10 — Handle streaming data using AWS services
- D1.2 — Develop code for AWS Lambda
- 1.2.5 — Integrate Lambda functions with AWS services
- 1.2.7 — Use Lambda functions to process and transform data in near real time