Stream Processing
Your guide: Data Dora
“Every reading has a time and a cost — decide retention before you decide the database.”
This module explains how IoT systems move from sensor events to useful downstream decisions. It focuses on stream-processing concepts, pipeline structure, production review concerns, and hands-on practice.
Use this wrapper as a route map. Start with stream-processing concepts, then study pipeline and architecture choices, then review production concerns and labs. Interoperability content now lives in Protocol Integration.
Start With One Reading Arriving Now
Picture one sensor reading arriving while the device is still running. A batch report can wait until later, but this reading may decide whether a pump slows down, a warning appears, or a record is sent to another system.
Stream processing is the discipline of keeping that live path understandable. This module follows the reading from event shape to pipeline stage, review evidence, production concern, and lab practice so each decision can be retested instead of guessed.
What You Will Learn
By the end of this module, you should be able to:
- explain why stream processing is useful when IoT data arrives continuously;
- identify the stages of a streaming pipeline, from ingestion through filtering, enrichment, state, and output;
- compare architecture choices using evidence from data rate, latency need, reliability need, and integration boundary;
- recognize common stream-processing challenges and review pitfalls;
- connect stream-processing outputs to event contracts owned by protocol-integration reviews;
- practice stream-processing decisions through labs and review-game checks.
Recommended Route
Follow the chapters in module order if you are new to this topic:
Choose A Starting Point
Use these entry points when you already know what you need:
- To understand the module vocabulary, start with Stream Processing Fundamentals.
- To review core concepts before design work, use Stream Processing Fundamentals.
- To compare processing shapes, use Stream Processing Architectures.
- To trace events through a data path, use Building IoT Streaming Pipelines.
- To prepare for production review, use Common Pitfalls and Worked Examples.
- To connect systems cleanly, use Interoperability Fundamentals, Interoperability Standards, and Integration Patterns for IoT in Protocol Integration.
- To practice decisions, use Lab: Stream Processing, Hands-On Lab: Advanced CEP, and the review-game practice checks.
Study Questions
As you work through the module, keep asking:
- What event or measurement is arriving as a stream?
- What decision depends on each event, aggregate, or alert?
- What context must be added before the stream is useful?
- What state must be kept, and what can be discarded?
- What happens when events arrive late, out of order, duplicated, or missing?
- Which interface or data format keeps the next system from guessing?
- What evidence would show that the pipeline is behaving as intended?
Concept Relationships
- Sensor events become useful when a pipeline names ingestion, filtering, enrichment, state, output, and review evidence.
- Architecture choices should follow the stream’s decision needs, not a generic tool preference.
- Interoperability choices are handled in Protocol Integration; this module links to those event-contract reviews when a stream crosses system boundaries.
- Production review checks whether timing, order, loss, duplication, and recovery assumptions are visible.
- Labs and review-game checks help turn the route-map vocabulary into practiced decisions.