Data Distribution and Processing

In the previous chapter, we explored the architecture of data pipelines, understanding their role as the circulatory system for observability data. In this chapter, we’ll dive deeper into the specific processes of data distribution and processing. Think of a retail warehouse where online purchases result in items being picked, packaged, labeled with order details, and then distributed to their destinations via conveyor belts:

Figure 6.1 – Warehouse distribution and processing example

Similarly, in telemetry and observability, data collected from metrics, logs, flows, and events in general undergoes a parallel journey:

• Processing: Here, similar to packing and labeling in our warehouse analogy, data needs to be normalized into a common format and perhaps enriched with additional details for clarity and context. This step ensures that the data is package-ready for its journey through the pipeline.
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