DynamoDB Throttling Diagnostic Framework

New to the DynamoDB team, working on a known pain point for DynamoDB users. The subject was one of the most technically dense in the product: 16 distinct throttling reasons spanning provisioned capacity, on-demand mode, GSIs, and partition-level behavior — with an SDE and a solutions architect as support, and no useful prior content to build from.

Build a complete diagnostic and resolution framework that would help users access the right information when encountering throttling issues.

Went deep independently into capacity modes, partition internals, table and GSI architecture, CloudWatch metrics taxonomy, and back-pressure propagation. Designed a four-category taxonomy based on how operators actually encounter throttling. Built the reason→metric reference table so operators could move directly from an exception to the right CloudWatch signal without intermediate lookup steps. Wrote the GSI back-pressure section to explain the non-obvious indirection: you write to the base table, you get throttled because of the GSI. Structured the diagnostic framework — analyze the exception, correlate the metric, use Contributor Insights, implement the fix, monitor — to reflect the incident workflow operators actually use.

Complete diagnostic coverage of all 16 throttling reasons shipped as a major deliverable on a new team. The taxonomy, reference table, and GSI back-pressure explanation are information architecture decisions that required deep product understanding acquired entirely from scratch.