Fast dimensional analysis for root cause analysis at scale

What this post added

Introduced a Fast Dimensional Analysis (FDA) framework to automate root cause analysis on structured logs at scale. The framework combines structured logs from multiple sources, deduplicates data, and uses one-hot encoding to prepare data for frequent pattern mining. It leverages Apriori/FP-Growth algorithms to identify frequent item-sets and uses support and lift metrics for filtering and significance measurement. Pre- and post-processing, parallelism, and filters are employed to enhance scalability and interpretability.