**Steps**: (1) Workflows > Runs; find failed run. (2) Task tree—identify failed task (red). (3) Logs—stdout, stderr, notebook output. (4) Cluster events if task never started. (5) Reproduce—run notebook with same parameters. (6) Job config—cluster, libraries, params. (7) Delta history for data issues.
**Why Systematically**: Random checks waste time. Logs first; config second; data third.
**Scalability Trade-offs**: Large logs; use log delivery to S3 for retention....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like TCS. The answer also includes follow-up discussion points that interviewers commonly explore.
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