Reviewed by Aditya Kumar · Last reviewed 2026-03-24
(1) Structured logging—JSON with record_id, rule_id, severity, sample. (2) Centralized—ELK, Splunk, CloudWatch. (3) Metrics—failed count per rule; alert on spikes. (4) DLQ—store bad records for reprocessing. (5) Dashboards—DQ score, trends. (6) Sampling—log sample, not all. WHY:...
Red Flag: Blocking pipeline on bad data. Pro-Move: 'DLQ + sampled logging; we replay from DLQ after fix; metrics feed into DQ dashboard; 99.9% good data path unaffected.'
(1) Structured logging—JSON with record_id, rule_id, severity, sample. (2) Centralized—ELK, Splunk, CloudWatch. (3) Metrics—failed count per rule; alert on spikes. (4) DLQ—store bad records for reprocessing. (5) Dashboards—DQ score, trends. (6) Sampling—log sample, not all. WHY: Root cause without full rerun. SCALABILITY: Sampling and aggregation; avoid log explosion. COST: Log volume = cost; sample and aggregate.
Red Flag: Blocking pipeline on bad data. Pro-Move: 'DLQ + sampled logging; we replay from DLQ after fix; metrics feed into DQ dashboard; 99.9% good data path unaffected.'
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