Posts about cost optimisation. ← All posts
What looked like an idiomatic BigQuery MERGE was scanning the full target table on every batch. The fix was syntactic, not architectural — and it was the single biggest contributor to a 57% data-warehouse cost reduction across the Tata Group engagement.
₹100 Cr / ~$12M in proven savings across a year-plus engagement. The four levers that did the heavy lifting, the lever I expected to win that didn't, and the post-engagement playbook that became a Searce managed service.
Not every query needs the production agent. A cost-aware dispatcher decides whether to route to the cheap-and-fast agent or the expensive-and-thorough one. Same UX, dramatically lower bill.
Cross-cloud data movement is billed by the GB. The bill is invisible until it isn't. A multi-region or multi-cloud architecture that doesn't model egress costs in design will discover them in production.