Cloud cost optimisation is the practice of reducing infrastructure spend without sacrificing reliability or performance. Articles here cover FinOps strategies for BigQuery, multi-cloud egress reduction, reservation planning, and query-level cost attribution that have delivered measurable savings in production environments.
3 posts tagged with 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.
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.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.