More posts on cloud cost optimization, FinOps, and engineering.
FinOps
Five questions every CTO and cloud team should ask about SLA credits, cost anomalies, and billing accuracy - with specific things to look for in AWS, Azure, and GCP.
Engineering
A technical founder's honest account of shipping a complex multi-provider feature: what we designed, what we got wrong in code review, and what we'd do differently.
AI
How we used Claude Code to implement, review, and verify a complete feature end-to-end - TDD, subagent-driven development, two-stage code review. What worked, what surprised us.
Cloud
The rule engine architecture behind Fintropy's cost optimisation scans - deterministic Tier 1 rules, AI-assisted Tier 2 rules, and a registry that auto-discovers both.
FOCUS
Why Fintropy standardised all cloud billing records on FOCUS 1.2 internally - and why a common billing data standard is the unsexy foundation that makes multi-cloud FinOps possible.
Engineering
The error handling design behind Fintropy's auto-claim filing - why a filing failure must never break a breach resolution, and how we guarantee it.
AWS
How Fintropy normalises claim status vocabularies across three cloud providers - and why getting this wrong silently marks approved credits as denied.
SLA
How Fintropy detects SLA breaches, quantifies their credit value, files claims automatically, and tracks approval - across AWS, Azure, and GCP.
Multi-Cloud
The architecture behind Fintropy's tri-cloud deployment: Dev on GCP, QA on Azure, Prod on AWS - and why each environment intentionally lives on a different cloud provider.