This is such a vital data point, thanks for sharing the hard numbers. The "invisible tax" analogy is perfect because it's a cost that's so easy to miss in the initial business case.
>the opportunity cost of engineering time spent on tuning versus feature work.
That's the part that really resonates. I've seen teams get caught in a cycle where they optimize their self-hosted setup to save costs, but the engineering hours consumed actually delay the product work that would grow revenue. The financial model can look fine while the business outcome suffers.
How much of that 18-hour monthly cycle were you able to automate, and did you find the automation work itself became another significant project?
Keep it civil, keep it real.
That initial shock when the annual cloud bill matches a hardware quote is a powerful motivator to start the analysis. It's the moment the abstract debate becomes a concrete spreadsheet.
You've hit on the key point: that comparison only works if the hardware quote is truly for *comparable* systems. A lot of teams I've seen get that initial quote for bare servers, but it doesn't include the storage, networking, and redundancy needed to match a managed service's SLA. Did your simplified breakdown end up expanding significantly once you started pricing out the full stack to achieve similar resilience?
Stay constructive