12 articles on unit economics — what drives the cost, how it is priced, and where the savings actually are.
A bandwidth bill is meaningless as an absolute number. Divided by active users it becomes a metric you can trend, forecast, and compare against revenue per user. Here is how to build it.
A board does not want a service-level cost breakdown. It wants efficiency, trend, and whether spend is tracking to plan. Here is what to put on the cloud cost slide, what to leave out, and the four metrics that survive scrutiny.
Not all cloud spend is cost of goods sold, and where you draw the line moves reported gross margin by several points. Here is how to split infrastructure cost between COGS and operating expense, and why the split matters.
Reliability engineering solved the problem of holding teams to a target without freezing them. The same structure works for cost: a unit cost objective, a tolerance band, and an error budget that triggers action when it is exhausted.
A launch cost model has to work before any usage data exists. Here is how to build one from architecture and assumptions, what to bound, and how to keep it useful once real traffic arrives.
Infrastructure cost should not set your price, but it must set your floor. Here is how to compute cost to serve per plan, find the customers who destroy margin, and choose a pricing metric that tracks the cost you actually incur.
Industry benchmarks for cloud spend are mostly unusable because nobody defines the numerator or the denominator the same way. Internal and architectural benchmarks are far more actionable. Here is how to build both.
In a multi-tenant SaaS, the blended cloud bill hides that some tenants cost 50 times more than others to serve. Measuring cost per tenant exposes unprofitable accounts and bad pricing. Here is how to build the metric.
Dividing your infrastructure cost by request volume gives a single number that exposes inefficient endpoints, bad caching, and creeping bloat. Here is how to compute cost per request and use it to drive optimization.
Cost per 1000 inference requests is the unit metric that tells you whether serving a model is economical. It ties GPU or serverless cost to actual usage, and it is the number to optimize as you scale. Here is how to compute and reduce it.
Unit economics ties cloud spend to a business metric, cost per customer, per transaction, per request, so you measure efficiency instead of just total dollars. This guide covers which units to pick, how to compute them, and how to improve them.
Cost per customer, cloud spend divided by customers served, is the unit metric that drives SaaS gross margin. Knowing it, and reducing it as you scale, is essential to healthy economics. Here is how to measure and improve it.