59 articles on architecture — what drives the cost, how it is priced, and where the savings actually are.
A small B2B SaaS with 1,000 users, a managed database, a cache, and a CDN lands around 195 dollars a month on AWS. Here is the full component-by-component breakdown, the assumptions behind it, and where the money actually goes.
A multi-tenant SaaS at 100,000 users, 250 million API requests a month and a 2 TB database costs roughly 6,540 dollars a month on AWS. Here is the full breakdown, and why observability turns out to cost more than the application tier.
An e-commerce store doing 500,000 monthly visits and 25,000 orders costs about 2,190 dollars a month on AWS, which is 9 cents of infrastructure per order. Here is the full breakdown, including why the CDN is a third of the bill.
A chat app with 10,000 concurrent WebSocket connections and 20 million messages a month costs about 977 dollars on AWS. Here is the breakdown, plus where managed WebSockets stop being cheaper than running your own.
A multiplayer game with 200,000 monthly players and 3,000 concurrent at peak costs about 8,325 dollars a month on AWS. Here is the breakdown, including why patch downloads cost more than the game servers.
A WordPress site doing 2 million page views a month costs about 825 dollars on AWS, and full-page caching cuts that to around 650. Here is the component breakdown and why the database is the fragile part.
A notification service sending 5 million emails, 2 million pushes, and 200,000 SMS a month costs about 2,543 dollars, and SMS is 69 percent of it for 2.6 percent of the volume. Here is the breakdown.
A file sharing service holding 80 TB for 50,000 users with 20 TB of monthly downloads costs about 4,006 dollars on AWS. Here is the breakdown and why tiering storage matters more than anything else.
A service receiving 30 million webhooks a month, processing them with retries, and archiving payloads costs about 506 dollars on AWS. Here is the breakdown, including the 150 dollar mistake almost everyone makes.
A self-hosted headless CMS with 8,000 entries, 25 editors, and 30 million API requests costs about 1,025 dollars a month on AWS, or 41 dollars per editor seat. Here is the breakdown against the hosted alternative.
Splitting a monolith turns function calls into network calls. Those calls are metered, and a fan-out pattern across availability zones can quietly add thousands per month. Here is the arithmetic.
Active-active across two regions is not twice the cost of one. Duplicated compute, duplicated storage, and constant bidirectional replication traffic push the multiple closer to 2.3 or 2.5. Here is the breakdown.
The more data you accumulate in one place, the more it costs to move elsewhere, and the more services cluster around it. Egress pricing is what turns that pull into a financial constraint.
When one function calls another synchronously, you pay for both at once. Chains of waiting functions are the most expensive common anti-pattern in serverless, and they are easy to spot.
A read replica is a full copy of your database with a full copy of its price. A cache node is a fraction of that. The choice comes down to hit ratio, data freshness, and how many distinct queries you are serving. Here is the cost-per-read math.
HA doubles compute and storage on every major cloud, so the question is not whether availability is good but what outage cost the second node avoids. Here is how to do that arithmetic honestly.
Self-hosting looks cheaper until you price the engineers who run it. Managed looks expensive until you price the outage you avoided. Here is a build-versus-buy model with the operational and risk costs made explicit.
An ADR that compares options on latency and operability but not cost leaves the most durable consequence undocumented. Here is how to add a cost section that is specific, auditable, and worth revisiting later.
Dedicated infrastructure per tenant is simple to reason about and expensive to run. Shared infrastructure is cheap per tenant and complicated everywhere else. The break point is not philosophical, it is a curve you can compute. Here is how to find yours.
More accounts means smaller blast radius and cleaner attribution. It also means more baselines, more egress paths, more cross-account traffic, and more discount fragmentation. The right number is the one where isolation value exceeds the separation tax. Here is how to calculate it.
Disaster recovery cost is a direct function of how fast you need to recover. Cold standby is nearly free and slow, hot standby is instant and doubles the bill. Most teams buy hot when warm meets their actual recovery objective. Here is the comparison.
The most expensive cost decisions are made in architecture, not operations, and they are hard to undo later. Adding a cost lens to design reviews catches the costly pattern before a line of code is written. Here is how.
Scaling up means fewer, larger instances; scaling out means many smaller ones. The per-vCPU price is often similar, but overhead, granularity, and resilience differ enough to change the total. Here is when each is cheaper, with numbers.
Single-tenant gives each customer their own isolated stack; multi-tenant packs many customers onto shared infrastructure. Isolation costs more per customer but simplifies some things; sharing amortizes cost but adds complexity. Here is the cost comparison for SaaS architects.