Cloud Hosting Cost Calculator — Estimate Monthly Spend in 60 Seconds

A cloud bill is really four bills stacked on top of each other: compute, storage, data egress, and managed services. This calculator estimates each line separately and then sums them, so instead of one intimidating total you get a breakdown that tells you where the money actually goes. Everything runs locally in your browser as you type — no account, no API calls, no data leaving your machine.

Compute is the largest line for most application workloads. We multiply your instance count by a blended hourly rate and by the hours each instance runs per month. A full always-on month is roughly 730 hours, so lowering the monthly-hours input is how you model autoscaled, scheduled, or spot workloads that are not running 24/7. Storage is priced per GB-month at a rate you control, defaulting to a typical general-purpose SSD figure. Egress — data transferred out to the internet — is billed per GB and is the line that surprises teams most often. Managed database is entered as a flat monthly figure because hosted database pricing varies so widely by engine, size, and replica count that a single field is more honest than a fake formula.

Why egress is the line to watch

Storing a gigabyte costs a couple of cents a month. Moving that same gigabyte out to your users can cost ten to twenty times as much, and unlike compute it scales directly with traffic and product success. A viral launch or a chatty mobile client can multiply egress overnight while every other line stays flat. That is why a content-delivery network and a sensible caching strategy are among the highest-leverage cost decisions you can make — they turn repeat egress into cache hits you do not pay full freight for.

What this calculator deliberately leaves out

This is a planning estimate, not an invoice simulator. Real bills add load balancers, public IP addresses, snapshots and backups, inter-availability-zone traffic, NAT gateways, per-request charges, logging and monitoring, and a support plan on top. Pricing also differs by provider and region for the exact same resource. The simplifications are what make this fast and useful for an architecture gut-check; when you need a number you can put in a budget, we model the real line items against a specific provider and region. Our engineering blog goes deeper on the trade-offs, and the glossary explains the terms if any of this is new.

When cloud cost becomes an engineering problem

There is a predictable point where the cloud bill stops being a finance line item and becomes an engineering project: when it grows faster than usage. That is usually a signal of over-provisioned compute, missing caching, on-demand pricing for steady baseline load, or hot storage holding cold data. Right-sizing, reserved-capacity commitments, a CDN, and tiered storage routinely cut a bill by a third or more without touching the product. Owning that optimization work — and the infrastructure decisions that prevent the sprawl in the first place — is part of what our software development practice does.