A cloud bill you can explain line by line.

Your first cloud bill was easy to read. Three years later, the total at the bottom is one nobody can explain, with dozens of lines that each come from somewhere. A test environment kept running after a project ended. A disk is no longer attached to a server. A backup history grows a little every night. Nobody did anything wrong. It built up bit by bit.

Where the bill comes from

A cloud invoice is not one amount. It is a stack of separate items: compute by the hour, storage by the gigabyte, data that leaves your environment, licenses, and services that charge per call or per user. While those items are not tied to a project, a client, or a department, there is nothing to steer. So we always start by breaking them down. We pull the last 12 months of usage, add labels, and show which part of the bill belongs to which part of your business.

That overview is often half the work by itself. Once someone sees that an environment used twice a year runs every month, the decision is easy. Data transfer surprises almost everyone too. Moving data in is usually free, moving it out is not, and a report that pulls a full copy every night can cost more than the server running it.

Cutting without breaking anything

Saving is easy if you may switch everything off. The work lies in telling apart capacity nobody uses from capacity that is there for Tuesday morning or the year-end close. So we first measure what a server really does over a longer period, peaks included, and only then adjust the size. Six weeks of measuring prevents the savings round that looked fine in November and stopped your accounting in January.

We also look at what keeps running quietly: disks with no server, old snapshots, test environments for projects delivered long ago, and log files that grow forever because there is no retention period. What can go, goes, but not before you confirm that nobody needs it. We make each change separately and measure it afterward. If something disappoints, we know exactly which step it was.

The right place for each workload

Not every workload belongs in the same place. A database that runs day and night is almost always cheaper on fixed capacity than at an hourly rate. A job that works for a minute a few times a day fits better in Serverless computing, where you pay only for the calls. Archive material you rarely open does not belong on fast disks. It belongs in Object storage (S3), at a fraction of the price per gigabyte.

Sometimes the bill points to a bigger choice. If you run heavy, predictable systems that stay for years, Private cloud or Hybrid cloud is often cheaper than public capacity, even when you count the management. We make such moves only if the numbers hold over several years. We also draw the consequences first within Cloud architecture, before anything moves. Whatever moves stays in our managed environments in European data centers, and your data stays in the EU.

Costs that stay visible

A cleanup works once. Without visibility into usage, in a year and a half there is another bill nobody can explain, because new projects, new environments, and new services keep arriving. So this project does not end with a report. It ends with an overview that updates itself: per month, per project, with the trend of the past period next to it.

We attach limits to it. If an item grows faster than agreed, the responsible person gets a message instead of finding out in the quarterly figures. Systems watch those limits, with an agreed route for who gets called when. You start with a free intake in which we look at your latest invoices, and you remain the owner of your environment, your data, and the scripts we write for you.