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How SeatGeek Decoded Its AWS Bill and Measured Cost Per Customer

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3 Things Finance Teams Should Understand About AWS (Straight from Engineering)

AWS finance can get complicated. Here are three things any CFO should know about working with engineering to understand the AWS bill.

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If you’re a CFO or finance leader at a company that uses public cloud services like AWS, chances are you’ve had a bill cross your desk that may seem confusing. You or your team of financial analysts may have frequent conversations with engineering about how AWS services are allocated across different engineering initiatives. 

Understanding a few key things up front may save time in these conversations, and help you navigate some of the most frequently questions about how AWS finances relate to engineering initiatives. Here’s  some advice from an engineer on three key things to understand about AWS:

Know the difference between R&D and production costs.

One of the most important things to understand about AWS is how much of the monthly bill is allocated to production in engineering versus R&D. For many companies, R&D costs can be written off the year in which those costs occur. (However, it’s important to note that upcoming changes to the tax law will require that by 2022, these costs are amortized over five years, which may change the budgeting conversation slightly).

Regardless, engineering should have a firm understanding about which AWS accounts or shared databases are partitioned to production or R&D. When calculating the monthly or quarterly OpEx budget, it’s important to collaborate with engineering leadership to understand this exact breakdown. 

Managing toward COGS may be more efficient than strict AWS budgeting.

Unfortunately, public cloud provider costs at a fast-growing SaaS company may be difficult to accurately budget and predict. Instead, managing toward cost of goods sold (or COGS) may be an easier parameter for engineering to operate within. For example, one product line at the company may be its biggest seller, so more investment may go toward that product (which would, in turn, require more AWS spending to sustain innovation and growth).  If that product has especially high operating costs, engineering may want to prioritize rearchitecting it. 

Or, in other cases, such as with new products, expected COGS figures can be useful for engineering teams to map toward when determining their budgets for the month or quarter. That way, if something changes within the product roadmap that requires a shift in AWS provisioning strategy, the engineering team can quickly act on it without slowing down to ask permission from finance. 

A single source of truth can answer questions about cost anomalies and more.

Here’s a common scenario: an important customer could require scale testing that causes a temporary AWS cost spike. You approach engineering about an unexplained AWS cost, and they justify it to finance by explaining why the customer needed this testing. 

Instead of having to ask questions around every cost anomaly, a single source of truth on cloud spending, such as CloudZero, provides both finance and engineering with data on exactly what’s causing cost spikes and why. If an expected event (such as scale testing) happens, engineering can proactively approach you to justify costs in advance. 

If an unexplained anomaly happens, engineers can fix problems in-the-moment, rather than after you get the monthly bill (and costly errors have added up to meaningful dollars and cents). In addition, CloudZero can help you understand other common questions about R&D vs. production spending, and how AWS costs are broken down within specific product lines.

What AWS spending data do you wish you had access to? Reach out to us to learn more about how CloudZero can help!

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