In the summer of 2015, we ran a high monthly bill and a lot of EC2 instances. See our historic AWS usage below:
Historic AWS Usage During summer 2015, we had already begun planning for the holiday season. As a company that manages returns and D2C sales, we knew our inventory would increase. We knew that we could scale and spend our way through the holidays, but Optoro aimed to maintain a high level of volume after the season ended. We had already started hitting the limits of what our AWS magnetic volumes could handle on our principal MySQL database server, as well as our MongoDB cluster. Once the holidays arrived, our expenditures would continue to increase to cover newer GP2 disks, which cost more on AWS. Given the high traffic levels, our annual spend would have increased even more than we anticipated.
To determine the best way to tackle this issue, we chatted with our resident financial analyst, Josh Burns, reviewed quotes from vendor conversions, and created a financial model. We knew that Optoro prioritized spreading out payments and moving away from three-year RIs in order sustain long-term flexibility, and when creating the model, we aimed to compare the value of AWS to the value of running on our own system. Our cloud cost estimation assumed a 2% increase every month (this was our historic average) and building 1 YR all upfront RIs (for which Amazon provides us with a 40% overall discount on our EC2 instances). We did not factor performance into this model because AWS instances have variable performance across the board, so we considered AWS to be as performant as bare metal. As a result of our analysis, we concluded that moving onto our own servers would reduce our costs by a significant amount (see below).