Forecasting is the process of making predictions based on our assumptions about the factors driving the data of interest and its actual past and present values. The key value of having accurate forecasts is that they allow to be proactive, rather than reactive.
In 2020, for one in three respondents, cloud spend was projected to be over budget by between 20 percent and 40 percent. One in 12 respondents said their cloud spend was expected to be over budget by more than 40 percent.
– Pepperdata
Making wrong or no forecasts has a high cost for your Company. Many have wondered if it’s a good idea to forecast at all. In our experience, the answer is yes. While nobody owns a crystal ball, a conversative forecasting model prevents the damage from wild guesses, that, if you don’t build a good model, your team will still implicitly make irrespective on their opinion that forecasts were a bad idea or look at someone else’s model. There is no discussion about this, we saw it happen in small and large Companies.
In the AWS context, we recommend forecasting both usage and spend
- accurate usage forecasts allow, for example,
- to purchase the right number of reserved instances / savings plans
- to accurately decide the EC2 / RDS instance type and whether to use serverless instead
to accurately set up AWS services parameters
accurate cost forecasts allow, for example,
to create realistic budgets and thus better allocate resources – such as time, money, hiring etc.
to help with the solution pricing
to determine the cost-effective technology given the expected revenue.
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