which ones are under active development, the locations of the development teams, the
number of expected releases and hours of active use per week or per month. Once this
is done, you will see that things like user acceptance testing (UAT) environments are
prime candidates for being turned off, since they may only be used for a short time
before each monthly release. Similarly, development environments are likely to be used
only during regular business hours, and could be spun down overnight and on the
weekends.
The cost reductions you can achieve by managing the uptime of environments are
enabled by the on-demand, pay-as-you-go payment models available through the cloud
providers. With this type of flexible pricing, you are billed per hour or even per second
for the compute resources that you consume, depending on the provider and the ser-
vice. However, there are other opportunities to reduce your cost by utilizing other pay-
ment methods. Most notably, the Reserved Instance (RI) payment model, available in
AWS and Azure, allows your organization to reserve compute resources for one or three
years, and recognize significant cost savings when compared to operating those same
resources continually in a pay-as-you-go scenario. Depending on the cloud platform
your organization uses, a payment model strategy is key to driving down costs.
Payment model strategies may vary per cloud, but we have developed general best
practices that apply across platforms. One notable strategy is to pre-purchase capacity
up to a level your organization is certain it will use. This typically means all produc-
tion-level environments will be running on reserved instances, and that you should stag-
ger purchasing new reservations across each quarter to account for variability in
demand. This allows you to adapt to variations in your usage patterns, and also gets you
out of the mindset of needing to overprovision to allow for the distant future. This is also
why we recommend sticking with one-year instead of three-year reservations. While the
three-year reservations may provide better cost reduction options, they require the
same inflexible capacity forecasting seen on-premises.
Production environments are not the only cases which can benefit from reservations.
Every instance (regardless of environment) has a break-even point where the on-de-
mand payment model will end up being cheaper than the long-term reservation.
Reserved Instance cost ($/month)
On-Demand cost ($/hr)
= Break-Even Point (hrs/month)
If you are expecting to use a non-production instance for fewer hours than the calcu-
lated break-even point, it makes more financial sense to use an on-demand payment
model. Conversely, if you expect to have an instance running for more hours than the
calculated break-even point, it makes more financial sense to purchase a reservation.
There are cost-reduction opportunities related to your billing and account structure
that you may be benefiting from without even knowing it. There are settings, usually
enabled by default, which allow your reservations to be shared across accounts. This
means that if you make a reservation in one account, and do not end up needing it for
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