Azure savings plan recommendations

Azure savings plan purchase recommendations are provided through Azure Advisor, and through the savings plan purchase experience in the Azure portal.

Purchase recommendations in the Azure portal

The savings plan purchase experience shows up to 10 commitment amounts. All recommendations are based on the last 30 days of usage. For each amount, we include the percentage (off your current pay-as-you-go costs) that the amount could save you. The percentage of your total compute usage that would be covered with the commitment amount is also included.

By default, the recommendations are for the entire billing scope (billing account or billing profile for MCA and enrollment account for EA). You can also view subscription and resource group-level recommendations by restricting benefit application to one of those levels.

Recommendations are based the selected terms, so you'll see the 1-year or 3-year recommendations at each level by toggling the term options. We don't currently support management group-level recommendations.

The first recommendation value is the one that is projected to result in the highest percent savings. The other values allow you to see how increasing or decreasing your commitment could affect both your savings and compute coverage. When the commitment amount is increased, your savings could be reduced because you could end up with reduced utilization. In other words, you'd pay for an hourly commitment that isn't fully used. If you lower the commitment, your savings could also be reduced. Although you'll have increased utilization, there will likely be periods when your savings plan won't fully cover your use. Usage beyond your hourly commitment will be charged at the more expensive pay-as-you-go rates.

How hourly commitment recommendations are generated

When Azure recommends an hourly amount for a savings plan, it tries to help you make the most cost-effective commitment. Recommendations are generated by examining your historical on-demand usage. Calculations include any discounts that you might have on your on-demand rates. Usage covered by existing reservations or savings plans is excluded.

The first step is to determine the total on-demand charge from savings plan-eligible resources for each hour during the last 30 days. Each candidate amount is used to determine your recommended hourly commitments.

Azure then runs simulations of what your total costs would have been if each candidate were your hourly commitment for both a 1-year and 3-year savings plan. Simulations are performed for usage at the billing account/profile, and at the subscription and resource group levels.

With each candidate:

  • Some hours will result in savings.
    • For example, when savings plan-discounted usage plus saving plan commitment is less than on-demand charges during that hour.
  • Some hours won't result in savings.
    • For example, when discounted usage plus hourly commitment is greater than or equal to on-demand charges.

For each candidate, Azure sums all simulated hourly charges. The sum is then compared to your actual on-demand charges to determine the total savings provided by that candidate. Because compute usage varies over time, the simulations are run several times a day, using a rolling 30-day usage window.

As the savings are calculated for each candidate, Azure determines the percentage of your compute usage that would be covered by the candidate savings plan plus any other previously purchased reservations or savings plan. For example, when a specific value hourly savings plan commitment results in a specific percentage of your compute usage being covered by one or more savings plans or reservations.

Finally, Azure selects a set of differentiated candidates, currently up to 10 each for 1-year and 3-year commitments, that provide the greatest savings across different compute coverage levels. Azure provides them as recommendations - the amount with the greatest savings for 1-year and 3-year are the highlighted options.

To account for scenarios where there was significant reductions in your usage, including recently decommissioned services, Azure runs more simulations using only the last three days of usage. The lower of the 3-day and 30-day recommendations are highlighted, even when the 30-day recommendation appears to provide greater savings. Azure tries to ensure that you don't overcommit based on stale data.

Reservation trade in recommendations

When you trade one or more reservations for a savings plan, you're shifting the balance of your previous commitments to a new savings plan commitment. For example, if you have a one year reservation with a value of $500, and half way through the term you look to trade it for a savings plan, you would still have an outstanding commitment of about $250.

The minimum hourly commitment must be at least equal to the outstanding amount divided by (24 times the term length in days).

As part of the trade in, the outstanding commitment is automatically included in your new savings plan. We do it by dividing the outstanding commitment by the number of hours in the term of the new savings plan. For example, 24 * term length in days. And by making the value the minimum hourly commitment you can make during as part of the trade-in. Using the previous example, the $250 amount would be converted into an hourly commitment of ~ $0.029 for a new one year savings plan.

If you're trading multiple reservations, the aggregate outstanding commitment is used. You may choose to increase the value, but you can't decrease it. The new savings plan will be used to cover usage of eligible resources.

The minimum value doesn't necessarily represent the hourly commitment necessary to cover the resources that were covered by the exchanged reservation. If you want to cover those resources, you'll most likely have to increase the hourly commitment. To determine the appropriate hourly commitment:

  1. Download your price list.
  2. For each reservation order you're returning, find the product in the price sheet and determine its unit price under either a 1-year or 3-year savings plan (filter by term and price type).
  3. Multiply the rate by the number of instances that are being returned.
  4. Repeat for each reservation order to be returned.
  5. Sum the values and enter it as the hourly commitment.

Recommendations in Azure Advisor

When appropriate, a savings plan purchase recommendation can also be found in Azure Advisor. Keep in mind the following points:

  • The savings plan recommendations are for a single-subscription scope. If you want to see recommendations for the enrollment account or billing profile, then navigate to Savings plans > Add and then select the type that you want to see the recommendations for.
  • Recommendations available in Advisor consider your past 30-day usage trend.
  • The recommendation is for a three-year savings plan.
  • The recommendation calculations reflect any discounted on-demand usage rates.
  • If you recently purchased a savings plan, Advisor reservation purchase and Azure saving plan recommendations can take up to five days to disappear.

Next steps