Update advisor-cost-recommendations.md

Author: themar-msft

articles/advisor/advisor-cost-recommendations.md

@@ -16,44 +16,46 @@ Azure Advisor helps you optimize and reduce your overall Azure spend by identify
 
 1. On the **Advisor** dashboard, select the **Cost** tab.
 
-## Optimize virtual machine spend by resizing or shutting down underutilized instances 
+## Optimize virtual machine (VM) or virtual machine scale set (VMSS) spend by resizing or shutting down underutilized instances 
 
-Although certain application scenarios can result in low utilization by design, you can often save money by managing the size and number of your virtual machines. 
+Although certain application scenarios can result in low utilization by design, you can often save money by managing the size and number of your virtual machines or virtual machine scale sets. 
 
-Advisor uses machine-learning algorithms to identify low utilization and to identify the ideal recommendation to ensure optimal usage of virtual machines. The recommended actions are shut down or resize, specific to the resource being evaluated.
+Advisor uses machine-learning algorithms to identify low utilization and to identify the ideal recommendation to ensure optimal usage of virtual machines and virtual machine scale sets. The recommended actions are shut down or resize, specific to the resource being evaluated.
 
 ### Shutdown recommendations
 
 Advisor identifies resources that have not been used at all over the last 7 days and makes a recommendation to shut them down. 
 
 -	Recommendation criteria include **CPU** and **Outbound Network utilization** metrics. **Memory** is not considered since we’ve found that **CPU** and **Outbound Network utilization** are sufficient.
 - The last 7 days of utilization data are analyzed
-- Metrics are sampled every 30 seconds, aggregated to 1 min and then further aggregated to 30 mins (we take the max of average values while aggregating to 30 mins)
+- Metrics are sampled every 30 seconds, aggregated to 1 min and then further aggregated to 30 mins (we take the max of average values while aggregating to 30 mins). For virtual machine scale sets, the metrics from individual virtual machines are aggregated using the average of the metrics across instances.
 - A shutdown recommendation is created if: 
   - P95th of the maximum value of CPU utilization summed across all cores is less than 3%.
   - P100 of average CPU in last 3 days (sum over all cores) <= 2%   
   - Outbound Network utilization is less than 2% over a seven-day period.
 
 ### Resize SKU recommendations
 
-Advisor recommends resizing virtual machines when it's possible to fit the current load on a more appropriate SKU, which is less expensive (based on retail rates). 
+Advisor recommends resizing virtual machines when it's possible to fit the current load on a more appropriate SKU, which is less expensive (based on retail rates). FOr virtual machine scale sets, Advisor recomments resizing when it's possible to fit the current load on a more appropriate cheaper SKU, or a lower number of instances of the same SKU.
 
 -	Recommendation criteria include **CPU**, **Memory** and **Outbound Network utilization**. 
 - The last 7 days of utilization data are analyzed
-- Metrics are sampled every 30 seconds, aggregated to 1 min and then further aggregated to 30 mins (we take the max of average values while aggregating to 30 mins)
-- An appropriate SKU is determined based on the following criteria:
+- Metrics are sampled every 30 seconds, aggregated to 1 min and then further aggregated to 30 mins (we take the max of average values while aggregating to 30 mins). For virtual machine scale sets the metrics from individual VMs are aggregated using the avg of the metrics for instance count recommendations, and aggregated using the max of the metrics for SKU change recommendations. 
+- An appropriate SKU (for virtual machines) or instance count (for virtual machine scale set resources) is determined based on the following criteria:
   - Performance of the workloads on the new SKU should not be impacted. 
     - Target for user-facing workloads: 
       - P95 of CPU and Outbound Network utilization at 40% or lower on the recommended SKU 
       - P100 of Memory utilization at 60% or lower on the recommended SKU
     - Target for non user-facing workloads: 
       - P95 of the CPU and Outbound Network utilization at 80% or lower on the new SKU
       - P100 of Memory utilization at 80% or lower on the new SKU 
-  - The new SKU has the same Accelerated Networking and Premium Storage capabilities 
-  - The new SKU is supported in the current region of the Virtual Machine with the recommendation
-  - The new SKU is less expensive 
+  - The new SKU, if applicable, has the same Accelerated Networking and Premium Storage capabilities 
+  - The new SKU, if applicable, is supported in the current region of the Virtual Machine with the recommendation
+  - The new SKU, if applicable, is less expensive 
+  - Instance count recommendations also take into account if the VMSS is being managed by Service Fabric or AKS. In the case of service fabric managed resources, recommendations take into account reliability and durability tiers. 
 - Advisor determines if a workload is user-facing by analyzing its CPU utilization characteristics. The approach is based on findings by Microsoft Research. You can find more details here: [Prediction-Based Power Oversubscription in Cloud Platforms - Microsoft Research](https://www.microsoft.com/research/publication/prediction-based-power-oversubscription-in-cloud-platforms/).
 - Advisor recommends not just smaller SKUs in the same family (for example D3v2 to D2v2) but also SKUs in a newer version (for example D3v2 to D2v3) or a different family (for example D3v2 to E3v2) based on the best fit and the cheapest costs with no performance impacts. 
+- For VMSS resources, Advisor prioritizes instance count recommendations over SKU change recommendations due to the easy actionability of instance count changes, resulting in faster savings. 
 
 ### Burstable recommendations
 
@@ -64,17 +66,17 @@ We evaluate is workloads are eligible to run on specialized SKUs called **Bursta
   - If the P95 of CPU is less than two times the burstable SKUs' baseline performance
   - If the current SKU does not have accelerated networking enabled (burstable SKUs don’t support accelerated networking yet)
   - If we determine that the Burstable SKU credits are sufficient to support the average CPU utilization over 7 days
-- The result is a recommendation suggesting that the user resize their current VM to a burstable SKU (with the same number of cores) to take advantage of the low costs and the fact that the workload has low average utilization but high spikes in cases, which can be best served by the B-series SKU. 
+- The result is a recommendation suggesting that the user resize their current virtual machine or virtual machine scale sets to a burstable SKU (with the same number of cores) to take advantage of the low costs and the fact that the workload has low average utilization but high spikes in cases, which can be best served by the B-series SKU. 
 
-Advisor shows the estimated cost savings for either recommended action: resize or shut down. For resize, Advisor provides current and target SKU information.
-To be more selective about the actioning on underutilized virtual machines, you can adjust the CPU utilization rule on a per-subscription basis.
+Advisor shows the estimated cost savings for either recommended action: resize or shut down. For resize, Advisor provides current and target SKU/instance count information.
+To be more selective about the actioning on underutilized virtual machines or virtual machine scale sets, you can adjust the CPU utilization rule on a per-subscription basis.
 
 There are cases where the recommendations cannot be adopted or might not be applicable, such as some of these common scenarios (there may be other cases):
-- Virtual machine has been provisioned to accommodate upcoming traffic
-- Virtual machine uses other resources not considered by the resize algo, i.e. metrics other than CPU, Memory and Network
+- Virtual machine or virtual machine scale set has been provisioned to accommodate upcoming traffic
+- Virtual machine or virtual machine scale set uses other resources not considered by the resize algo, i.e. metrics other than CPU, Memory and Network
 - Specific testing being done on the current SKU, even if not utilized efficiently
-- Need to keep VM SKUs homogeneous 
-- VM being utilized for disaster recovery purposes
+- Need to keep virtual machine or virtual machine scale set SKUs homogeneous 
+- Virtual machine or virtual machine scale set being utilized for disaster recovery purposes
 
 In such cases simply use the Dismiss/Postpone options associated with the recommendation.