Azure Advisor cost savings recommendations is limited

One of the challenges the customer had is that Azure is not reporting many rightsizing recommendations in Azure advisor. Nevertheless, there were 19 virtual machines with approximately $60k per year worth of rightsizing recommendations identified by Azure advisor. These had not been implemented by the customer because they had not realized they were there and the recommendations are not easily visible in the scope of the application that would benefit from them.

The customer completed the migration and then recognised that they had missed out on taking advantage of Azure reservations which had resulted in opportunities to reduce the bill by $700k per year. Using Turbo360 they had identified these savings and had implemented appropriate reservations where they can reduce those costs.

The customers next step was to look at rightsizing opportunities. Turbo360 was flagging up a lot of resources which are over provisioned. When the migration was performed an appropriate estimate of the required size for resources was made and then later it is found that these sizings were overestimates.

How Turbo360 identified 1M worth of savings with cost democratization?

With Turbo360 the customer had democratized the management of cost to the operations teams who look after each application. This means instead of having 1 person with the right access and knowledge to look into cost, now every application team can participate in this.

Turbo360 had identified 336 downgrade recommendations which ranged in size from $10 to $12,500.

The application teams can now look to review their rightsizing recommendations within their scope and can easily review resource usage.

The customers teams can now follow the pattern like shown below.

It will take the customer a while to work through the huge number of recommendations they have. Some will be very easy to implement and others will require an impact assessment but the customer will start seeing immediate cost reduction as soon as changes are implemented.

Conclusion

This customer identified a backlog of $1.2 million worth of potential waste in their Azure spend. They have a backlog of items to work through to reduce costs and some of them are individual resources with large cost savings which can be achieved with very little effort.