Our Inaugural Product Update!

Welcome to the Reserved.ai inaugural product update! By popular demand from our customers we're excited to showcase some of the changes we've been working on to save you money on your AWS (and now Azure, but let's not get ahead of ourselves) bill. So, without further ado...

Azure Support in Open Beta

Support for Azure is now in open beta! Same great reservation optimization, easy install, and automation where it counts.

Like you, we can't afford to be locked in to one cloud provider: that's why we've architected our own infrastructure to be entirely cloud-agnostic. Similarly, our vision for Reserved.ai is to provide a cloud-agnostic spend optimization solution for our customers on AWS, Azure, or GCP. This release for our Azure customers marks the first major landmark in that pursuit!

In building support for Azure, we encountered a couple of challenges, most notably providing the same safety & authentication that our AWS customers required. This became not only a function of providing top-notch security standards and conforming with Azure best practices, but also ease of use for users that may be entirely new to Azure. After too many iterations to count and many productive conversations with the Azure team, we've created a simple onboarding process that guarantees safety and security of all data.

DynamoDB Reservation Optimization

When you think of reserving machine hours or committing to a certain spend per hour, your thoughts probably go to "please, no" or something similarly abysmal. If you're a special kind of DevOps professional, you may think "Reserved Instances" or "Savings Plans," but usually not "Provisioned Write/Read Capacity for DynamoDB."  This one has been on our backlog for a while and we're excited to finally release it, due in no small part to collaboration with a customer (thanks, D.S.!).

Reserving Write and/or Read Capacity can lend to some deep savings, but choosing how many units to reserve can be extremely tricky. Usage often varies by time of day or week and when usage goes above your reserved units threshold, you pay expensive on-demand prices. When usage dips below your reserved units threshold, you're paying for capacity you're not using. This new tool calculates the optimal amount of units to reserve given historical usage and exiting commitment.

Amortized & Unblended Costs

The Summary Page now includes amortized and unblended costs across services, accounts, or regions, meaning more transparency for where your money is going.  

One of the most common questions we received from our early customers was "Hey, why don't you match Cost Explorer?" Well, as much as we'd like to stay away from the unnecessary complexity of Cost Explorer, we do want to provide our users the ability to compare the few important metrics apples-to-apples. So, we've added that option to access both the Amortized costs (including those pesky support and tax costs) on the Summary Page. You can access this by clicking the logo in the top left next to the Group By and Date dropdowns or by clicking the button below.

Cost of Capital

For your FP&A team, where to spend money across AWS services is often a question pondered for a few minutes then cast aside never to be brought up again or the beginning of spreadsheets with tens of thousands of rows and complex models that don't seem to achieve any sort of optimal solution.

Inside our Reservation Recommendation Engine, accessible on the Purchase Dashboard, we allow any user to model out where (for every dollar you're inclined to give Mr. Bezos now instead of later) that money should go to achieve the highest discount available.

We've updated our default cost of capital in the upfront spend optimizer from 5% to 10%. If you'd like to use a custom cost of capital for your organization, let us know and we can make the change to fit your business needs.