Turn Data into Strategy for Smarter Asset Management

So you’re going to build a multi-tenant application and now it’s up to you to figure out how to make it all work. Ask any software engineer who has built one and they will tell you that multi-tenant applications are inherently more complicated than single-tenant applications. That complexity comes from the added overhead required to ensure that your tenants’ data are secured and isolated from one another (e.g., Tenant 1 can’t see Tenant 2’s customer list) and that large tenants don’t adversely affect other tenants in the same environment (e.g., Tenant 1 does not use all the resources, thereby slowing the performance for Tenant 2). The overhead caused by these requirements may take the form of either operational or developmental complexity, but the key to building an effective system in any multi-tenant scenario is to reduce that complexity.

How do you handle customer #2? You delivered an MVP of some hosted software for customer #1. Your brother-in-law knows a guy who has a similar problem and after a lunch meeting, now you need to add customer #2 to your incubating SaaS tool. Of course customer #1 and customer #2 shouldn’t be able to see each other’s data, but you don’t necessarily want to install and configure everything all over again just because you added another customer.

Unit of measure conversions are a constant concern in scientific code. Most well written scientific domain kernels should be unit un-aware because the equations of nature are generally unit invariant: momentum is mass times velocity whether velocity is in meters per second or furlongs per fortnight. But there are always important places where the actual values matter: water boils at 100 degrees Celsius. Therefore one typically assumes a set of canonical units in the computational domain to make the programming more straightforward. It’s also more efficient and numerically stable to only translate units on the boundaries of the computation domain, rather than littering them throughout.