Digital transformation has been used to describe such a wide variety of things. It's not that it doesn't mean anything, but when it starts to mean everything, it's hard to build a strategy around it.

I think there were two real digital transformations, and we use the same words to talk about them. The first was the transformation of operations themselves, which has been going on for decades. It was about taking your filing cabinet and replacing it with a giant mainframe. You're not changing a product or service, but you're digitizing the way that we deliver it.  And then there's the transformation of customer relationships and of revenue itself. Even if you're not in the business of selling software—if you’re an airline, for example, —you want to have an app. While the first digital transformation was ultimately about being more efficient and delivering things faster and cheaper, the second one is about changing what you're delivering. We use some of the same nouns and verbs to discuss both, but strategically they’re very different.  The challenges—especially in recent years with truly digital products and services, —are truly unique.

Observability is a lot like digital transformation—. It’s a term that's been applied so broadly to so many different things that the definition is a bit blurry. Fundamentally, it’s the ability to understand the insides of a system just given the bits of data that are coming out. It's become increasingly important for complex production software, often run by hundreds or thousands of engineers operating in parallel to make changes to the software while it's running. Observability is the capacity to understand how software is working without a really robust test or staging environment. It’s the only way to actually see how these software applications are working when they're under a real workload affecting real customers and real revenue.

Without good observability, you can't make changes quickly, and you can't react to changes quickly.