You’ve likely heard some variation of the saying, “We can’t succeed tomorrow with today’s capabilities.” It’s not a new concept. Innovation is key to the survival of any industry or business. The same is true for the enterprise architectures that business is built upon.
An innovation receiving a lot of attention lately is generative AI. But AI, powered by machine learning, is built upon the foundation of automation. And while you can automate manual processes and repetitive tasks, the success and force multiplier of automation isn’t truly realized without its counterpart, observability.
Take for example innovations within the automotive industry and their impact on the average driver. If you were on the road 25-30 years ago, it’s likely there was a map present in the glove compartment of your car. If you were traveling somewhere new without a co-pilot to help you navigate your route when you missed a turn or exit, you would have to pull over, lay said map out on the front of your car, and squint at tiny lines and street names to course correct.
Insert observability and automation. With advancements in Global Positioning System (GPS) tracking—which is essentially an influx of location data, or telemetry, that can identify longitudinal and latitudinal location—drivers could use personal navigation devices to know where they were in relation to their destination without having to drive to the nearest street sign. Additionally, these navigation devices included automation capable of using the observed telemetry to reroute the path of a driver to their end destination. Then it was just up to the driver to follow the new course.
Digital businesses, unlike their brick-and-mortar counterparts, can’t thrive without observability and automation capabilities included in the enterprise architecture. The digital experience of customers is tied to the availability, security, and performance of the business’ digital service.
Monitoring the elements of a digital service requires full stack observability of all systems and applications, across all locations—on prem, in the cloud, and at the edge—to recognize performance degradations and identify threats before they can seriously impact the consumer experience, and in turn the business. But even with insights gleaned from the flow of operational data, without full automation the digital experience is at risk. Manual actions, remediation, and mitigation cannot meet demand at scale, because “there is no room for human intervention when milliseconds matter.” And that is what we’re talking about when we consider a truly digital business.
Take for instance the earlier driver using their navigation system. The system automation only extends so far; it is up to the driver to make the choice to follow the new course. And if you’ve ever been driving in the city waiting for your GPS to reroute you may have experienced the repeat frustration of just missing your turn again and again because of the additional time it takes for the system to process the data that says you are off course, identify a new path, and update your map just as you finish rolling through the intersection it rerouted you to. Full automation for your digital service is more like self-driving cars. Within their architecture, observability and automation are clearly not afterthoughts. They’re fully integrated into the foundation to ensure constant evaluation, analysis, and action is taken for the optimum passenger experience.
In both the case of digital business and (with rare exceptions) driving a car, humans remain the ultimate decision makers. But making optimal decisions requires information, and that information comes from digital signals—whether from a GPS system or a full-stack observability capability. Digital business can't course-correct any faster than decisions can be made, and the speed with which decisions are made is entirely reliant on the speed with which a system can ingest, analyze, and produce actionable insights. For digital business, that means observability and automation. Therefore, we must modernize the enterprise architecture to include these as core capabilities.
To learn how to instrument these key capabilities and the added benefits they provide to a digital business, read “Observability and Automation,” a chapter by VP of Engineering and CTO of Applications, Mike Wiley, in our O’Reilly book, Enterprise Architecture for Digital Business.