Blackberries, Blockbusters and AS400s ruled supreme back when we were building the company nine years ago. At this time, most phones didn’t have GPS, most shopping was in person and most computing happened in one place. It seemed like much simpler times, right? Yet massive disruption was on the horizon that would completely shake up how people used and thought about technology.
Brace yourself – SaaS is coming. This radical movement proved that abstracting complexity can not only free businesses from fretting over the nuts and bolts of infrastructure, but it can also free them to think bigger about what they can accomplish through technology. This was a huge wake up call for our entire industry, and became my obsession, and our inspiration for AppDynamics.
What if the principles of SaaS were applied to monitoring solutions? What if stripping away complexities of reporting and alerting about applications could free businesses in a similar way?
After many late nights working out how software can be more of a business enabler and less of a management burden, came the invention of our machine-learning powered Business Transaction, the foundation of AppDynamics.
It’s hard enough for businesses to stay on top of the latest trends and shifting needs of consumers, managing applications should come secondary to hitting business goals. So, we engineered our product with business performance as the top priority. By pairing the right business metrics with the noise-cancelling abilities of machine learning, the root cause of business-impacting problems are brought to the forefront and many intricacies of related symptoms are collapsed underneath. As a result, enterprises get a straightforward, dynamic baseline that intelligently evolves with the business. And, for the first time, the world’s most complex systems can transform into real competitive advantages.
As time went on, digital strategies became synonymous with business strategies and consumer expectations rose to a point where “next-day” isn’t fast enough. To keep up with the pace set by titans like Apple, Google and Amazon, enterprises entered uncharted territories in cloud, DevOps and IoT causing new levels of strain on technical teams. On top of that, these developers, IT pros and CIOs were challenged to defend these changes to business colleagues who are asking if it’s worth their time and money.
The evolution of enterprises’ needs have always been the fire for our innovations and today’s announcement is no exception. With systems continuing to sprawl, businesses need a way to make sense of it all – from the depths of networking to the edge of multi-cloud. So we’re widening our scope to capture exactly how devices and the network impact the business. Another side effect of distributed systems are blind spots in customer interactions, which make it harder for CIOs to map customer journeys. To help provide a more complete view, our vision for the next generation of Business iQ is to link various distributed business events for a fuller picture that can boost opportunities to stay competitive in customer experience.
With the unrelenting rush of data coming in from countless sources, we see machine learning as the next big disruptor on the horizon. Machine learning, which sounded like science fiction not too long ago, has reached critical mass in its abilities to spot patterns for predictive analytics and automation. It can also be found in our latest announcement simplifying troubleshooting to a click. With new devices coming out daily, we don’t see data slowing down anytime soon, so expect to see more developments in machine learning from us that will help enterprises achieve the scale and speed needed to take on whatever is next in this on-demand, data-driven world.