AppDynamics surveyed 6,000 global IT leaders about application performance monitoring and AIOps. Read on to discover the trends shaping the space.

Chronically understaffed and constantly stressed-out IT Ops and NOC teams are overwhelmed by today’s IT noise. Artificial Intelligence (AI) and Machine Learning (ML) can help these teams because ML (and AI) are exceptionally good at processing enormous volumes of very complex data in real-time, or near real-time, and surfacing actionable insights. But ML successes in IT Ops are still hit-or-miss.

You’ve just recovered from a critical application outage and your team is being asked to report on root cause and recommended remediation steps later this afternoon. Can you quickly analyze all the data, identify all the leading events, and discern which one was responsible for the cascading failure?

Rapidly increasing IT complexity, customer expectations around application availability and performance, and the importance of supporting new digital initiatives and services, taken together, are placing unprecedented demands on Network Operations Centers (NOCs) and IT Operations teams inside large, complex organizations like yours.

We all know the latest trend in today’s technology and how Machine Learning is changing the way business decisions are made. Machine learning replaces old manual repeatable processes and provides the systems the ability to get into a mode of self-learning without being explicitly programmed.

At first glance, applying machine learning to Continuous Delivery might sound a bit like cracking a peanut with a sledgehammer. I mean, how hard can deployment automation actually be? As it turns out, it’s way more complex than we think.

Automation and efficiency go hand in hand and is something that has been mentioned in IT since the 70’s. Nevertheless, 40 years on, and the majority of companies still have to internalize and embrace automated processes.

With the number of cyberattacks growing with each passing day, the need for increasingly sophisticated security systems has never been higher. Just when these ceaseless attacks had you at your wit’s end, machine learning may just restore some sanity to the cybersecurity scene.