The Rise of AIOps: How Data, Machine Learning, and AI Will Transform Performance Monitoring
AppDynamics surveyed 6,000 global IT leaders about application performance monitoring and AIOps. Read on to discover the trends shaping the space.
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.