Despite its reputation as a technical field, IT operations require a host of skills and capabilities that are uniquely human. The key to making the most of emerging AI technology is to know how it complements an IT pro, not where it competes.

According to one survey, 94% agree that AIOps is “important or very important” to manage network and cloud applications performance. AIOps intends to help customers contextualize humongous data volumes and streamline IT operations with automation. As IT infrastructure grows in complexity, alerts flood IT Ops centers and Ops teams drown in managing the deluge.

The absence of topology can be a key inhibitor for AIOps tools, creating blind spots for AIOps as they only have access to event data. A topology, an IT service model, or a dependency map is a real-time picture of tools and services that are connected and dependent on each other to deliver an IT service. Suppose an application is driven by cloud-native technology, connected with any kind of ephemeral systems (containers and microservices), and relies on storage, database, and a load balancing tool.

There’s plenty of loaded terminology and buzzword bingo when it comes to the latest advances in cloud application delivery. Especially when it comes to multi-cloud – which should merely mean multiple cloud instances when modern cloud applications really leverage multiple hybrid IT operating models, atop both existing business silos and newer microservices application workloads.

A pivotal inhibitor to mitigate these challenges is the Data Value Gap. Data automation and Data Fabric are emerging as key technologies to overcome these challenges. Learn from industry experts about these key technologies and how they create a lasting impact in enterprise IT.