The ONUG Community is eager to explore the application of AI technology to streamline operator workflows and drive the automation of complex, hybrid multi-cloud infrastructure. In a conference session at ONUG Spring 2019 in Dallas, IT executives and vendors shared perspectives on the challenges of hybrid cloud operations and exchanged ideas for solving the key problem of correlating monitoring data sourced from different operational silos across multiple domains and multiple layers (application, infrastructure and network).

 

A promising approach is to provide an abstraction layer that supports APIs for accessing a virtual data lake that actually consists of multiple repositories for monitoring data. Ideally, this virtual data lake would be cloud-based, simplifying the process of aggregating data from different operational silos while ensuring high performance. This approach also requires data records to adhere to a common format or schema that supports the necessary fields for tagging and enriching data in order to correlate between alerts, events and anomalies spanning multiple silos.

 

The virtual data lake construct enables machine intelligence to be readily applied within a specific operational domain or just as easily between different domains. AI and machine learning algorithms can analyze and correlate monitoring data with other data sources to generate actionable insights for use cases including root cause analysis, performance monitoring, cybersecurity and predictive analytics. The end game, of course, is autonomous operation, utilizing AI so that machines can manage machines, with little or no operation intervention required.

 

Based on the strong interest expressed by participants in this conference session, ONUG is launching a new AIOps for Hybrid Multi-Cloud Working Group at ONUG Fall 2019 in New York. The initial goal is to develop a proof-of-concept (PoC) demonstration that showcases how AI can be applied to managing the availability and performance of a commonly used enterprise SaaS application in a real-world enterprise user environment. The PoC will feature products provided by vendors in the ONUG community that specialize in AI, machine learning and application, infrastructure and network monitoring solutions.

 

Interested in getting involved in an ONUG Working Group? Let us know here.