Observability has become a cornerstone for enterprises as companies harness the full potential of generative artificial intelligence capabilities driven by cloud-native tools. Several emerging trends show that more than a buzzword, gen AI in observability is a critical capability driving the future of IT infrastructure and application resilience.

Splunk’s Nimish Doshi and Dan Holmes talk to theCUBE about gen AI in observability.

“As the architectures and infrastructures supporting applications move to the cloud, it’s introducing a change in how organizations build, run and operate applications, and then more importantly, how organizations ensure resilience in that application experience,” said Dan Holmes (pictured, right), director of observability advisory at Splunk Inc. “I think that’s the first. The second one that I think AI is starting to introduce is we’re all coming back to the killer app again.”

Holmes and Nimish Doshi (left), director of technical advisory at Splunk, spoke with theCUBE’s John Furrier at the AWS Financial Services Symposium, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how organizations can drive innovation, enhance performance and deliver superior user experiences by focusing on comprehensive, unified observability solutions. (* Disclosure below.)

The role of gen AI in observability

Today’s intricately built applications demand high observability to ensure they function correctly and deliver the intended user experience. As AI continues to evolve, it brings new challenges and opportunities in how applications are designed and managed, emphasizing the importance of observability in this context, according to Holmes.

“If you look at what’s happening at the data level of analytics is the initiative around OpenTelemetry,” he said. “The diversity of infrastructures, platforms and applications have exploded. And anticipating that explosion is what inspired the Cloud Native Computing Foundation to really mature OpenTelemetry, which gives a high-quality data source regardless of its source.”

Synthetic monitoring involves simulating user interactions with websites and application programming interfaces to proactively identify and resolve issues before they affect real users. Application performance monitoring and infrastructure monitoring complement this by providing detailed insights into the performance and health of applications and their underlying infrastructure. As the role of gen AI in observability matures, combining these capabilities into a unified observability platform represents the state-of-the-art in monitoring technology, according to Doshi.

“Most applications that are in the financial services, they’re not going to be a 100% cloud,” he said. “They’re going to be sometimes on-prem, a lot of it on cloud, depending on what the services are. And the ability to trace on different platforms, different clouds for that matter, hybrid clouds, that is going to be a new trend as time goes on.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the AWS Financial Services Symposium: 

(* Disclosure: Amazon Web Services Inc. and Splunk Inc. sponsored this segment of theCUBE. Neither AWS, Splunk nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE