Cisco Splunk: Agentic Observability, Token Economics and the Smaller War Room, Podcast, Cisco and Splunk are focused: helping customers bring the right information together, with the right context, so AI can be useful rather than overwhelming
By Doug Green
“The real opportunity is helping customers pull together all the different sources of data into an environment where they can understand when they need to pay attention, how to find and fix problems, and how to layer AI on top of that.”
In this Technology Reseller News podcast, recorded at Cisco Live, I spoke with Patrick Lin of Cisco Splunk about the changing role of observability in a hybrid, AI-driven IT environment — and why the conversation now also includes token economics.
As AI becomes part of everyday IT operations, enterprises are beginning to ask a new economic question: how much does it cost to reason over all this data? In an AI-native environment, every log, metric, trace, network signal and security event may become part of a larger decision-making process. That creates value, but it also creates cost. Token economics becomes part of the observability discussion because customers need to know what data matters, when to use AI, and how to get better answers without flooding systems with unnecessary context.
That is where Cisco and Splunk are focused: helping customers bring the right information together, with the right context, so AI can be useful rather than overwhelming.
Lin described how Cisco and Splunk are connecting observability, networking intelligence and AI-native workflows to help teams see across complex environments. A key example is the integration between ThousandEyes and Splunk Observability Cloud, giving teams the ability to understand whether a problem is happening in the application or in the network — and, if it is in the network, whether the issue is in the part of the network they own or the part they do not.
That distinction matters. In hybrid environments, responsibility is often shared across enterprise infrastructure, cloud platforms, service providers, SaaS applications and third-party systems. Knowing where the problem lives can dramatically reduce the time teams spend in war rooms trying to determine what went wrong.
Lin also pointed to Cisco Cloud Control and AI Canvas as part of a broader AI-native approach. Rather than forcing users to jump across separate tools and interfaces, Cisco is working toward a model where information from Splunk, Cisco platforms and the wider ecosystem can be brought into a collaborative environment. That includes human teammates as well as agentic assistants that can help teams reason across data, identify patterns and accelerate troubleshooting.
For channel partners, Lin said the opportunity is significant. Customers need help bringing together data sources, building the right observability foundation and applying AI in practical ways. Partners can play a key role in making agentic observability real for customers by helping them move from disconnected monitoring tools to a more unified, intelligent operating model.
The goal, Lin said, is not just more data. It is a “much, much smaller war room” when incidents happen.
For Cisco Partners, that message is timely. As customers modernize applications, adopt AI, expand hybrid environments and depend on increasingly distributed infrastructure, observability becomes more than an IT operations tool. It becomes a business resilience capability.