Machine Data: Fighting Fire With Fire for Digital Resilience

.conf25 starts Septemer 8th in Boston and to say the least, I’m extremely excited about seeing so many customers and partners in person. Especially, to have the opportunity to hear from them how we can help solve the challenges they are facing amidst the proliferation of AI and its impact on data. One of those challenges that I have been thinking about a lot and which we will cover at .conf is the proliferation of machine data.

Machine data are the application logs, infrastructure telemetry, netflow data logs, and events created by every conceivable digital system. To add to this, AI agents are increasing the volume and complexity of the data at a rate that is beyond human capacity to keep up with, making the management and analytics of this machine data a daunting task. No wonder organizations do not even know how to begin to make sense of it all, much less make the information useful and helpful in an efficient and effective manner.

Talking to our largest customers, it is becoming clear that Agentic AI is rapidly evolving and we are fast moving from human-centric to agent-centric operations. Agents operate at machine speed and scale. They can automatically review and resolve alerts, cutting down the time to monitor and investigate from hours to minutes. This is the proverbial “double edged sword.” The potential benefits are enormous, but we can’t ignore the new challenges that AI presents. Organizations need to make thousands of critical decisions every day — many of which are now powered by AI. But if you’re not careful, AI can run amok and create more problems than it solves. AI can be both a benefit and a threat.

The stakes are incredibly high. Our report "The Hidden Costs of Downtime," which analyzed the direct and hidden costs of unplanned downtime, revealed the total associated costs for Global 2000 companies to be $400B annually, or nine percent of profits, when digital environments fail unexpectedly. This could be due to security incidents, software failures, and other outages that usually occur due to human error.

At Splunk and Cisco, we have a vision for addressing this increase in volume and complexity of data, along with the impact of AI threats operating at machine scale and speed. Our vision is for real time digital resilience that turns the challenge of AI and deluge of data into a solution that is built on these specific two factors. Using AI fueled by machine data, to counter emerging threats at machine scale and speed. To fight AI with AI — fire with fire. We are delivering this vision right now and not in some distant future.

The approach we are taking to leverage AI consists of the following:

At .conf25 we will share more details of this vision. I invite you to join me and Jeetu Patel, president and chief product officer at Cisco, along with customers such as Deloitte, T-Mobile, and Regeneron Pharmaceuticals to hear more about how organizations are maximizing the trust and power of AI to achieve digital resilience in the agentic AI era. See you in Boston!

Follow all the conversations coming out of #splunkconf25!

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