Operations | Monitoring | ITSM | DevOps | Cloud

On this episode of Masters of Data, we sat down with Patrick Kobly, who runs security for a boutique MSSP serving fintech, crypto, and gaming clients, to dig into how phishing has evolved past the obvious tells. Kobly walks through how attackers spin up reverse proxies behind Cloudflare, route through residential IPs to dodge reputation-based blocking, and can take a fake domain from registration to full attack in under five hours. The conversation turns into an unexpected case for treating SEO as a security discipline, since search rank and AI-generated results are now part of the attack surface too.

This video provides an overview of Macros in Sumo Logic and how they can be used in search queries. It also introduces nested Macros and Macros with arguments, with examples of how Macros can be incorporated into searches.

This video demonstrates how to use Mobot to investigate issues, interpret its findings, and identify recommended next steps. Follow along as Mobot responds to a prompt by understanding your intent, gathering relevant data, performing multi-step analysis, reasoning across data sources, surfacing insights, and recommending next steps.

This video introduces Mobot, an AI-powered chat assistant built into Sumo Logic, and provides an overview of its key capabilities, the AI features that power it, alongside the Unified Conversational Interface. It gives you a foundation for understanding how Mobot can support and accelerate investigative workflows.

This video introduces Sumo Logic's SOC Analyst Agent, an AI-powered tool within the Dojo AI platform designed to transform security operations centers.

Learn about the Sumo Logic MCP Server -- allowing the use of Sumo Logic data and functionality in conjunction with your AI-driven tools (such as Claude Code or Github Copilot) to support agentic AI workflows for your organization.

Join us as Sunil teaches how Sumo Logic is advancing observability with OpenTelemetry, AI, and automated investigations to help teams gain insights and resolve issues faster.

On this episode of Masters of Data, we unpack what it actually means to expect AI to be the primary interface for everything we do. We dig into the pull toward centralizing work in a single hub like Claude versus staying spread across specialized tools like Slack, Asana and Zoom, and where the line sits between helpful automation and letting an agent speak on your behalf. We also get into the "chief of staff" agent workflow for daily roundups and why specialized, best-of-breed tools aren't going anywhere, even as hubs get smarter.

On this episode of Masters of Data, we revisit the predictions Adam White, Zoe Hawkins, and David Girvin made at the end of last year, checking our own scorecard halfway through 2026. The hits: agents running amok and deleting databases, MCP becoming the backbone for tracking what agents actually do, growing security gaps around personal data, and a collective rejection of low-quality AI content. The misses: we underestimated how fast companies would cut staff for AI, then quietly start rehiring once the agents couldn't cover the work, and we're still arguing about whether token burn is a cost problem or a coming attack vector.