Sumo Logic announced new and expanded agentic AI capabilities that translate telemetry into actionable signals and insights for Security and Cloud Operations teams.
Sumo Logic SOC Analyst Agent, MCP Server, and a new version of its conversational interface, Mobot, extend agentic AI across both security and observability workflows.
"We believe that telemetry is the fuel of the AI future," said Jeremy Powell, CISO for Sumo Logic. "Every threat detection, investigation, and response traces back to telemetry. As AI agents become an increasingly valuable tool for security operations, telemetry is the source of truth that separates a confident answer from an educated guess. We're seeing this in our very own SOC, building from trusted telemetry from Sumo Logic Dojo AI, we were able to reduce MTTR by 64% and saved 25 hours per week per analyst."
Sumo Logic's Dojo AI agentic platform is built on its secure data lake, SIEM and context layer that normalizes, correlates, and enriches telemetry, creating signals autonomous agents need to quickly and accurately identify and resolve issues.
The Sumo Logic Intelligent Operations Platform refines telemetry into AI-ready fuel, and its conversational interface, Mobot, and MCP Server make it accessible wherever teams work. Together, this context layer and the agentic layer form an essential solution for intelligent security operations.
What's new:
- SOC Analyst Agent - Now generally available, the Sumo Logic SOC Analyst Agent automatically investigates SIEM alerts, delivers evidence-backed verdicts, and enables instant human-led investigation through Mobot.
- Mobot - A significantly enhanced version of Sumo Logic's conversational agent now includes multi-turn capabilities that help drive work forward, with new skills for creating and editing playbooks and other content.
- Conversational playbooks - Describe a workflow to Mobot in plain language and have a fully drafted playbook ready in minutes without needing to configure node-by-node.
- Log Analysis Agent - Guides analysts of every skill level from business question to defensible answer, going beyond query writing to guided investigation and content management with Mobot.
- Platform Optimization Agent - Helps users and admins get more value from Sumo Logic through troubleshooting, optimization, and guided configuration via Mobot.
- Sumo Logic MCP Server - Enables Sumo Logic users to connect tools such as Claude Code and GitHub Copilot to Sumo Logic SIEM and Log Analytics through a governed set of API tools. No custom integrations or raw data, just context, wherever teams work.
The Latest
While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...
For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...
As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...
The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...
The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...
Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...
Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...
Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...
In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...
Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...