Operations | Monitoring | ITSM | DevOps | Cloud

Tame the data chaos with Sumo Logic's Data Pipelines

Security and operations teams are collecting more telemetry than ever, and AI is accelerating that curve. IDC projects the world will generate 393.9 zettabytes of data in 2028, up from 149 zettabytes in 2024, with AI and machine learning workloads driving much of that growth. That growth forces a hard trade-off. Ingest everything, and you pay for it. Filter aggressively, and you risk missing the signal that matters.

How to extract structured fields from unstructured logs

If you’ve spent any time digging for insights in logs, you know the shape of the problem. A single log line might contain an IP address, a status code, a response time, and a user ID, but it’s all buried in one long, unstructured string. You know the information is there. Getting it into a field you can filter, group, or chart on is a different matter.

The six pillars of AI-ready telemetry

“AI-ready” is everywhere right now, attached to nearly every product in every category. The catchy label rarely means anything specific, just as additional questions are warranted when vendors claim to be “AI-native”. After fighting through all the marketing jargon, there needs to be a standard, not a slogan. And the definition changes depending on what the data is for. AI-ready for a data warehouse and AI-ready for live operational telemetry are not the same problem.

Mobot levels up: Build incident response playbooks with natural language

We’ve recently shown how Mobot, Sumo Logic’s AI assistant, has evolved from a search assistant into a true thinking partner, introducing natural language to log analysis and monitors. Today, we’re bringing that same conversational reasoning to one of the most powerful parts of the platform: playbooks in Automation Service. Historically, playbook authoring has been a highly manual process that required deep organizational and Sumo Logic platform knowledge.

Only hard work: AI's unexpected burnout risk

On this episode of Masters of Data, we dig into what happens when AI actually delivers on its promise to eliminate busywork, and explore why removing the toil doesn't feel like the win everyone expected. We make the case that repetitive tasks build the intuition, pattern recognition, and muscle memory people need to do the harder work well. Security and engineering leaders rethinking how much triage and busywork to hand off to AI will find plenty to chew on here, especially anyone staring down a task list where every single item feels like the hardest one.

SEO isn't just a marketing KPI anymore. It's a security one.

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.

Microlesson: Using Mobot for Log Analysis

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.