Monthly Archive

Agentic First Security -- Customer Brown Bag - August 20th, 2026

Aug 20, 2026 By Sumo Logic, Inc. In Sumo Logic

Join Jeremy Powell, CISO of Sumo Logic, to learn how AI-powered agents are reshaping modern security operations. Discover the key principles, governance, and best practices for building an agentic security program that enhances analyst productivity, accelerates threat response, and strengthens organizational resilience.

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Think like a criminal: How to land your first security role

Aug 11, 2026 By Sumo Logic, Inc. In Sumo Logic

On this episode of Masters of Data, we tackle breaking into cybersecurity. David shares his journey from welder to AppSec manager, proving that career pivots are tough but doable. We explore entry points like SOC analyst, GRC, and application security roles, noting that penetration testing gigs are fiercely competitive. AI is reshaping the landscape, making technical skills more accessible while amplifying the need for critical thinking. Networking beats degrees. Side projects and hands-on certifications matter more than credentials.

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Navigating cybersecurity in the airline industry: Balancing legacy systems and innovation

Aug 6, 2026 By Tamara Bailey In Sumo Logic

Commercial airlines run some of the world’s most complex technology environments. Every day, they balance decades-old aircraft systems with modern cloud platforms, connected devices, global payment networks, and strict regulatory requirements, all while ensuring flights depart safely and on time. For security teams, that means protecting an enormous attack surface without disrupting operations.

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Dojo AI: Agentic security and cloud operations powered by AI-ready telemetry

Aug 3, 2026 By Margaret Selid In Sumo Logic

You’re collecting more telemetry than ever, but chances are it hasn’t made your job easier. Fragmented data, disconnected tools, and manual investigations mean more noise, slower response times, and higher operational costs. The promise of AI is that it will solve it, but in most cases, you just end up trading noise for expensive hallucinations. Point an LLM at raw, unorganized log storage, and you get an assistant that burns through credits to produce generic, unreliable answers.