Operations | Monitoring | ITSM | DevOps | Cloud

Discover the features provided in devpack-for-spring that make Ubuntu the ideal platform for building robust Java applications with Spring.

Subscribe to the channel → / @netdata Now in research preview: Netdata Insights The problem: Incident? You're jumping between dashboards, piecing together timelines. Reporting? You're copy-pasting charts and correlating trends by hand. The data’s there, but turning it into a narrative doesn’t scale. The solution: Netdata Insights. Synthesizes high-fidelity telemetry using the latest LLMs into AI-powered reports with natural-language explanations, visuals, and clear recommendations.

Netdata is a real-time, high-performance and on-premises observability platform designed to monitor metrics and logs with unparalleled efficiency. Netdata requires zero-configuration to get started, and provides alerts, anomaly detection and AI assisted troubleshooting out of the box, providing a powerful and comprehensive infrastructure monitoring experience. Netdata is known for its distributed design. Instead of funneling all data into a few central databases like most traditional monitoring solutions, Netdata processes data at the edge, keeping it close to the source.

Every bank needs to prove it’s compliant. So why is every bank reinventing the same rules? Manual, duplicative compliance across teams Engineers stuck gathering screenshots for audits Custom rules for common risks Missed opportunity to define shared standards Mike joins FINOS Aaron Griswold and explains why Kosli joined FINOS—and how defining shared SDLC controls can help regulated organizations stop wasting time and start delivering software faster and safer. Unpacking the real problems in regulated software delivery.

This panel brings together experts Josh Mesout (Civo), Nobel Chowdary Mandepudi (Arm), Jimil Patel (Intuit), Numa Dhamani (iVerify), and James Gress (Accenture) to discuss the cutting edge of AI and machine learning. They explore when AI might develop its own language beyond human syntax, the evolving landscape of ML frameworks such as MLIR, Mojo, and JAX, and the challenges involved in bridging the gap from AI research to production while optimizing models for deployment.

Forrest and Jake are back with what's new in v5.13.0. Join us to see what's new and get a demo of the latest features!