AI for Network Leaders by Selector - Round Table discussion
AI Leaders in Networking Roundtable | Greg Freeman, Du’An Lightfoot, Jeremy Shulman, William Collins, Scott Robohn & John Capobianco (Moderator)
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
Qovery the new standard for DevOps automation
Qovery is a DevOps automation platform that lets developers deploy and scale applications on their cloud by simplifying and automating infrastructure so tech teams can focus on what matters most: building great products. Designed for modern and innovative companies, Qovery delivers the ease of a PaaS with the flexibility and control of your own cloud. Qovery takes the toil out of DevOps, freeing engineers to focus on what matters, while providing a refined experience and full control at every stage of scaling.
Announcing Scout's MCP Server for AI-Native Monitoring!
We’re excited to introduce the Scout Monitoring MCP Server — a new way to bring AI-native monitoring directly into your coding assistant. Instead of flipping between dashboards and logs, the MCP (Model Context Protocol) server surfaces performance data, errors, and slow endpoints right where you work. Ask plain-language questions like “show me the latest five errors” and get answers grounded in live telemetry. You can even let your coding assistant propose and push fixes!
Our rebrand: setting a new standard for DevOps automation
Qovery unveils its new brand identity, reinforcing its mission to make DevOps simple, intuitive, and powerful. Discover how our DevOps automation platform simplifies infrastructure, scaling, security, and innovation across the full DevOps lifecycle.
How to Get Internal Support for Your Project Fast #shorts #sales
For more information please visit our site at www.invgate.com
You have to talk about reliability failures to fix them
Gremlin Founder & CEO Kolton Andrus talks about how you can’t improve your reliability unless you’re willing to talk about it.
Debugging Microservices in Production with Distributed Tracing
Your production checkout flow just started returning 500 errors. Six microservices handle checkout. Logs show errors in three of them. Which service broke? Which error happened first? What caused the cascade? Traditional debugging doesn't work. You can't attach a debugger to production. Searching logs across six services gives thousands of lines with no obvious connection. By the time you correlate timestamps and trace IDs manually, customers have abandoned their carts.
Cloud Microservices Monitoring on AWS and Azure with OpenTelemetry
Your checkout flow starts in an AWS Lambda function, calls a payment service running on EKS, then triggers notifications through Azure Functions. Three different compute platforms, two cloud providers, one distributed trace that you can't see. Cloud providers want you to use their native monitoring tools. AWS pushes X-Ray and CloudWatch. Azure promotes Application Insights and Azure Monitor. These tools work well within their ecosystems but lock you into vendor-specific implementations.
Seer can fix Web Vitals
Join Serge and Ben to learn more about Web Vitals, lab data vs real user metrics and how Seer can help fix your Web Vitals.
Resolve CEO breaks down Accelerating Zero Ticket IT with Agentic AI and Automation #itautomation
“How do we build a truly agentless helpdesk?” Resolve CEO Sean Heuer breaks it down. RITA + Espressive = 30–40% fewer tickets AI agents that actually resolve The future of Zero Ticket IT.