Operations | Monitoring | ITSM | DevOps | Cloud

Watch Coroot’s Root Cause Analysis AI pinpoint the exact cause of an incident and suggest fixes in seconds.

In this episode, Daniel Roe, Lead Maintainer of the Nuxt framework, discusses his journey from studying law and theology to leading a major open-source framework. He explains Nuxt's unique governance and how Nuxt manages contributions through volunteer-driven work, LLM-powered issue triage, and creating welcoming spaces for newcomers to open source. This week, our chat touches on a variety of topics including.

From 2015 - 2020, Ribbon Communications and Comporium have partnered on a comprehensive modernization of Comporium’s voice infrastructure, replacing legacy switching systems with a fully IP‑based architecture built on Ribbon’s C20 Call Controller and Session Border Controllers (SBCs). This long‑term collaboration has enabled Comporium to enhance service reliability, streamline operations, and introduce a new generation of customer‑focused voice and unified communications offerings.

Software development is hard, especially when you have to ensure every component works together; it's an integration maze! And running a full stack (like React, Go, and Postgres) on your dev machine often means one thing: running out of memory! The Fix: We'll show you how to use Proxymock to record your components, effectively letting you run the frontend (or any component) completely isolated.

Tired of complex setups and running out of memory just to test one component? Learn how to use Proxymock (a FREE tool) to solve your biggest testing headache: component isolation! This demo shows you how to record and mock interactions across a complex React, Golang, and PostgreSQL stack, allowing you to find bugs before they ever hit production. In This Demo: This strategy lets you easily isolate components, simulate customer behavior, and ensure quality with lightning-fast local testing.

Training an AI foundation model on over a trillion data points sounds impossible without hitting your production systems. Here's how Datadog did it with Apache Iceberg for their time series forecasting model TOTO. The key challenge: extracting massive historical observability data (metrics spanning years) and running incremental preprocessing pipelines without overwhelming production services. Iceberg solved this by providing schema governance, consistency guarantees, and seamless integration with ML tools like Ray and PyTorch.