Operations | Monitoring | ITSM | DevOps | Cloud

Want to see how dbForge AI Assistant works? This quick video shows how the Assistant generates SQL, explains it, fixes errors, optimizes queries, and converts natural language to SQL. No manual coding needed Works inside multiple dbForge products.

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.

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.

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

Meet dbForge AI Assistant — your AI-powered copilot for SQL coding, query optimization, explanations, troubleshooting, and conversion of natural language to SQL code. This overview shows how the Assistant works inside dbForge products and how it helps developers, DBAs, analysts, and teams increase productivity. Key features: Context-aware SQL generation Conversion of natural language to SQL Query optimization SQL explanations Troubleshooting and error insights AI chat for SQL-related questions Optional web search.