Operations | Monitoring | ITSM | DevOps | Cloud

This post covers ~80% of VictoriaLogs concepts and features people ask about most often. For deeper details and full references, see the official VictoriaLogs documentation. Part of a series.

SQL Prompt’s January release brings support for Microsoft Fabric and an exciting new preview feature.

As the new year begins, development teams are looking to build momentum, set clear goals, and establish reliable, scalable processes that will help them deliver value consistently throughout 2026. That’s why many teams are turning to SQL Toolbelt Essentials: a powerful, easy-to-adopt toolkit that helps teams speed up database development, reduce risk, and standardize workflows.

First, I’d like to say how happy and lucky I feel to be working at Redgate on Flyway. I’m one of two Senior Product Managers in Flyway and we’ve been looking for a third to join us. We work alongside the Flyway Group Leadership Team (Group Product Manager, Architect, Lead Designer, and Development Manager) and four amazing engineering teams with embedded designers. We also work with the Product Support, Marketing, Sales, and Customer Success teams.

Teams work on databases across multiple environments (e.g., Development, Test, QA/UAT, Production) and differences can happen in these databases over time. A hot fix applied directly to Production or a quick change applied in Test while troubleshooting are examples of how the schema can diverge from what’s expected. These differences are known as drift and can cause problems with deployments making them unpredictable and harder to troubleshoot.

2025 has been quite a year! As we enter into 2026, we want to share all the great features that VictoriaMetrics Cloud has brought in the last quarter. Remember that this Quarterly Live Update is available in video format as well here: Let’s get to it!

Redis is a widely used in-memory data store, commonly deployed as a cache, session store, message broker, or fast key-value database. Because Redis often sits on the critical path of an application, having visibility into its behavior (memory usage, client connections, command throughput, cache efficiency) is essential for troubleshooting and performance tuning.

AI-powered coding assistants have transformed how developers write software. Tools like Claude Code, OpenAI Codex, Gemini CLI, Qwen Code, and OpenCode have introduced what many call “vibe coding” — a new paradigm where users describe their intent and AI agents handle the implementation details. But as these tools become integral to development workflows, a critical question emerges: how do we understand what’s happening under the hood?