Operations | Monitoring | ITSM | DevOps | Cloud

A new milestone is achieved with the release of dbForge 2025.2! This time, it brings you enhancements in dbForge AI Assistant, long-awaited user interface improvements, and further significant advancements across dbForge tools for SQL Server, MySQL/MariaDB, Oracle, PostgreSQL. Interested in learning more? Let’s get started!

We have launched Request Mirror, a little free service to reflect HTTP requests. We've also open-sourced it: you can read the code in the ohdearapp/request-mirror.ohdear.app repo on GitHub. In this blog post I'd like to explain why we built it and how you can use it.

One kind of data in most relational databases is what we call static data. This is also referred to as lookup data, code data, domain data or even list data. Whatever you like to call it, it’s usually smaller data sets consisting of data that never changes, or changes very slowly. One example might be Canadian postal codes. Another example, and one I’m going to use, is the amateur radio band definitions within a given country.

For nearly 20 years, SQL Prompt has been a trusted companion for database professionals, helping them write cleaner code, reduce errors, and save time. From its earliest days, the focus has been on productivity while removing the repetitive, mundane tasks that slow people down. It’s been about building the reliability and performance that developers and DBAs depend on every day and that story doesn’t stop here.

If you’re in IT operations, you’ve likely faced the disconnect firsthand: your dashboards say everything’s green, but your business stakeholders are asking why the website is slow, the customer portal is timing out, or a regional service is underperforming. Your team is usually on top of issues, such as monitoring infrastructure health, resolving alerts, and keeping systems online. But the business isn’t looking at device uptime.

Experience seamless control, clarity, and cost optimization with the CloudSpend app on iOS 26. This update integrates Apple’s new Liquid Glass design and secure, on-device AI summaries to deliver instant insights into your cloud spending, empowering you to act decisively from anywhere.

Modern engineering teams face a persistent challenge: knowing when something goes wrong before their customers do. With microservices architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives.

If you’ve been following my public journey with LLMs this year, it probably won’t surprise you to learn that this blog post is an announcement about the general availability of Honeycomb’s hosted MCP server. I want to share a few updates about what’s new in the GA release, discuss some interesting learnings from building it, and share examples of how we’re using MCP internally. First: if you're still in the dark about MCP and AI agents, go read the earlier blogs I linked.

Every day, IT teams are flooded with alerts—thousands of messages about performance issues, service outages, or suspicious activity. With so many notifications, it’s easy to get overwhelmed, miss critical problems, or waste time chasing false alarms. Correlating related alerts into groups can help reduce the noise and make sense of everything, but setting up those correlations takes time, experience, and a lot of both system and historic knowledge.

TL;DR: Error monitoring and crash reporting for all major gaming consoles is now generally available (plus, the v1.1 of our Unreal Engine SDK). Already convinced? Jump to the ‘What’s In The Release?’ section. Over a decade ago, a customer hacked Sentry into their PlayStation 3 games. Fast forward to today, Sentry now supports thousands of game developers across web, mobile, and desktop. The missing piece? Consoles. Developers asked for it. We built it.