Operations | Monitoring | ITSM | DevOps | Cloud

What SharePoint's 'Sorry, something went wrong' means, what to do with the correlation ID, and Microsoft's documented fixes for search and site template errors.

Let’s stop debating it and just lean in: you can have both. Sentry is now shipping a unified experience that bridges the gap, and we think its the right solution right now for agents with access to sandboxes. You’re probably immediately asking why? Probably because you think CLI is superior (its not btw).

We use GitHub workflows to make sure our products match our expected quality standards, and by using Sentry Tracing we improved CI run time by 71%. Here’s how you can too.

Gorman is a Database and AI Advocate and Engineer at Redgate She's the previous director of Data and AI at Silk, and the Oracle SME in Azure at Microsoft. With a robust background in cloud technology and a passion for promoting its merits and potential, I am thrilled to spearhead conversations and actions that help shape the future of this industry. Kellyn has authored numerous technical books, white papers and solution repositories in GitHub on database, AI and engineering topics.

Five new MCP tools expand access to Skylar One operational data, giving AI agents greater flexibility to retrieve information, gain context, and support AI-assisted IT workflows.

If your Laravel app authenticates API requests with a token, this one is worth a look today. Laravel just backported a TokenGuard fix to the 10.x line for CVE-2026-114509, and it closes an authentication bypass that needs nothing more than a cleverly shaped query string. Scout Monitoring instruments Laravel out of the box, so if you run an older app that’s still on 10.x, this is exactly the kind of change worth confirming lands cleanly in production. Watch it with Scout for free while you upgrade.

LogicMonitor MCP for Edwin AI makes monitoring data and AI investigation results available to approved AI clients, helping engineers investigate incidents in the tools they already use.

Purpose-built Databases for metrics, logs, and traces, deployed and ingested the same way. Most teams we talk to run three observability backends: one for metrics, one for logs, and one for traces. Each has its own storage model, scaling behavior, and upgrade cycle, and each needs someone on the team who knows how to keep it alive. The bill grows with telemetry volume, and so does the time engineers spend operating the tools instead of using them.