Operations | Monitoring | ITSM | DevOps | Cloud

Ask any engineering leader how AI has changed their team, and you'll get an optimistic answer. Ask them to prove it with a number, and most go quiet. That gap is the story of 2026. Individual engineers are faster than they've ever been. Teams, in a lot of cases, aren't. We talked to our own engineering team, the people who've spent the last year building and shipping Upsun Dispatch and living through exactly this shift, and the same tension came up again and again.

When we launched DNS provider sync with six providers, one name came up in nearly every "what about..." email: Amazon Route 53. That makes sense. Route 53 runs DNS for an enormous share of production infrastructure, and it does not support zone transfers — so until now, monitoring a Route 53 zone meant relying on autodiscovery's educated guesses. Today that gap closes.

How to find, search and retain the SharePoint audit log in Microsoft 365 - the Purview audit search, Search-UnifiedAuditLog PowerShell, retention limits, and where the native audit trail falls short.

When platform providers talk about autoscaling, they usually mean one thing: application autoscaling, adding or removing web instances based on traffic. The pattern is well understood. Define a metric, set a threshold, and let the platform act on it. Most platforms still leave database capacity as a separate, mostly manual problem. Teams either pre-provision for the worst hour of the worst day, upgrade plans on a calendar, or wire together their own scaling logic on Kubernetes or RDS.

For years, the cloud migration business case was framed around one comparison: “Will AWS be cheaper than our data center?” That question still matters, but it is no longer where the value is. The 2017-2024 wave of mass migration is largely complete. Most enterprise workloads are already in the cloud - often in a lift-and-shift state: oversized instances, commercial-OS BYOL, on-prem-shaped network designs, and legacy frameworks that block the next step.

A design partner told us the AI Explorer table needed a way to get data out so it could be saved and shared elsewhere. Now you export the whole view in one click, cost, tokens, cache, and model count all included. The values come through as clean numbers, not text you have to scrub. It’s the same pattern as Explorer, so there’s nothing new to learn.

The first half of 2026 reinforced a key idea about Cloud and SaaS reliability - dependency risk. IncidentHub tracked 30,246 outages across 1,082 providers between January and June 2026. May was the busiest month, with 6,070 incidents. Cloud providers led in the total number of outages (4,723), followed closely by developer tools (4,589).

What’s in this article? Modern enterprise workloads are demanding more from IT infrastructure than ever before. AI platforms, advanced analytics, virtualisation clusters and high-performance computing (HPC) environments all require significantly more compute power than traditional business applications. Many organisations are discovering that their existing on-premise facilities were never designed for these demands.

If you pull cost data from a CloudZero Snowflake Data Share, a request for just a few days of data could be surprisingly slow and expensive. Because of how the data was stored, Snowflake had to read far more than the days you asked for. You paid for that in query time and credits.