Operations | Monitoring | ITSM | DevOps | Cloud

Different teams ship on different clouds, each setup grows its own pipeline and runbook, and the fragmentation surfaces later as missed deadlines and extended audits. By then the operating-model debt has been compounding for months.

Upsun acknowledged for its Ability to Execute and Completeness of Vision. Upsun is proud to be recognized for a third year in the 2026 Gartner Magic Quadrant for Cloud-Native Application Platforms alongside other evaluated CNAP platforms. Upsun empowers development teams to ship better software, faster, not just by simplifying infrastructure management, but by rethinking how the entire software development lifecycle works in an era of AI-powered development.

The hidden cost of multicloud lives in operations and governance. Each provider develops its own console, runbooks, and audit posture, and the gaps widen quietly. The bill comes due at the next migration, audit, or incident.

When engineering teams evaluate AI agents, the first questions are usually about capability. Which model performs best? How much faster can it write code? What's the return on investment? Security, if it enters the conversation at all, tends to come later. Patrick Dawkins, Principal Software Engineer at Upsun, thinks that's backward. Over the past year, he's been building the infrastructure that enables AI agents to operate safely within engineering teams.

Migration projects fail in a predictable sequence. The technical work gets scoped. The timeline gets set. The engineering team starts moving workloads. Somewhere in the middle, dependencies surface that weren't in the original assessment, the double-run period extends beyond the budget allocated for it, and the project either stalls or completes at significantly higher cost than planned.