Operations | Monitoring | ITSM | DevOps | Cloud

Watch this AI agent find and fix performance bottlenecks

Anyone can claim an AI agent will fix your performance problems. This demo shows exactly what it looks at and what it hands back. In this Product Highlights conversation, Sylvain Guittard, Senior Director of Product at Upsun who leads the team behind the Upsun console and CLI, runs the Upsun Cloud Performance Agent live on a demo project. His take: "You have a patch that is already available, and a recommendation, so you can see if it fits or not to your context." We get into.

This AI agent finds your app's bottlenecks and suggests the fix

Most teams collect the profiles and traffic data that explain a slowdown. Almost nobody has time to read it before users notice. In this Product Highlights conversation, Sylvain Guittard, Senior Director of Product at Upsun who leads the team behind the Upsun console and CLI, breaks down the Upsun Cloud Performance Agent, the first background agent running on Upsun Cloud. His take: "We monitor everything, we feed that into an agent, and the agent will be capable of finding what the bottlenecks are in your application. And on top of it, it gives you a patch, or a way to fix it." We get into.

Your AI stack will change again. Stop rebuilding it.

The model your team relies on today is unlikely to be the one you're relying on a year from now. If your team's process for shipping AI-assisted code is built around a specific model, coding assistant, or a vendor's take on an autonomous agent, you are not building infrastructure. You are building something you will tear out and rebuild the next time the leaderboard shifts.

Before your AI bottleneck gets worse: what to put in place now

Your engineers have agents running. Not one agent, but several, spread across the team. Some run in a terminal on a laptop, some are wired into your CI jobs, and some live inside whatever coding tool each person prefers. Each one got set up separately, by whoever needed it, in whatever way worked that week. That is the state most teams are in right now. Code stopped being the slow part a while ago.

You made coding faster. Guess where the bottleneck went next.

Somewhere in the last year, your team's code output went up. Pull requests are opened faster. The backlog of small fixes and routine changes started clearing quicker than it used to. If delivery still feels roughly as slow as it did before, that's what happens when you speed up one part of a process without touching anything downstream of it.

Your AI coding gains are stuck before the code is even written

At some point this year, you likely approved a request to expand AI coding tool access across the team. The pitch was straightforward: engineers write code faster, the team ships more, the investment pays for itself. The first half happened. Engineers are writing code faster. If you're now being asked whether the investment paid off, and you're finding the honest answer is more complicated than a yes, you are not alone, and you have not been sold something broken.

How Upsun Dispatch runs workflows, from issue to reviewed code

Upsun Dispatch is generally available to the public as of today. Our previous article explains what it is and why we built it. This round, we take you into the details of how it works, the primitives it consists of, and the functionality available right away. You'll also get a glimpse of our roadmap at the end of the article.

Introducing Upsun Dispatch - AI helped your engineers ship more code, now you can ship more product

AI models got good enough that teams want to let them loose on the backlog. Then somebody asks who approved that change, what is waiting on a decision, and what the agent actually cost. Upsun Dispatch gives your team and your agents a shared place to work together. It runs on the repository you already have, connects to the tools your team already uses, and keeps a person on the decisions that matter.