Infrastructure control plane for your coding agents. Agents deploy, you stay in control.

New York 🇺🇸 / Paris 🇫🇷
Joined October 2019
1/ An AI agent with production access should run inside your cloud, next to the workloads it touches. 🔐
1
30
3/ The Qovery control plane only processes deployment metadata: configuration state, resource metrics and deploy events. We don't host your workloads, and on Enterprise you can self-host the control plane itself.
1
8
the demo was the easy part 🫠 Second Opinion #2 is about everything after it: safety, prod access, and the token bill Nov 12, Paris, with @avec_alan , @Qovery_ & @AWS luma.com/4lhbur28
1
2
68
1/ During a Heroku exit, you pay Heroku and AWS at the same time for roughly 4 to 8 weeks. That overlap is what quietly drains the budget. 💸
1
105
3/ Activate is the startup path. MAP is the bigger pool for a migration, and an AWS Partner drives the request for you. Watch NAT Gateway and data transfer, the two charges that surprise people.
2
13
1/ Nov 12, Paris: "Agents in production: beyond the demo". Alan, AWS and Qovery host an evening of talks on running AI agents in production. 🧵
1
1
1
95
3/ Romaric Philogène (CEO, Qovery) on "Who gives the agent access to production?": scope, check and contain, with a live demo of policy-based agent tokens.
1
16
1/ Tip: Debug production without opening a shell inside the live pod. 🐚
1
70
3/ Handy for database migrations, one-off scripts or checking config. Need more room for a heavy data job? Add --memory 2Gi --cpu 1.
1
12
Wonderful
Rebuilt the @Qovery_ onboarding this week, with a few small details like the transition between steps
1
166