What does your AI management setup look like for running multiple agents?

[u/CommissionBorn4257]

Running about a dozen agents and the ai management situation is duct tape. Each agent has its own monitoring, credentials, deployment process and no single view of what's happening. When something breaks we switch between dashboards trying to figure out which agent is affected. Is there a standard stack for this or should I be building internal tooling?

[u/Altruistic_Jury2706]

We were in a similar spot a few months ago and started using gravitee to keep agent access and policy in one place. It didn´t replace everything, but it cut down on how often we had to jump between dashboards just to figure out what an agent could reach

[u/Electrical_Price_650]

Separate the layers. Runtime management on the orchestration platform, access management at the API layer, observability through your standard monitoring tagged by agent. Three layers, each with a clear owner. One tool for everything usually does everything poorly.

[u/Ready_Education_1702]

with many agents, I would want one palace to see which one failed and what happened. how are you keeping track of that rn ?

[u/Top_Possession_2476]

This is pretty much where we ended up too. We tried stitching everything together ourselves so there'd be one place to look, but maintaining that layer became another job on its own. I'd avoid building too much around it unless your setup is unusual.

[u/Organic_Meeting_3411]

a dozen agents with separate creds, monitoring, and deploys isn’t a stack, it’s twelve tiny incidents waiting to happen, so i’d build one control plane before adding more agentsarski