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HI Yaniv,

Different ways to solve this. One question would be: Did you try to use Pulumi Deployments? It's a new service from Pulumi allows to use the RemotWorkspace in the automation api. This means the deployment will be done serverless from us.
<https://www.pulumi.com/docs/intro/pulumi-service/deployments/>

we are using automation API and have a self service  no code platform called Q-Cloud. ya the api uses a bit of memory for the pulumi container we have BUT this is only during execution as you mention. we have optimized a few things and works fine for 25 users / occasionally slows down during 5 or so stack updates concurrently. we thing the mem usage may be due to our proprietary layer on top of pulumi api to store each stack no code canvas state locally in a file system. Our stack is nodejs for api but use TS for the program...   is your deployment containerized ?

Hi <@U033KKRC6HY>
Never used this feature. I’ll read about it and try it. Thanks! There are also another solutions for this issue?
<@U02GSRCGS0J> The environment is containerized. Running inside docker (pulumi/pulumi-python)