Model security
Serve models securely with Baseten
Securing users' data and the infrastructure that runs their code and models is paramount. Each user's workload is isolated in a separate Kubernetes namespaces with strict network security policies on inter-namespace communication as well as Pod security policies enforced and monitored by Gatekeeper and Sysdig.
Baseten strongly encourages the best practice of keeping sensitive data away from code by providing multiple ways to store secrets securely.
We developed a network accelerator to speed up model loads from common model artifact stores, including HuggingFace, CloudFront, S3, and OpenAI. Our accelerator employs byte range downloads in the background to maximize the parallelism of downloads. If you prefer to disable this network acceleration for your Baseten workspace, please contact our support team at [email protected].
Last modified 3mo ago