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AMD Accelerators in CloudBender Nodes

· One min read

proxiML now supports AMD accelerators as a compute backend for CloudBender nodes. Workloads can run on AMD GPUs through ROCm, expanding the hardware options available to CloudBender deployments beyond NVIDIA.

Deploy LLMs in Minutes with the New LLM Job Type

· 3 min read

proxiML now offers a dedicated LLM job type that lets you deploy pre-configured large language models as managed inference endpoints in minutes. Select a model family and size from the platform and get an OpenAI-compatible endpoint with no custom serving commands, Docker images, or manual checkpoint setup required. Currently supported families include Gemma 4, Qwen 3.5, and Qwen 3.6.

Endpoint Authorizers Secure Your Deployed Models

· 2 min read

proxiML now supports Endpoint Authorizers, letting you control access to your deployed ML serving endpoints. Choose between API Key authentication for simple shared-secret access or OIDC (OpenID Connect) for enterprise-grade JWT-based authentication with configurable issuers, audiences, and required claims.

Worker Output Name Customization

· One min read

By default, uploaded artifacts use the <job_name>.zip convention (or <job_name>_<worker_number>.zip for multi-worker jobs), as described in the job form data section. You can now override those default artifact names (including per-worker names where applicable) from the job form and from the SDK via output_options.

Clean Room Version Upgrade Management

· One min read

CloudBender clean room stacks can now be managed through a clearer version upgrade workflow, so you can adopt platform fixes and capabilities in your CloudBender nodes on a controlled schedule.

Azure CloudBender Provider

· One min read

proxiML now supports Azure as a CloudBender provider. You can provision and run proxiML Clean Rooms in your Azure regions alongside existing provider options.