New: Deploy ML/AI Confidently with Perimeters, Policies, New UIs, and Authenticated Apps
September 19, 2024
Earlier this week, we released features that help you develop and scale ML/AI more effectively. Today, we focus on three new features related to deploying ML/AI into production:
- The foundations: Use Outerbounds Perimeters and perimeter-specific security policies to secure production deployments and isolate them from development environments.
- Automated workflows: Deploy and operate event-triggered, highly-available production workflows confidently with new UIs.
- Human workflows with Outerbounds Apps: Create and deploy custom dashboards and other services to test and observe results using your favorite tools, like Streamlit, FastAPI, and others – securely authenticated with your SSO provider.
The Foundations
Outerbounds always deploys within your cloud account(s) using the Bring-Your-Own-Cloud (BYOC) deployment model. All data, metadata, and processing remain securely within your cloud accounts, as no data leaves your account, concerns related to compliance and privacy are greatly reduced. This promise applies to state-of-the-art GenAI models as well, thanks to our native integration with NVIDIA NIM. Optionally, you can manage consistent development environments powered by VSCode and notebooks securely inside your cloud accounts too, thanks to Outerbounds Workstations. Outerbounds is fully managed through a control plane, so you can free up engineering resources from maintaining the foundational infrastructure.
New: Perimeters and Perimeter Roles
Often, organizations have existing IAM roles and policies that define permissions for their users and workloads. Instead of asking your security team to redo and audit new policies, we make it easy for them: just Bring Your Own Policies. You can take your existing roles and configure them to be used for workloads and workstations on Outerbounds.
Policies are rarely one-size-fits-all. Outerbounds Perimeters enable you to meet these requirements by creating fully isolated environments within the platform. Should you have a more advanced use case that needs more granular permissioning within a perimeter, even at the level of an individual Metaflow step, you can make it happen with a decorator:
@iam_role(role_arn="arn:aws:iam::123456789012:role/role-name")New: Improved UIs for managing event-triggered production workflows
One of the key features of Outerbounds is the ability to create event-triggered production deployments, which can be used to set up continuous training pipelines, automatically updating batch inference, or to compose sophisticated reactive systems out of modular components. Given the importance of the feature, we improved all views that govern deployment and operation of event-triggered workflows. With a few clicks you can establish a secure connection to a data source, receive real-time events whenever new data is available, and deploy workflows that react to new data automatically.
New: Host Streamlit, Plotly, and other apps on Outerbounds
You can now host Streamlit, Plotly Dash, FastHTML, and any other such apps on Outerbounds, securely behind an SSO-based authentication. Outerbounds Apps support three main use cases: internal dashboards with Streamlit etc., internal UIs that can trigger runs on Outerbounds or support human-in-the-loop workflows such as LLM evaluations, and development of real-time inference endpoints with FastAPI, BentoML, NVIDIA Triton, and others.
Start deploying today
To recap our action-packed launch week, you are now able to develop, scale, and deploy with secure perimeters, event-triggered workflows, and custom apps and dashboards on Outerbounds. It takes only 15 minutes to get started!