Apolo AI Ecosystem:
Permission Management

Managing permissions effectively is crucial for safeguarding ML workflows, preventing accidental modifications, and ensuring compliance with regulatory policies. By implementing Role-Based Access Control (RBAC), organizations can assign predefined roles with specific access levels, streamlining security and minimizing risks. Permission management tools help control user access, manage resources efficiently, and maintain accountability in ML operations. A structured approach to access control fosters collaboration while ensuring that critical resources remain protected from unauthorized users.

Role-Based Access Control (RBAC)

Assign permissions based on predefined user roles to enforce security policies.

Custom Role Creation

Allow users to define tailored permission sets to align with specific project requirements.

Audit & Compliance Logging

Track access history and permission changes to ensure compliance with security standards.

Granular Access Management

Define permissions at multiple levels, including datasets, models, and infrastructure components.

Tools & Availability

Tool: Apolo Flow (RBAC)

Tool Description: The Apolo platform supports role-based access control (RBAC). A role is a predefined set of permissions assigned to multiple entities, which can be shared together. Several default roles exist in each cluster, and users may create custom roles to tailor access control based on their specific needs..

Benefits

A robust permission management system enhances security, reduces risk, and ensures that ML infrastructure remains compliant and well-governed.

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Open-source

All tools are open-source.

Unified environment

All tools are installed in the same cluster.

Python

CV and NLP projects on Python.

Resource agnostic

Deploy on-prem, in any public or private cloud, on Apolo or our partners' resources.

Prevents Unauthorized Access

Restricts access to sensitive ML components, reducing the risk of security breaches.

Enhances Security Compliance

Aligns with organizational and regulatory security requirements by enforcing strict access policies.

Facilitates Secure Collaboration

Allows teams to work efficiently while maintaining appropriate levels of access.

Improves Accountability

Provides detailed logs of permission changes and access history for audit and governance purposes.

Apolo AI Ecosystem:
‍Your AI Infrastructure, Fully Managed

Apolo’s AI Ecosystem is an end-to-end platform designed to simplify AI development, deployment, and management. It unifies data preparation, model training, resource management, security, and governance—ensuring seamless AI operations within your data center. With built-in MLOps, multi-tenancy, and integrations with ERP, CRM, and billing systems, Apolo enables enterprises, startups, and research institutions to scale AI effortlessly.