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User Profiles

End-User Self-Service for Automated User Profile Creation in SageMaker Domains

As organizations expand their use of Amazon SageMaker to empower data scientists and machine learning (ML) engineers, managing access to development environments becomes a critical concern. In the last blog, we discussed how SageMaker Domains can provide isolated, secure, and fully-featured environments for users.

However, manually creating user profiles for every user quickly becomes a bottleneck—especially in large or fast-growing organizations. Asking users to submit an IT ticket and wait for days before it can be fulfilled is unacceptable in today's fast paced environment.

In this blog, we will describe how organizations use Rafay's PaaS to provide their users with a self-service experience to onboard themselves into SageMaker Domains without waiting on IT or platform teams. This not only improves efficiency and user experience but also ensures consistency and compliance across the organization.

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Why Enterprises Should Use Domains for SageMaker AI

As organizations continue to invest in artificial intelligence (AI) and machine learning (ML) to drive digital transformation, the demand for streamlined, secure, and scalable development environments has never been greater.

Many organizations that are standardized on Amazon AWS may use Amazon SageMaker AI to build, train, and deploy machine learning models at scale with minimal operational overhead. SageMaker AI provides a fully managed environment that streamlines the entire ML lifecycle, enabling faster innovation, stronger governance, and cost-effective AI development.

In this introductory blog, we will describe one of the most critical capabilities of SageMaker AI called Domains. In the next blog, we will describe how organizations can scale their AI/ML teams by providing their data scientists and ML engineers with a self service experience for access to SageMaker Domains.

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