Sure! Here’s the translation into American English:
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Amazon has launched SageMaker Unified Studio, an innovative platform designed to integrate the entire lifecycle of data, analytics, artificial intelligence, and machine learning into a single, regulated environment. This advancement positions organizations in a context where they can unify their workflows in these key areas. However, this transition also presents challenges in terms of scalability, automation, resource isolation, multi-tenancy, and the need to establish effective continuous integration and delivery practices.
As more companies begin to implement this solution, they face the complexity of managing artificial intelligence initiatives that span multiple teams and accounts, which can increase operational burdens. Security and governance become fundamental aspects, making it essential to adopt appropriate mechanisms for isolation and multi-tenancy to protect the data and processes involved.
To address these challenges, strategic architectures and a scalable framework have been proposed that enable organizations to manage multi-tenant environments, automate processes consistently, and introduce governance controls while scaling their artificial intelligence initiatives. This information is part of a series dedicated to exploring artificial intelligence operations using SageMaker Unified Studio.
The suggested architecture promotes a multi-account approach that not only enhances security but also enables effective resource isolation and meets scalability needs. In this framework, various key roles are established, such as data scientists, AI engineers, and administrators, each with specific functions in the AI and machine learning workflow.
SageMaker Unified Studio provides a wide range of shared tools and services, from project management to code version control, as well as data governance and ML pipeline automation. This allows each team to operate in isolation within a secure and controlled environment, fostering innovation without compromising the integrity of the processes.
As organizations integrate their work within this environment, improvements in continuous integration and delivery (CI/CD) practices, along with the use of tools like Amazon EventBridge, are expected to further optimize the development and deployment of artificial intelligence models. This approach ensures that projects progress efficiently from the creation phase to production implementation.
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Source: MiMub in Spanish