2012 Accountability Big data 
AWS Machine Learning
MARCH 13, 2024
Data scientists across business units working on model development using Amazon SageMaker are granted access to relevant data, which can lead to the requirement of managing prefix -level access controls. Amazon S3 Access Points simplify managing and securing data access at scale for applications using shared datasets on Amazon S3.
AWS Machine Learning
SEPTEMBER 3, 2024
Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise. elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*"
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning
OCTOBER 30, 2023
The Amazon Bedrock VPC endpoint powered by AWS PrivateLink allows you to establish a private connection between the VPC in your account and the Amazon Bedrock service account. Use the following template to create the infrastructure stack Bedrock-GenAI-Stack in your AWS account. You’re redirected to the IAM console.
AWS Machine Learning
NOVEMBER 9, 2023
Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. Approve the model in SageMaker Model Registry in the central model registry account. Create a pull request to merge the code into the main branch of the GitHub repository.
AWS Machine Learning
AUGUST 22, 2023
However, sometimes due to security and privacy regulations within or across organizations, the data is decentralized across multiple accounts or in different Regions and it can’t be centralized into one account or across Regions. Each account or Region has its own training instances.
AWS Machine Learning
MAY 8, 2023
How to use MLflow as a centralized repository in a multi-account setup. Prerequisites Before deploying the solution, make sure you have access to an AWS account with admin permissions. Multi-account considerations Data science workflows have to pass multiple stages as they progress from experimentation to production.
AWS Machine Learning
AUGUST 31, 2023
As you scale your models, projects, and teams, as a best practice we recommend that you adopt a multi-account strategy that provides project and team isolation for ML model development and deployment. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.
Expert insights. Personalized for you.
113 
Let's personalize your content