AWS next-generation-sagemaker documentation change
Summary
Complete restructuring of the Amazon SageMaker documentation page, including updated overview, simplified navigation, reorganization of capabilities into new sections (Connect and Transform Data, Core Capabilities, AI/ML, Catalog/Governance), and removal of detailed use cases.
Security assessment
The changes are organizational and focus on improving user navigation and content structure. No security vulnerabilities, incidents, or weaknesses are mentioned. References to governance/access controls (e.g., 'Data Governance', 'fine-grained access') describe existing features rather than new security documentation.
Diff
diff --git a/next-generation-sagemaker/index.md b/next-generation-sagemaker/index.md index e9ca09032..7ef84e876 100644 --- a//next-generation-sagemaker/index.md +++ b//next-generation-sagemaker/index.md @@ -3 +3 @@ -# Get Started with Amazon SageMaker +# Amazon SageMaker Documentation @@ -5 +5 @@ -The next generation of Amazon SageMaker is the center for all your data, analytics, and AI. +Amazon SageMaker is the center for all your data, analytics, and AI. @@ -7 +7 @@ The next generation of Amazon SageMaker is the center for all your data, analyti -## Overview of Amazon SageMaker +## Overview @@ -9,19 +9 @@ The next generation of Amazon SageMaker is the center for all your data, analyti -Bringing together widely adopted AWS artificial intelligence and machine learning (AI/ML) and analytics capabilities, the next generation of [Amazon SageMaker ](https://aws.amazon.com/sagemaker/) delivers an integrated experience for analytics and AI with unified access to all your data. The next generation of Amazon SageMaker consists of two primary components: - - * Amazon SageMaker Unified Studio, which provides an integrated experience to use all your data and tools for analytics and AI - * Amazon SageMaker Catalog, which enables secure discovery and access to approved data and models. - - - -Additionally, SageMaker is built upon an open lakehouse architecture that unifies access to all your data across Amazon Simple Storage Service ([Amazon S3](/AmazonS3/latest/userguide/GetStartedWithS3.html)) data lakes, [Amazon Redshift](/redshift/) data warehouses, and other external sources. - -**Benefits** - - * Build with all your tools for analytics and AI in SageMaker Unified Studio - * Develop and scale AI with a comprehensive set of AI capabilities - * Reduce data silos and unify all your data with SageMaker lakehouse architecture - * Meet your enterprise security needs with end-to-end data and AI governance - - - -To get started, go to the [Amazon SageMaker user guide](/next-generation-sagemaker/latest/userguide/what-is-sagemaker.html). +Amazon SageMaker brings data engineering, analytics, machine learning, and AI into a single platform. Built on open formats with your choice of compute engine, it lets you query, transform, train, deploy, and govern in one place. Shared context and consistent governance span the full workflow, so the platform works for data and AI practitioners, external IDEs, and agents. To get started, go to the [Amazon SageMaker user guide](/sagemaker-unified-studio/latest/userguide/what-is-sagemaker-unified-studio.html). @@ -31,121 +13 @@ To get started, go to the [Amazon SageMaker user guide](/next-generation-sagemak -## Capabilities of Amazon SageMaker Unified Studio - -Amazon SageMaker Unified Studio is a single data and AI development environment where you can find and access all of the data in your organization and act on it using the best tools across any use case. - - * Streamline access to familiar tools and functionality from purpose-built AWS analytics and artificial intelligence and machine learning (AI/ML) services like Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. - * Develop ML and foundation models (FMs) using the fully managed infrastructure, tools, and workflows of SageMaker AI. - * Efficiently build generative AI applications in a trusted and secure environment using Amazon Bedrock. - * Analyze, prepare, and integrate data for analytics and AI using open source frameworks on Amazon Athena, Amazon EMR, and AWS Glue - * Streamline your data journey with Amazon Q Developer to author code, generate SQL, integrate data, and troubleshoot. - - - -## Key concepts - -To learn more about Amazon SageMaker Unified Studio, Catalog, lakehouse architecture, and SageMaker AI, explore the following guides: - -### SageMaker Unified Studio - -Build with all your data and tools for analytics and AI in a single development environment with SageMaker Unified Studio - -[Learn more](/sagemaker-unified-studio/latest/userguide/what-is-sagemaker-unified-studio.html) - -### SageMaker lakehouse architecture - -Unify data access across Amazon S3 data lakes, Amazon Redshift data warehouses, and third-party and federated data sources with SageMaker lakehouse architecture - -[Learn more](/sagemaker-lakehouse-architecture/latest/userguide/what-is-smlh.html) - -### SageMaker Catalog - -Securely discover, govern, and collaborate on data and AI with SageMaker Catalog (built on Amazon DataZone) - -[Learn more](/datazone/latest/userguide/what-is-datazone.html) - -### Amazon SageMaker AI - -Build, train, and deploy ML models—including FMs—for any use case with fully managed infrastructure, tools, and workflows. - -[Learn more](/sagemaker/latest/dg/whatis.html) - -## Use cases - -Learn more about how to apply your use case to SageMaker Unified Studio and which underlying services are being used. - -Import and query data - -You can use the SageMaker Unified Studio query editor to perform analysis using SQL. It provides a place to write and run queries, view results, and share your work with your team. You can also import and query data sets in your existing Glue Data Catalog resources. - -[  Amazon Athena](/athena) [  AWS Glue](/glue) - -Scale data infrastructure and integrate access controls - -SageMaker lakehouse architecture provides a unified environment for accessing, discovering, preparing, and analyzing data from various sources for machine learning (ML) and analytics workloads. Use lakehouse access controls to: - - * Streamlining the creation of connections to diverse data sources through a unified interface - * Centralizing access control management through [AWS Lake Formation ](https://aws.amazon.com/lake-formation/) - * Enabling in-place querying through federated catalogs without data movement - * Providing fine-grained permissions at the catalog, database, table, and column levels - * Exploring data for ad hoc reporting and proof of concept before setting up new zero-ETL pipelines - - - -[  AWS Lake Formation ](/lake-formation) - -Fine-tune foundation models - -Amazon SageMaker Unified Studio provides a large collection of state-of-the-art foundation models. These models support use cases such as content writing, code generation, question answering, copywriting, summarization, classification, information retrieval, and more. You can find, customize, and deploy these foundation models in the JumpStart model catalog. You can use the foundation models to build your own generative AI solutions for a wide range of applications. - -[  Amazon SageMaker AI](/sagemaker) - -Create a chat agent application - -Amazon Bedrock in SageMaker Unified Studio offers multiple playgrounds that allow you to easily access and experiment with Amazon Bedrock models. With the [chat](/sagemaker-unified-studio/latest/userguide/bedrock-explore-chat-playground.html) playground, you can chat with a model through text and image prompts. With the [image and video](/sagemaker-unified-studio/latest/userguide/explore-image-playground.html) playground, you can use a compatible model to generate and edit images and videos. In addition to the playgrounds, you can also use Amazon Bedrock in SageMaker Unified Studio to create [chat agent apps](/sagemaker-unified-studio/latest/userguide/create-chat-app.html) and [flows apps](/sagemaker-unified-studio/latest/userguide/create-flows-app.html). - -[  Amazon Bedrock ](/bedrock) - -## Start building - -Now that we've covered what Amazon SageMaker is and its benefits, you can get started by selecting one of the following workflows: - -Setup - -**[Setting up Amazon SageMaker](/next-generation-sagemaker/latest/userguide/setting-up.html) ** - -Learn how to set up Amazon SageMaker. - -Upload and query data - -**[Get started with uploading and querying data](/next-generation-sagemaker/latest/userguide/upload-query.html) ** - -Learn how to write and run queries, view results, and share your work with your team. - -Bring existing resources - -**[Get started with importing and querying data sets for AWS Glue Data Catalog and Amazon S3 in Amazon SageMaker Unified Studio](/next-generation-sagemaker/latest/userguide/getting-started-sagemaker-gdc-s3.html) ** - -Learn how to access and leverage your existing AWS Glue Data Catalog resources within Amazon SageMaker Unified Studio, allowing you to query and analyze your data without moving or duplicating it. - -Get started with compute - -**[Get started using EMR Serverless in Amazon SageMaker Unified Studio](/next-generation-sagemaker/latest/userguide/emr-serverless.html) ** - -Use a single EMR Serverless application on multiple clusters and run clusters on demand as it fits your use case and needs. - -Model Development - -**[Get started fine-tuning foundation models](/next-generation-sagemaker/latest/userguide/getting-started-sagemaker-training.html) ** - -Learn how to fine-tune foundation models, Amazon SageMaker Unified Studio provides an example training dataset for each model that's eligible for training. - -Get started with lakehouse architecture - -**[Get started with lakehouse access controls for Athena federated queries in Amazon SageMaker Unified Studio](/next-generation-sagemaker/latest/userguide/lakehouse-athena-federated-queries.html) ** - -This guide shows you how to use SageMaker lakehouse architecture with integrated access controls for Athena federated queries. - -## Resources - - - -### Learn +## Get started @@ -153 +15 @@ This guide shows you how to use SageMaker lakehouse architecture with integrated -Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/claude/), [Cohere Command Embed ](https://aws.amazon.com/bedrock/cohere-command-embed/), [AI21 Labs Jurassic ](https://aws.amazon.com/bedrock/jurassic/),[Meta Llama ](https://aws.amazon.com/bedrock/llama/), [Mistral AI ](https://aws.amazon.com/bedrock/mistral/), [Stable Diffusion XL ](https://aws.amazon.com/bedrock/stable-diffusion/), [Amazon Nova ](https://aws.amazon.com/ai/generative-ai/nova/),[Amazon Titan ](https://aws.amazon.com/bedrock/titan/)) +### [Access SageMaker Sign in and navigate the platform. ](/sagemaker-unified-studio/latest/userguide/getting-started-access-the-portal.html) ### [Set up your domain Set up an IAM domain and configure your first project. ](/sagemaker-unified-studio/latest/userguide/gs-admin-setup.html) ### [Tutorials Run your first SQL query, build a data pipeline, train a model. ](/sagemaker-unified-studio/latest/userguide/getting-started.html) @@ -155 +17 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[PartyRock, an Amazon Bedrock Playground ](https://partyrock.aws/) for hands-on prompt engineering experimentation +## Connect and Transform Data @@ -157 +19 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl - +### [Data Sources and Connections Connect to S3, Redshift, Glue catalogs, and federated sources. ](/sagemaker-unified-studio/latest/userguide/data.html) ### [Data Integration and Processing Run processing jobs and monitor data quality. ](/sagemaker-unified-studio/latest/userguide/sagemaker-unified-studio-jobs.html) @@ -159 +21 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -### Build +## Core Capabilities @@ -161 +23 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Build private and secure enterprise generative AI apps with Amazon Q Business and IAM Identity Center ](https://aws.amazon.com/blogs/machine-learning/build-private-and-secure-enterprise-generative-ai-apps-with-amazon-q-business-and-aws-iam-identity-center/) +### [Notebooks Create, run, and schedule notebooks with Spark or Python. ](/sagemaker-unified-studio/latest/userguide/notebooks.html) ### [Query Editor Write and execute SQL queries. ](/sagemaker-unified-studio/latest/userguide/sql-query.html) ### [Visual ETL Build data pipelines visually with 30+ built-in transforms. ](/sagemaker-unified-studio/latest/userguide/visual-etl.html) ### [SageMaker Data Agent Ask questions in natural language, get code and insights. ](/sagemaker-unified-studio/latest/userguide/sagemaker-data-agent.html) ### [Code Spaces JupyterLab, Code Editor, bring your own image (BYOI). ](/sagemaker-unified-studio/latest/userguide/ide-spaces.html) ### [Local IDE Support Connect VS Code, Kiro, or Cursor to your SageMaker environment. ](/sagemaker-unified-studio/latest/userguide/local-ide-support.html) ### [Workflows Orchestrate serverless and provisioned pipelines. ](/sagemaker-unified-studio/latest/userguide/workflow-orchestration.html) ### [Data Visualization Build and share dashboards with Amazon QuickSight. ](/sagemaker-unified-studio/latest/userguide/quicksight-integration.html) @@ -163 +25 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Fine-tune and deploy language models with Amazon SageMaker AI ](https://aws.amazon.com/blogs/machine-learning/fine-tune-and-deploy-language-models-with-amazon-sagemaker-canvas-and-amazon-bedrock/) +## AI and Machine Learning @@ -165 +27 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Build generative AI applications with Amazon Bedrock Studio ](https://aws.amazon.com/blogs/aws/build-generative-ai-applications-with-amazon-bedrock-studio-preview/) +### [Amazon Bedrock in SageMaker Build agents, flow apps, playgrounds, knowledge bases, and guardrails. ](/sagemaker-unified-studio/latest/userguide/bedrock.html) ### [Machine Learning JumpStart models, training, inference endpoints, MLflow, HyperPod. ](/sagemaker-unified-studio/latest/userguide/sagemaker.html) @@ -167 +29 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Build enterprise-grade applications with natural language using AWS App Studio (preview) ](https://aws.amazon.com/blogs/aws/build-custom-business-applications-without-cloud-expertise-using-aws-app-studio-preview/) +## Catalog and Governance @@ -169 +31 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl - +### [SageMaker Catalog Discover, publish, and subscribe to data products and assets. ](/sagemaker-unified-studio/latest/userguide/working-with-business-catalog.html) ### [Data Governance Business glossaries, metadata forms, lineage, fine-grained access. ](/sagemaker-unified-studio/latest/userguide/data-governance.html) ### [Third-Party Integrations Atlan, Collibra, Alation catalog connectors. ](/sagemaker-unified-studio/latest/userguide/third-party-integrations.html) @@ -171 +33 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -### Discover +## Platform @@ -173 +35 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Amazon Q capabilities to reimagine developer experience ](https://aws.amazon.com/blogs/aws/amazon-q-developer-now-generally-available-includes-new-capabilities-to-reimagine-developer-experience/) +### [Admin Guide Manage domains, users, permissions, and platform configuration. ](/sagemaker-unified-studio/latest/adminguide/what-is-sagemaker-unified-studio-admin.html) ### [Projects Create, manage, and collaborate in team projects. ](/sagemaker-unified-studio/latest/userguide/projects.html) ### [Compute Athena, Redshift, EMR (EC2/EKS/Serverless), Glue ETL. ](/sagemaker-unified-studio/latest/userguide/compute.html) ### [CI/CD Deploy across regions and accounts with automated pipelines. ](/sagemaker-unified-studio/latest/userguide/cicd.html) @@ -175 +37 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Chat about your AWS account resources with Amazon Q ](https://aws.amazon.com/blogs/devops/chat-about-your-aws-account-resources-with-amazon-q-developer/) +## Reference @@ -177 +39 @@ Public foundation models ([Anthropic Claude ](https://aws.amazon.com/bedrock/cl -[ Amazon Bedrock model evaluation is now generally available ](https://aws.amazon.com/blogs/aws/amazon-bedrock-model-evaluation-is-now-generally-available/) +### [API Reference Describes all of the API operations for Amazon SageMaker in detail. ](/sagemaker-unified-studio/latest/userguide/execution-apis.html) ### [Terminology and Concepts Learn about key terms, components, and how they relate across the SageMaker platform. ](/sagemaker-unified-studio/latest/userguide/concepts.html) ### [Release Notes Stay up to date with the latest features, improvements, and fixes for Amazon SageMaker. ](/sagemaker-unified-studio/latest/userguide/release-notes.html)