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Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

NOVEMBER 14, 2024

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. Tagging is an effective scaling mechanism for implementing cloud management and governance strategies.

Government

Government Best practices Accountability APIs

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Human oversight : Including human involvement in AI decision-making processes.

Government

Government Management APIs Accountability

Govern generative AI in the enterprise with Amazon SageMaker Canvas

AWS Machine Learning

SEPTEMBER 23, 2024

This is crucial for compliance, security, and governance. In this post, we analyze strategies for governing access to Amazon Bedrock and SageMaker JumpStart models from within SageMaker Canvas using AWS Identity and Access Management (IAM) policies. We provide code examples tailored to common enterprise governance scenarios.

Government

Government Enterprise APIs Accountability

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

Government

Government Engineering Metrics APIs

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

AWS Machine Learning

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker.

Government

Government Metrics Accountability APIs

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

APRIL 11, 2023

These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. One important aspect of this foundation is to organize their AWS environment following a multi-account strategy.

APIs

APIs Accountability Scripts Enterprise

Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

AWS Machine Learning

JULY 31, 2024

The new ApplyGuardrail API enables you to assess any text using your preconfigured guardrails in Amazon Bedrock, without invoking the FMs. In this post, we demonstrate how to use the ApplyGuardrail API with long-context inputs and streaming outputs. For example, you can now use the API with models hosted on Amazon SageMaker.

APIs

APIs Banking Best practices Engineering

Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.

Government

Government Accountability Enterprise Engineering

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

NOVEMBER 7, 2024

We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic.

Enterprise

Enterprise APIs Government Accountability

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

Accountability

Accountability Government Engineering Scripts

How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning

AUGUST 9, 2024

This post provides an overview of a custom solution developed by the AWS Generative AI Innovation Center (GenAIIC) for Deltek , a globally recognized standard for project-based businesses in both government contracting and professional services. Deltek serves over 30,000 clients with industry-specific software and information solutions.

Government

Government Healthcare Construction Engineering

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Government

Government APIs Enterprise Best practices

Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning

FEBRUARY 9, 2024

IT teams are responsible for helping the LOB innovate with speed and agility while providing centralized governance and observability. A software as a service (SaaS) layer for foundation models can provide a simple and consistent interface for end-users, while maintaining centralized governance of access and consumption.

SaaS

SaaS APIs Government Accountability

Improve governance of your machine learning models with Amazon SageMaker

AWS Machine Learning

DECEMBER 1, 2022

Overview of model governance. Model governance is a framework that gives systematic visibility into model development, validation, and usage. Model governance is applicable across the end-to-end ML workflow, starting from identifying the ML use case to ongoing monitoring of a deployed model through alerts, reports, and dashboards.

Government

Government Metrics APIs Engineering

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

NOVEMBER 15, 2024

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. When using the RetrieveAndGenerate API, the output includes the generated response, the source attribution, and the retrieved text chunks.

APIs

APIs Government Best practices Metrics

Use Amazon SageMaker Model Cards sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.

Government

Government Accountability Enterprise Engineering

Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning

NOVEMBER 19, 2024

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon Web Services available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case.

APIs

APIs Management Engineering Enterprise

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

AWS Machine Learning

NOVEMBER 18, 2024

Amazon Bedrock is a fully managed service to build generative AI applications with foundation models (FMs) from leading AI companies such as Anthropic, Mistral AI, Meta, Stability AI, Cohere, AI21 Labs, and Amazon through a single API. A second Lambda function invokes the Amazon Bedrock API. AWS Management Console access. A Python 3.12

APIs

APIs Government Engineering Accountability

Maximizing Efficiency: Integrating Paystub Generators with Accounting Software

CSM Magazine

NOVEMBER 29, 2023

However, by integrating generators with accounting software, businesses can simplify their payroll process, save time, and minimize the risk of discrepancies. Understanding Paystub Generators Before exploring the benefits of integrating generators with accounting software, it’s important to grasp what paystub generators are.

Accountability

Accountability Self service APIs Government

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

AWS Machine Learning

OCTOBER 5, 2022

So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through stolen credentials, phishing, social engineering, and multiple forms of ATO. To put it into perspective: account takeover fraud increased by 90% to an estimated $11.4 Overview of solution.

Accountability

Accountability APIs Metrics Engineering

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

AWS Machine Learning

SEPTEMBER 28, 2023

Regulated and compliance-oriented industries, such as financial services, healthcare and life sciences, and government institutes, face unique challenges in ensuring the secure and responsible consumption of these models. In addition, API Registries enabled centralized governance, control, and discoverability of APIs.

APIs

APIs Government Enterprise Engineering

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

AWS Machine Learning

NOVEMBER 1, 2024

Customers use Druva Data Resiliency Cloud to simplify data protection, streamline data governance, and gain data visibility and insights. Dru on the backend decodes log data, deciphers error codes, and invokes API calls to troubleshoot. This approach allowed us to break the problem down into multiple steps: Identify the API route.

APIs

APIs Scripts Engineering Government

Facebook’s Conversion API – what marketers need to know

Infinity

MARCH 3, 2022

So, in autumn 2021, when Facebook partnered up with Amazon and launched the Conversion API Gateway, it was a very exciting day for Facebook advertisers. When talking Facebook and data, you’re likely to come across two key models – the Conversion API Gateway and the Facebook Pixel, but what’s the difference?

APIs

APIs Marketing Advertising Government

How Aviva built a scalable, secure, and reliable MLOps platform using Amazon SageMaker

AWS Machine Learning

OCTOBER 3, 2024

The proposed baseline architecture can be logically divided into four building blocks which that are sequentially deployed into the provided AWS accounts, as illustrated in the following diagram below. Developers can use the AWS Cloud Development Kit (AWS CDK) to customize the solution to align with the company’s specific account setup.

APIs

APIs Construction Engineering Accountability

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

AWS Machine Learning

NOVEMBER 1, 2023

In the legal system, discovery is the legal process governing the right to obtain and the obligation to produce non-privileged matter relevant to any party’s claims or defenses in litigation. This two pass solution was made possible by using the ContainsPiiEntities and DetectPiiEntities APIs.

APIs

APIs Government Engineering Telecommunications

Build a cross-account MLOps workflow using the Amazon SageMaker model registry

AWS Machine Learning

NOVEMBER 16, 2022

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

Accountability

Accountability Best practices Scripts Engineering

Use Amazon SageMaker Studio with a custom file system in Amazon EFS

AWS Machine Learning

OCTOBER 17, 2024

Improved data governance and security – The shared EFS directory, being centrally managed by the AWS infrastructure admin, can provide improved data governance and security. You should have an AWS CloudTrail log file that logs the SageMaker API CreateUserProfile.

Government

Government Accountability APIs Engineering

Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

MARCH 1, 2024

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API.

APIs

APIs Finance Chatbots Enterprise

Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

MAY 8, 2023

It offers many native capabilities to help manage ML workflows aspects, such as experiment tracking, and model governance via the model registry. This can be a challenge for enterprises in regulated industries that need to keep strong model governance for audit purposes. Now let’s dive deeper into the details.

APIs

APIs Government Accountability Scripts

Improve public speaking skills using a generative AI-based virtual assistant with Amazon Bedrock

AWS Machine Learning

OCTOBER 15, 2024

Organizations across various sectors, including corporations, educational institutions, government entities, and social media personalities, can use this solution to provide automated coaching for their employees, students, and public speaking engagements. The system prompt instructs the Anthropic Claude 3.5

APIs

APIs Construction Engineering Accountability

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

AWS Machine Learning

JULY 30, 2024

The response from API calls are displayed to the end-user. When the IAM Identity Center instance is in the same account where you are deploying the Mediasearch Q Business solution, the finder stack allows you to automatically create the IAM Identity Center customer managed application as part of the stack deployment.

APIs

APIs Accountability Management Entertainment

Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

JULY 2, 2024

With this access control capability, you can safely use retrieval across different user groups or scenarios while complying with company specific data governance policies and regulations. The following GitHub repository provides a guided notebook that you can follow to deploy this example in your own account.

Healthcare

Healthcare APIs Government Accountability

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

AWS Machine Learning

SEPTEMBER 25, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs

APIs Call flow Accountability Technology

Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

MARCH 4, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Feedback

Feedback APIs Engineering Surveys

Implementing Knowledge Bases for Amazon Bedrock in support of GDPR (right to be forgotten) requests

AWS Machine Learning

MAY 31, 2024

Amazon Bedrock is a fully managed service that makes foundational models (FMs) from leading artificial intelligence (AI) companies and Amazon available through an API, so you can choose from a wide range of FMs to find the model that’s best suited for your use case. Model providers can’t access customer data in the deployment account.

Best practices

Best practices APIs Accountability Personalization

Build and train ML models using a data mesh architecture on AWS: Part 1

AWS Machine Learning

JULY 29, 2022

Create accountability on data providers from individual LoBs to share curated data assets that are discoverable, understandable, interoperable, and trustworthy. In this first post, we show the procedures of setting up a data mesh architecture with multiple AWS data producer and consumer accounts.

Government

Government Banking Analytics Accountability

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

JANUARY 5, 2024

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

Management

Management APIs Engineering Government

Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

APRIL 18, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts

Scripts Best practices Engineering Accountability

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

AWS Machine Learning

SEPTEMBER 14, 2023

Governance and policy enforcement – Setting up document categorization rules helps to ensure that documents are classified correctly according to an organization’s policies and governance standards. We will introduce a custom classifier training pipeline that can be deployed in your AWS account with few clicks.

APIs

APIs Government Accountability Engineering

Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

NOVEMBER 19, 2024

Plus, learn how to evolve from data aggregation to data semantics to support data-driven applications while maintaining flexibility and governance. Learn how they created specialized agents for different tasks like account management, repos, pipeline management, and more to help their developers go faster.

APIs

APIs Enterprise Best practices Government

Introducing self-service quota management and higher default service quotas for Amazon Textract

AWS Machine Learning

SEPTEMBER 27, 2022

Amazon Textract now has higher service quotas for several asynchronous and synchronous APIs in multiple major AWS Regions. The following table summarizes the before and after default quota numbers for each of these Regions for the respective synchronous and asynchronous APIs. Increased default service quotas for Amazon Textract.

Self service

Self service APIs Management Accountability

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

OCTOBER 2, 2024

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. None What is the balance for the account 1234?

Best practices

Best practices APIs Metrics Accountability

Announcing the Yammer connector for Amazon Kendra

AWS Machine Learning

MARCH 7, 2023

The solution consists of the following steps: Configure the Yammer app API connector on Azure and get the connection details. An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. Log in to the Azure portal using your global admin user account and choose Next. Choose Add.

APIs

APIs Enterprise Accountability Government

How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants

AWS Machine Learning

NOVEMBER 17, 2022

Yara has built APIs using Amazon API Gateway to expose the sensor data to applications such as ELC. Extendibility – It can deploy to new Regions and accounts. SageMaker Model Monitor APIs offer data and model quality monitoring. ELC is a process optimization use case and is deployed to optimize workload accounts.

APIs

APIs Accountability Metrics Engineering

Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Trending Sources

Govern generative AI in the enterprise with Amazon SageMaker Canvas

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

Use Amazon SageMaker Model Card sharing to improve model governance

Build a multi-tenant generative AI environment for your enterprise on AWS

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

Improve governance of your machine learning models with Amazon SageMaker

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

Use Amazon SageMaker Model Cards sharing to improve model governance

Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

Maximizing Efficiency: Integrating Paystub Generators with Accounting Software

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

Facebook’s Conversion API – what marketers need to know

How Aviva built a scalable, secure, and reliable MLOps platform using Amazon SageMaker

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

Build a cross-account MLOps workflow using the Amazon SageMaker model registry

Use Amazon SageMaker Studio with a custom file system in Amazon EFS

Knowledge Bases for Amazon Bedrock now supports hybrid search

Securing MLflow in AWS: Fine-grained access control with AWS native services

Improve public speaking skills using a generative AI-based virtual assistant with Amazon Bedrock

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

Alida gains deeper understanding of customer feedback with Amazon Bedrock

Implementing Knowledge Bases for Amazon Bedrock in support of GDPR (right to be forgotten) requests

Build and train ML models using a data mesh architecture on AWS: Part 1

Modernizing data science lifecycle management with AWS and Wipro

Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

Your guide to generative AI and ML at AWS re:Invent 2024

Introducing self-service quota management and higher default service quotas for Amazon Textract

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

Announcing the Yammer connector for Amazon Kendra

How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants

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