Accountability, APIs, Big data and Strategy

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

AWS Machine Learning

APRIL 11, 2023

One important aspect of this foundation is to organize their AWS environment following a multi-account strategy. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs.

APIs

APIs Accountability Scripts Enterprise

Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

AWS Machine Learning

JUNE 30, 2022

In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.

APIs

APIs Enterprise Big data Accountability

Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

AWS Machine Learning

AUGUST 29, 2022

On August 9, 2022, we announced the general availability of cross-account sharing of Amazon SageMaker Pipelines entities. You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls.

Accountability

Accountability APIs Management Engineering

Webinars

Manual Call Reviews? Theres a Better Way!

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

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs

APIs Government Accountability Scripts

Designing generative AI workloads for resilience

AWS Machine Learning

FEBRUARY 1, 2024

If you’re performing prompt engineering, you should persist your prompts to a reliable data store. That will safeguard your prompts in case of accidental loss or as part of your overall disaster recovery strategy. In the low-latency case, you need to account for the time it takes to generate the embedding vectors.

Best practices

Best practices Engineering SaaS APIs

Use Amazon SageMaker Model Card sharing to improve model governance

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.

Government

Government Accountability Enterprise Engineering

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

JANUARY 26, 2024

This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs. In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices.

Best practices

Best practices Government Engineering Accountability

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account).

Scripts

Scripts APIs Enterprise Accountability

MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

JUNE 24, 2022

After the data scientists have proven that ML can solve the business problem and are familiarized with SageMaker experimentation, training, and deployment of models, the next step is to start productionizing the ML solution. In the same account, Amazon SageMaker Feature Store can be hosted, but we don’t cover it this post.

Enterprise

Enterprise Engineering Accountability APIs

Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

AWS Machine Learning

OCTOBER 27, 2022

We can then call a Forecast API to create a dataset group and import data from the processed S3 bucket. We use the AutoPredictor API, which is also accessible through the Forecast console. When those datasets are ready, we can start to train the predictor. He loves to read and watch sci-fi movies in his spare time.

APIs

APIs Best practices Metrics Government

Use Amazon SageMaker Model Cards sharing to improve model governance

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.

Government

Government Accountability Enterprise Engineering

Intelligent document processing with AWS AI services: Part 2

AWS Machine Learning

AUGUST 15, 2022

More specifically, we need to identify the customer’s savings and checking account numbers in the bank statement. The entities in this file are going to be specific to our business needs (savings and checking account numbers). Document is a wrapper function used to help parse the JSON response from the API. TDocumentSchema().load(response)

Banking

Banking APIs Accountability Analytics

UCcaS,CCaaS,CPaaS – Everything You Need to Know

Hodusoft

AUGUST 30, 2022

Companies, especially the call/contact centers, sales and service teams, and many others are reorganizing and updating their communication strategies to stay competitive. The vendors of CCaaS build different products on APIs (Application Programming Interfaces) that work across several operating systems and Internet browsers.

APIs

APIs Interactive Voice Response Contact Center voip

Localize content into multiple languages using AWS machine learning services

AWS Machine Learning

JULY 19, 2022

We set the OutputFormat to mp3 , which tells Amazon Polly to generate an audio stream for this API call. We again use the start_speech_synthesis_task method but specify OutputFormat to json , which tells Amazon Polly to generate speech marks for this API call. Prerequisites. AWS Cloud Development Kit (AWS CDK). Deploy the solution.

Engineering

Engineering APIs Education Best practices

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

Access to AWS services from Katib and from pipeline pods using the AWS IAM Roles for Service Accounts (IRSA) integration with Kubeflow Profiles. Prior to our adoption of Kubeflow on AWS, our data scientists used a standardized set of tools and a process that allowed flexibility in the technology and workflow used to train a given model.

Engineering

Engineering Healthcare APIs Scripts

10 Best Practices to Develop Your Digital Transformation Framework

aircall

MAY 24, 2021

A digital transformation strategy is critical for small businesses for many reasons. In today’s marketplace, it’s hard to survive without the cloud, big data, APIs, IoT, machine learning, artificial intelligence, automation, and mobile technologies. Software integrations assist on both accounts. Clear strategy.

Best practices

Best practices Call Center Technology Analytics

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

AWS Machine Learning

JULY 21, 2022

Compare and evaluate experiments – The integration of Experiments with Amazon SageMaker Studio makes it easy to produce data visualizations and compare different trials. You can also access the trial data via the Python SDK to generate your own visualization using your preferred plotting libraries. Suggested readings.

Metrics

Metrics Scripts Enterprise Telecommunications

Halo Smart Labs Develops a Smarter Smoke Alarm: IoT at It’s Best

Natalie Petouhof

MAY 25, 2016

What to Consider If You Want to Develop An IoT Product Strategy Constellation’s next-generation customer experience theme focuses on how digital business and IoT not only improve the customer journey, but also transforms business models.

Customer centricity

Customer centricity Technology Customer Experience Big data

Customer Contact Central

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

Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

Webinars

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Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

Webinars

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

Designing generative AI workloads for resilience

Use Amazon SageMaker Model Card sharing to improve model governance

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

MLOps foundation roadmap for enterprises with Amazon SageMaker

Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

Use Amazon SageMaker Model Cards sharing to improve model governance

Intelligent document processing with AWS AI services: Part 2

UCcaS,CCaaS,CPaaS – Everything You Need to Know

Localize content into multiple languages using AWS machine learning services

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

10 Best Practices to Develop Your Digital Transformation Framework

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

Halo Smart Labs Develops a Smarter Smoke Alarm: IoT at It’s Best

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