It is increasingly common to use multiple cloud services as building blocks to assemble a modern event-driven application. Using purpose-built services to accomplish a particular task ensures developers get the best capabilities for their use case. However, communication between services can be difficult if they use different technologies to communicate, meaning that you need to […]

I am excited to announce the availability of a distributed map for AWS Step Functions. This flow extends support for orchestrating large-scale parallel workloads such as the on-demand processing of semi-structured data. Step Function’s map state executes the same processing steps for multiple entries in a dataset. The existing map state is limited to 40 […]

With several global crises occupying our daily lives, it’s important to see where we can leverage technology to solve these hard human problems. Today, we have more access to data from wearables, medical devices, environmental sensors, video capture, and other connected devices than we have had at any point in the past. When combined with […]

More CISOs will have to deliver revenue growth to protect their budgets and grow their careers in 2023 and beyond, and a core part of that will be getting multicloud security right. It’s the most common infrastructure strategy for rejuvenating legacy IT systems and clouds while driving new revenue models. As a result, multicloud is the most popular cloud […]

AWS Marketplace Vendor Insights is a new capability of AWS Marketplace. It simplifies third-party software risk assessments when procuring solutions from the AWS Marketplace. It helps you to ensure that the third-party software continuously meets your industry standards by compiling security and compliance information, such as data privacy and residency, application security, and access control, […]

As you move your machine learning (ML) workloads into production, you need to continuously monitor your deployed models and iterate when you observe a deviation in your model performance. When you build a new model, you typically start validating the model offline using historical inference request data. But this data sometimes fails to account for […]

In 2019, we introduced Amazon SageMaker Studio, the first fully integrated development environment (IDE) for data science and machine learning (ML). SageMaker Studio gives you access to fully managed Jupyter Notebooks that integrate with purpose-built tools to perform all ML steps, from preparing data to training and debugging models, tracking experiments, deploying and monitoring models, […]

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. SageMaker JumpStart gives you access to built-in algorithms with pre-trained models from popular model hubs, pre-trained foundation models to help you perform tasks such as article summarization and image generation, and end-to-end solutions to solve common use cases. […]

AWS Machine Learning University is now providing a free educator enablement program. This program provides faculty at community colleges, minority-serving institutions (MSIs), and historically Black colleges and universities (HBCUs) with the skills and resources to teach data analytics, artificial intelligence (AI), and machine learning (ML) concepts to build a diverse pipeline for in-demand jobs of […]

When we talk with customers, we hear that they want to be able to harness insights from data in order to make timely, impactful, and actionable business decisions. A common pattern with data-driven organizations is that they have many different data sources they need to ingest into their analytics systems. This requires them to build […]