Tag: Irshad Buchh

Today, I am happy to announce that we are working on an AWS Region in Mexico. This AWS Mexico (Central) Region will be the second Region in Latin America joining the AWS South America (São Paulo) Region and will give AWS customers the ability to run workloads and store data that must remain in-country. Mexico in the works The Region will include three Availability Zones, each one physically independent of the others in the Region yet far enough apart to minimize the risk that an event in one Availability Zone will have impact on business continuity. The Availability Zones will be connected to each other by high-bandwidth, low-latency network connections over dedicated, fully redundant fiber. With this announcement, AWS now…

Over the past week, our service teams have continued to innovate on your behalf, and a lot has happened in the Amazon Web Services (AWS) universe that I want to tell you about. I’ll also share about all the AWS Community events and initiatives that are happening around the world. Let’s dive in! Last week’s launches Here are some launches that got my attention during the previous week. AWS Control Tower introduces APIs to register organizational units – With these new APIs, you can extend governance to organizational units (OUs) using APIs and automate your OU provisioning workflow. The APIs can also be used for OUs that are already under AWS Control Tower governance to re-register OUs after landing zone…

Today we’re previewing a new chat experience for AWS Glue that will let you use natural language to author and troubleshoot data integration jobs. Amazon Q data integration in AWS Glue will reduce the time and effort you need to learn, build, and run data integration jobs using AWS Glue data integration engines. You can author jobs, troubleshoot issues, and get instant answers to questions about AWS Glue and anything related to data integration. The chat experience is powered by Amazon Bedrock. You can describe your data integration workload and Amazon Q will generate a complete ETL script. You can troubleshoot your jobs by asking Amazon Q to explain errors and propose solutions. Amazon Q provides detailed guidance throughout the…

Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, you can now explore and transform your data to build highly accurate ML models. This new capability is powered by Amazon Bedrock. Data is the foundation for effective machine learning, and transforming raw data to make it suitable for ML model building and generating predictions is key to better insights. Analyzing, transforming, and preparing data to build ML models is often the most time-consuming part…