7/25/2023, 12:00:00 AM ~ 7/26/2023, 12:00:00 AM (UTC)

Recent Announcements

AWS Cost Management introduces visual Savings Plans recommendations

Starting today, customers can easily understand and validate their Savings Plans recommendations through new visual graphs. The new hourly graphs show On-Demand spend alongside the recommended Savings Plans commitment, providing insight into estimated savings, Savings Plans coverage, and Savings Plans utilization. This helps customers understand how their Savings Plans apply to each hour of spend without having to invest time and resources in building models to analyze their spend.

Amazon Chime SDK provides additional compositing options for live connector and media capture

The Amazon Chime SDK now provides additional options to customize the layout of video sent to streaming services or captured to Amazon Simple Storage Service (S3). Amazon Chime SDK lets developers add real-time audio, video, and screen share to their web and mobile applications. Starting today, developers have more flexibility to tailor the composited layout to suit their use case with either landscape or portrait orientation and stylize video tiles with borders, active speaker highlight, configurable aspect ratio and corner radius.

CloudWatch Application Insights adds monitoring for multi-app instance deployments

Amazon Web Services customers can now get detailed health metrics and analysis of their multi-application deployments residing in the same instances with Amazon CloudWatch Application Insights. CloudWatch Application Insights helps customers gain actionable insights for their application environment and AWS resources by making it easy to set up and monitor applications, recognize problems, and use data to make decisions.

Announcing the general availability of AWS HealthImaging

Today, AWS announces the general availability of AWS HealthImaging, a new HIPAA-eligible service that empowers healthcare providers and their software partners to store, analyze, and share medical images at petabyte scale. With HealthImaging, you can run your medical imaging applications at scale from a single, authoritative copy of each medical image in the cloud, while reducing infrastructure costs.

Amazon SageMaker Canvas supports training ML models with different objective metrics

Amazon SageMaker Canvas now provides the ability to train machine learning (ML) models with different objective metrics, allowing you to gain a more comprehensive understanding on the model’s strengths and weaknesses. SageMaker Canvas is a visual interface that enables business analysts and citizen data scientists to generate accurate ML predictions on their own — without requiring any ML expertise or having to write a single line of code.

Amazon SageMaker Canvas supports sharing ML models with Amazon QuickSight

Amazon SageMaker Canvas now supports sharing machine learning (ML) models with Amazon QuickSight, enabling analysts to build models in Canvas and generate predictions to build dashboards in QuickSight. This extends the ML/Analytics integrated solution between Canvas and QuickSight for analysts to build models, generate predictions, enrich them with interactive dashboards, and use insights for effective business decisions, without writing a single line of code.

Amazon EMR Serverless now supports storing logs in Amazon CloudWatch

Amazon EMR Serverless is a serverless option that makes it simple for data analysts and engineers to run open-source big data analytics frameworks like Apache Spark and Apache Hive without configuring, managing, and scaling clusters or servers. Starting today, you can store logs for your EMR Serverless Spark and Hive applications in Amazon CloudWatch.

Personalize your search results with Amazon Personalize and OpenSearch integration

Amazon Personalize launches a new integration with self-managed OpenSearch that enables customers to personalize search results for each user and assists in predicting their search needs. The Amazon Personalize Search Ranking plugin within OpenSearch helps customers to leverage the deep learning capabilities offered by Amazon Personalize and add personalization to OpenSearch search results, without any ML expertise.

AWS IoT Core announces MQTT support for Device Location feature

Today, AWS IoT Core announces the general availability of MQTT support for Device Location. IoT Core Device Location feature allows customers to obtain devices’ location data and build location based applications even when devices don’t have a built in GPS. With IoT Core Device Location feature, customers can use advanced cloud based location solvers, such as Wi-Fi scan, Cellular scan, Global Navigation Satellite System (GNSS) scan, and reverse IP look-up to determine geo-coordinates of their IoT devices for use cases such as map visualization, historical route tracking, and Geo-fencing.

AWS Elemental MediaLive now available in additional AWS Regions

AWS Elemental MediaLive is a broadcast-grade live video processing service. It lets you create high-quality live video streams for delivery to broadcast televisions and internet-connected multiscreen devices, like connected TVs, tablets, smartphones, and set-top boxes.

Amazon SageMaker Canvas announces Document Queries powered by Amazon Textract

Amazon SageMaker Canvas now supports Document Queries, a ready-to-use model powered by Amazon Textract. Document Queries allows you to specify the data you want to extract from structured documents using natural language, without requiring prior knowledge of the document’s structure (table, form, fields, nested data). This eliminates the need for manual processing and searching within extracted data, saving you time and reducing human-error.

Snowflake connectivity for AWS Glue for Apache Spark is now generally available

AWS Glue for Apache Spark now supports native connectivity to Snowflake, which enables users to read and write data from Snowflake without the need to install or manage Snowflake connector libraries. In addition, AWS Glue Studio has new visual ETL capabilities available for Snowflake source and targets to save time when authoring data pipelines for Snowflake. AWS Glue Studio enables ETL (Extract, Transform and Load) developers to visually transform data with a no-code, drag-and-drop interface. With this new connector and visual capabilities, ETL developers can read and write data into Snowflake more effectively using AWS Glue.

AWS Glue Studio now supports Amazon Redshift Serverless

AWS Glue Studio now supports Amazon Redshift Serverless as a data source or target out-of-the-box. AWS Glue Studio enables ETL (Extract, Transform and Load) developers to visually transform data with a no-code, drag-and-drop interface. Glue’s visual interface saves the developer time authoring, running, and monitoring highly scalable ETL jobs. Developers can pull data from a variety of data sources including AWS services like Amazon S3, Amazon Kinesis, and Amazon Redshift. With this new feature, developers can read and write data into Amazon Redshift Serverless more effectively.

Amazon SageMaker Canvas expands data preparation with five new capabilities

Amazon SageMaker Canvas now supports five new data transforms, enabling you to better prepare and analyze your data before building machine learning (ML) models. Data is the foundation of machine learning and transforming raw data to make it suitable for ML model building and generating predictions is key to better insights. Starting today, SageMaker Canvas allows you to change the type of data in your columns between numeric, text, and datetime, while also displaying the associated feature for that data type such as binary and categorical. This gives you the flexibility to manually change the type of data in your columns based on the features. The ability to choose the right data type ensures data integrity and accuracy prior to building ML models. As an example, using a datetime data type ensures only valid dates are stored in that particular column.

AWS Transfer Family launches SFTP connectors

AWS Transfer Family launches Secure File Transfer Protocol (SFTP) connectors, a fully-managed and low code capability to securely and reliably copy files at scale between remote SFTP servers and Amazon S3. Files transferred using SFTP connectors are stored in Amazon S3, enabling you to unlock value from data using analytics, data lakes or AI/ML services in AWS.

Amazon SageMaker Canvas supports custom Amazon S3 output location for ML artifacts

Amazon SageMaker Canvas now supports the ability to provide a custom output location in Amazon S3 for machine learning (ML) artifacts, such as trained models, explainability reports, and prediction results allowing you to organize and structure your output directory in a way that aligns with your specific needs and preferences. SageMaker Canvas is a visual interface that enables business analysts and citizen data scientists to generate accurate ML predictions on their own — without requiring any ML expertise or having to write a single line of code.

Amazon Redshift announces automatic mounting of AWS Glue Data Catalog

Amazon Redshift announces the general availability of automatic mounting of AWS Glue Data Catalog, making it easier for customers to run queries in their data lakes. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in AWS Glue Data Catalog. Now, you can query data lake tables directly from Amazon Redshift Query Editor v2 or your favorite SQL editors.

Amazon CloudWatch Internet Monitor now supports Network Load Balancers as a resource type

Today, Amazon Web Services (AWS) introduces support for Network Load Balancers (NLBs) as a supported resource type in Amazon CloudWatch Internet Monitor. You can now use Internet Monitor to get visibility about internet performance and availability for user traffic directed to specific NLBs. Internet Monitor also supports monitoring Amazon Virtual Private Clouds (VPCs), Amazon CloudFront distributions, and Amazon WorkSpaces directories.

Amazon EMR on EC2 announces support for native LDAP authentication

Amazon EMR is excited to announce a new feature that enables user authentication to EMR on EC2 clusters using Lightweight Directory Access Protocol (LDAP) based credentials. This feature allows administrators to configure EMR on EC2 clusters to authenticate corporate identities in their Active Directory (AD) using LDAP. With this launch, AD users are synced to the EMR on EC2 cluster automatically when LDAP authentication is enabled. This simplifies authentication to EMR clusters for administrators by eliminating the manual steps to sync users and/or implementing application-specific LDAP configuration.

Announcing auto-account association for AWS Billing Conductor billing groups

Starting today, customers can choose to automatically associate all newly created accounts (or any accounts invited to their AWS Organization) with an AWS Billing Conductor billing group. By enabling auto-account association, customers can reduce the steps needed to implement a custom chargeback model. For example, organizations can use the feature to automatically associate all newly created accounts with a default billing group, ensuring all accounts are included in their internal chargeback workflow. Partners can use the feature to automatically associate all new accounts to a default billing group, allowing them to bill their customers for all relevant usage without missing any charges.

AWS DataSync now supports copying data to and from Azure Blob Storage

AWS DataSync support for copying data to and from Azure Blob Storage is now generally available. Using DataSync, you can move your object data at scale between Azure Blob Storage and AWS Storage services such as Amazon S3. AWS DataSync supports writing to block blobs and can read from all blob types within Azure Blob Storage. It can also be used with Azure Data Lake Storage (ADLS) Gen 2.

AWS Glue jobs can now include AWS Glue DataBrew Recipes

AWS Glue Studio Visual ETL jobs now let you use DataBrew Recipes as steps in the flow of transformations. AWS Glue Studio Visual ETL is a no-code job authoring UI for ETL developers with a flow-diagram interface. AWS Glue DataBrew is a no code data preparation tool for business users and data analysts with a spreadsheet-style UI. The new integration between the two makes it simpler to deploy and scale DataBrew jobs and gives DataBrew users access to AWS Glue features not available in DataBrew. The integration also works in code-based jobs.

Amazon QuickSight now supports Snapshot Export APIs

Amazon QuickSight launches new API capabilities that allow you to programmatically export Paginated PDF Reports and CSV content. With these new APIs, you can export and customize content by passing parameters and session tags for Anonymous users. Optionally as part of the API call you can specify your own S3 destination to where the content should be exported.

Amazon Redshift now supports querying Apache Iceberg tables

Amazon Redshift today announces the preview release of Apache Iceberg support, enabling users to run analytics queries on Apache Iceberg tables within Redshift. Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service used by tens of thousands of customers. Whether your data is stored in operational data stores, data lakes, streaming engines or within your data warehouse, Amazon Redshift helps you quickly ingest, securely share data, and achieve the best performance for the best price. Apache Iceberg, one of the most recent open table formats, has been used by many customers to simplify data processing on rapidly expanding and evolving tables stored in data lakes.

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