Amazon Elasticsearch Service now supports SQL Workbench and SQL CLI to run queries on Elasticsearch indexes with the conventional and familiar database language. SQL Workbench, a popular open source visual tool used to manage database environments, is now integrated in Kibana to view the results of SQL queries executed on Elasticsearch indexes. SQL CLI provides the flexibility to run ad-hoc or predefined queries from client applications written in different programming languages.

Amazon Personalize uses machine learning technology perfected from over 20 years of recommender systems development at Amazon.com. With Amazon Personalize you are can personalize recommendations for products, videos, music, ebooks, ads, marketing emails, and more, for your users, without any prior machine learning experience.

You can now write the results of an Amazon Redshift query to an external table in Amazon S3 either in text or Apache Parquet formats. The external table metadata will be automatically updated and can be stored in AWS Glue, AWS Lake Formation, or your Hive Metastore data catalog. This enables you to easily share your data in the data lake and have it immediately available for analysis with Amazon Redshift Spectrum and other AWS services such as Amazon Athena, Amazon EMR, and Amazon SageMaker. Amazon Redshift Spectrum enables you to power a lake house architecture to directly query and join data across your data warehouse and data lake.

Following the April 24, 2020 announcement of the availability of PostgreSQL 11 support with Amazon Aurora with PostgreSQL compatibility in all commercial AWS Regions, we have expanded availability to AWS GovCloud (US) Regions. PostgreSQL 11 includes major improvements to partitioning, improvements to parallelism, and many other useful performance improvements like adding columns with a non-null column default faster. This version includes SQL stored procedures that allow embedded transactions within a procedure.

Amazon CloudWatch Application Insights launched several new features to enhance observability for customers’ applications. Starting today, CloudWatch Application Insights expands monitoring support for two databases, in addition to Microsoft SQL Server – MySQL and Amazon DynamoDB. This enables customers to easily configure monitors for these databases on CloudWatch and detect common errors such as slow queries, transaction conflicts, and replication latency.

Amazon Elastic Container Service (ECS) cluster auto scaling is now available in seven additional regions: Europe (Paris), Europe (Stockholm), Middle East (Bahrain), South America (São Paulo), Asia Pacific (Hong Kong), China (Beijing), operated by Sinnet, and China (Ningxia), operated by NWCD.

You can now restrict direct access to AWS Elemental MediaPackage by securing requests for VOD content using CDN authorization. With CDN authorization, content requests require a specific HTTP origin header and authorization code. MediaPackage verifies this code before it serves any content. For instructions on how to configure CDN authorization for live endpoints, please refer to the documentation pages .

You can now filter queue metrics by channel within contact flows for a single queue. With the launch of chat, queue metrics blended both voice and chat contacts. Now you can filter queue metrics by contact type when configuring the ‘Get queue metrics’ block. For example, based on the number of contacts in a blended queue, the contact flow designer can calculate the effective hold time to manage the duration a customer spends waiting.

Amazon Elastic Container Service (ECS) has added support for AWS PrivateLink in three additional regions: Africa (Cape Town), Europe (Milan), and Middle East (Bahrain).

Amazon Aurora with PostgreSQL compatibility now supports T3.large instances, in addition to the T3.medium and R5 class instances already available. Using T3.large instances with Amazon Aurora PostgreSQL is a cost-effective option for smaller workloads such as test, dev, and QA, while still giving you the option to use larger class instances for production deployments.