With AWS for Fluent Bit version 2.0.0, customers can now send container logs from Amazon ECS, Amazon EKS or AWS Fargate to Amazon Kinesis Data Streams. The AWS for Fluent Bit container image is a lightweight log collector and shipper for containerized environments. It is the recommended logging agent for Amazon ECS, Amazon EKS, and AWS Fargate. The container image is available on Docker Hub, as well as regionalized Amazon ECR repositories provided by AWS.
Encrypt your Amazon DynamoDB data by using your own encryption keys
Amazon DynamoDB is a fully managed, nonrelational database that delivers reliable performance at any scale. DynamoDB encrypts all your data at rest by default with an AWS owned customer master key (CMK), unless you opt to use a AWS managed CMK. Starting today, you also can use customer managed CMKs , which means you can have full control over how you encrypt and manage the security of your DynamoDB data.
Improve the Security Between AWS Applications and Your Self-Managed Active Directory with Secure LDAP using AWS Managed Microsoft AD
AWS Directory Service for Microsoft Active Directory, also known as AWS Managed Microsoft AD, can now encrypt Lightweight Directory Access Protocol (LDAP) communications between AWS applications, such as Amazon Workspaces and Amazon Chime, and your self-managed AD. This allows you to better protect your organization’s identity data and meet your security requirements by enabling AWS Managed Microsoft AD as your Secure LDAP (LDAPS) client.
Access your AWS Regions faster using the AWS Management Console
The AWS Management Console now makes it quicker for you to access your favorite AWS Regions , because you can find the right Region by its code (e.g. us-east-1), and not just by its name (e.g. US East (N. Virginia)). You save time and effort because you no longer have to refer to AWS documentation to get this information.
AWS Managed Services (AMS) now supports AWS CloudFormtaion Stack Update
AWS Managed Services (AMS) launched support for AWS CloudFormation (CFN) Stack Update. You can now make changes to your stack’s configurations or change it’s resources, such as new input parameter values or updated template, through the AMS request for change (RFC) process. Changes submitted are validated for safety and only nondestructive changes are automatically executed. For destructive changes, a change set is provided to you for approval before automated execution.
Amazon Elastic Inference now supports resource tagging
You can now assign AWS resource tags to Amazon Elastic Inference accelerators. Each tag consists of a key and an optional value, both of which you define. You can use tags to easily organize and identify your resources and create cost allocation reports , among other benefits. You can add or remove resource tags from Elastic Inference accelerators using API, CLI, or SDK.
New Amazon CloudWatch Contributor Insights for Amazon DynamoDB (Preview) helps you identify frequently accessed keys and database traffic trends
Amazon CloudWatch Contributor Insights for Amazon DynamoDB (Preview) is a new diagnostic tool that provides an at-a-glance view of the traffic trends of your DynamoDB table and helps you identify the most frequently accessed keys. Now, you can monitor a table’s item access patterns continuously and also use CloudWatch Contributor Insights to provide graphs and visualizations of the table’s activity. You can use this information to better understand the top drivers of your application’s traffic and respond appropriately to unsuccessful requests.
Amazon Athena Adds support for User Defined Functions (UDF)
Amazon Athena now supports user-defined functions (UDFs), a feature that enables customers to write custom scalar functions and invoke them in SQL queries. While Athena provides built-in functions , UDFs enable customers to perform custom processing such as compressing and decompressing data, redacting sensitive data, or applying customized decryption.
Amazon Athena adds support for running SQL queries across relational, non-relational, object, and custom data sources
Amazon Athena now enables users to run SQL queries across data stored in relational, non-relational, object, and custom data sources. With federated querying, customers can submit a single SQL query that scans data from multiple sources running on-premises or hosted in the cloud.
Amazon Athena adds support for invoking machine learning models in SQL queries
Today, Amazon Athena released a new feature that allows users to easily invoke machine learning models for inference directly from their SQL queries. The ability to use machine learning models in SQL queries makes complex tasks such anomaly detection, customer cohort analysis, and sales predictions as simple as invoking a function in a SQL query.