You can now run your applications on AWS Elastic Beanstalk using Amazon EC2 Spot Instances. You can add Amazon EC2 Spot Instances to your environment’s capacity in both single instance and load balanced environments. Previously, Elastic Beanstalk supported only On-Demand and Reserved Instances.  

AWS WAF announces AWS Managed Rules (AMRs), a set of AWS WAF rules curated and maintained by the AWS Threat Research Team. With just a few clicks, AMRs can help protect your web applications from new and emerging threats, so you don’t need to spend time researching and writing your own rules. AMRs are based on common Internet threats, including security risks referenced in the OWASP Top 10 publication. AMRs also include IP reputation lists based on Amazon threat intelligence that can help reduce your exposure to bot traffic.

You can now run Apache Flink and Apache Kafka together using fully managed services on AWS. AWS provides a fully managed service for Apache Flink through Amazon Kinesis Data Analytics, enabling you to quickly build and easily run sophisticated streaming applications. You can use these fully managed Apache Flink applications to process streaming data stored in Apache Kafka running within Amazon VPC or on Amazon MSK, a fully managed, highly available, and secure Apache Kafka service.

Starting today, you can now bring your own JDBC drivers to your Glue Spark ETL jobs. AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easier to prepare and load your data for analytics. AWS Glue has native connectors to connect to supported data sources either on AWS or elsewhere using JDBC drivers. This feature enables you to connect to data sources with custom drivers that were not natively supported in AWS Glue such as MySQL 8 and Oracle 18. You can also use multiple JDBC driver versions in the same Glue job enabling you to migrate data between source and target databases with different versions. To learn more, please visit our documentation .

Today, AWS X-Ray is launching support for Amazon CloudWatch Synthetics (preview), enabling developers and DevOps engineers to trace end-to-end requests for canaries that monitor web application endpoints, and URLs.

Until today, when using AutoML in Forecast customers could only determine the winning algorithm. Although useful, this did not give customers transparency into all the model runs.  

Amazon RDS Performance Insights supports SQL-level metrics on Amazon RDS for Oracle so you can identify high-frequency, long-running, and stuck SQL queries in seconds.

Developers using the Amplify CLI can now view backend environment information in the Amplify Console on project initialization. The Amplify Console offers a single location for the entire team to view and manage the AWS cloud resources required for their fullstack apps.  

The Amazon Redshift cluster elastic resize operation can now be automated using a scheduler that allows you to automatically resize clusters to accommodate changes in workloads that occur on a regular basis. For example, you can now automatically expand a cluster to accommodate heavier workloads as well as shrink a cluster to accommodate lighter workloads at specific times of day. This will allow you to automate cluster resizing to balance price and performance when using Redshift.

An Amazon Aurora Global Database is a single database that spans multiple AWS regions, enabling low latency global reads and disaster recovery from region-wide outages. With today’s launch, you can convert an existing single-region Aurora database to a global one, simply by adding another region to it.