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General Availability: A new addition to the Amazon EC2 memory-optimized X1 Instance family – x1e.32xlarge

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Amazon EC2 X1 instances were launched to extend the elasticity, simplicity, and cost savings of the AWS cloud to enterprise-grade applications with the largest dataset requirements for our customers. Today, we are excited to announce the general availability of a new EC2 instance in the X1 family – x1e.32xlarge – to take those benefits further for our customers. x1e.32xlarge offers 3,904 GiB of DDR4 instance memory, the most memory offered by any EC2 instance. This new instance enables customers to run larger in-memory databases, such as SAP HANA, and other memory-intensive and latency sensitive workloads compared to the previously available X1 instances.

Auto Scaling Lifecycle Hooks Enhancements

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You can now create and manage lifecycle hooks for Auto Scaling Groups using the AWS management console. Previously, this functionality was only available through the AWS Application Programming Interface (API) , Command Line Interface (CLI) , and AWS CloudFormation . In addition, creating lifecycle hooks is now more convenient as it can be done in the same step as creating your Auto Scaling Group using the ‘CreateAutoScalingGroup’ call through the AWS API and CLI .

Amazon Redshift now supports late-binding views referencing Amazon Redshift and Redshift Spectrum external tables

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You can now create a view that spans Amazon Redshift and Redshift Spectrum external tables. With late-binding views, table binding will take place at runtime, providing your users and applications with seamless access to query data. Late-binding views allows you to drop and make changes to referenced tables without affecting the views. With this feature, you can query frequently accessed data in your Amazon Redshift cluster and less-frequently accessed data in Amazon S3, using a single view. Simply archive historical data to Amazon S3, create an external table referencing the relevant files, and then create a view referencing both the Amazon Redshift and the Redshift Spectrum external tables.

Amazon Aurora Enables Database Activity Monitoring with CloudWatch Logs

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Starting today, you can send events recorded in Amazon Aurora audit logs to CloudWatch Logs. Audit logs include events such as database logins, user information, details of queries executed, and impacted tables. With these events tracked in CloudWatch Logs, you can create CloudWatch Metrics and Alarms to continuously monitor activity in your Aurora database. For example, you can define metrics for DML (Data Manipulation Language) queries performed on critical tables, and set up alarms. These alarms can alert you whenever undesired changes are made to your tables. Additionally, you can create graphs and dashboards with CloudWatch to visualize activity in your database, detect patterns, and identify issues at a glance.

Amazon Inspector expands security assessment support for RHEL 7.4

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Amazon Inspector is pleased to announce expanded support for security assessments on Red Hat Enterprise Linux 7.4 within Amazon EC2. You can now run assessments for Common Vulnerabilities & Exposures (CVE), Amazon Security Best Practices, and Runtime Behavior Analysis on the most recent version of Red Hat Enterprise Linux. To run security assessments, simply install the Amazon Inspector AWS Agent on the desired EC2 instance, configure your assessment in the Amazon Inspector console, and run your assessment. 

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