Quick Peek

  • IPv6 enabled for Network Load Balancer
  • Announcing an easy way to run containerized applications on the cloud named Amazon Lightsail Containers
  • Amazon EC2 Auto Scaling supports attaching multiple network interfaces at launch
  • Using SQL-compatible query language to insert, update, delete and query table data in Amazon DynamoDB
  • Amazon Elastic Compute Cloud Auto Scaling announces support for multiple launch templates for Auto Scaling groups
  • Amazon Elasticsearch Service announces support for Elasticsearch version 7.9
  • Amazon RDS Performance Insights supports additional dimension to segment performance data on Amazon RDS for MySQL, Amazon Aurora with MySQL compatibility, Amazon RDS for MariaDB, Amazon RDS for PostgreSQL, and Amazon Aurora with PostgreSQL compatibility
  • Amazon Elastic Container Service Cluster Auto Scaling now supports specifying a custom warm-up time, for instance

IPv6 enabled for Network Load Balancer

Network Load Balancer (NLB) supports Internet Protocol version 6 (IPv6), enabling you to configure Network Load Balancer (NLB) to operate in dual-stack mode, accepting both IPv4 and IPv6 clients connections.

For this, enable IPv6 for your VPC, assigning an IPv6 IP address range to your subnet. Then create a Network Load Balancer with dual-stack IP address type. Your NLB receives IPv6 addresses automatically. The load balancer’s IPv6 addresses are registered in a new AAAA DNS record created for your NLB.


Announcing an easy way to run containerized applications on the cloud named Amazon Lightsail Containers

You now can run containerized workloads on the cloud with little-to-no prior cloud experience provided by Amazon Lightsail. With Lightsail Containers, you can now deploy containerized applications directly to the cloud using the Docker images with just a few clicks, through an easy to use interface. In this way, you can focus on your application code as Lightsail takes care of all the infrastructure management complexities. You need to create a Container Service by specifying the power, scale suitable for your application traffic, and image.


Amazon EC2 Auto Scaling supports attaching multiple network interfaces at launch

Now, Amazon EC2 Auto Scaling lets you specify multiple network interfaces in a launch template, and your Auto Scaling group will attach them to instances as they launch automatically instead of any custom scripts.


Using SQL-compatible query language to insert, update, delete and query table data in Amazon DynamoDB

You can now use PartiQL (a SQL-compatible query language) to insert, update, delete, and query table data in Amazon DynamoDB. It is easier to interact with DynamoDB and also runs queries in the AWS Management Console using PartiQL. This enables developers to use a familiar, structured query language to perform these operations, increasing productivity.

The same availability, latency, and performance when performing DynamoDB operations can be expected from PartiQL.


Amazon Elastic Compute Cloud Auto Scaling announces support for multiple launch templates for Auto Scaling groups

Amazon EC2 Auto Scaling lets you configure your Auto Scaling group with multiple launch templates when using a MixedInstancesPolicy and specify multiple instance types. With this enhancement, you can specify a launch template alongside the instance type in the overrides of your MixedInstancesPolicy. That launch template will be used whenever launching instances of its corresponding instance type.


Amazon Elasticsearch Service announces support for Elasticsearch version 7.9

AWS has released the Elasticsearch Service that now supports the open-source Elasticsearch 7.9 version. The support for concurrent snapshot operations is also added, and you can create manual snapshots while automatic snapshots are in progress. Furthermore, this release also includes support for recently released features like detailed audit logging of all Elasticsearch requests, Security Assertion Markup Language (SAML) to offer single sign-on (SSO) for Kibana, and custom domain names.


Amazon RDS Performance Insights supports additional dimension to segment performance data on Amazon RDS for MySQL, Amazon Aurora with MySQL compatibility, Amazon RDS for MariaDB, Amazon RDS for PostgreSQL, and Amazon Aurora with PostgreSQL compatibility

Amazon RDS Performance Insights supports an additional dimension to identify the source of high-frequency, long-running, and stuck SQL queries faster. The new Performance Insights dimension is available on Amazon RDS for MySQL, Amazon Aurora with MySQL compatibility, Amazon RDS for MariaDB, Amazon RDS for PostgreSQL, and Amazon Aurora with PostgreSQL compatibility.

RDS Performance Insights supports segmenting the performance data by additional dimensions, such as database name, application, and session type. You can determine if a specific application generates an unusually high load or is issuing SQL queries that take unusually long to complete. You can then improve your application by changing connection patterns, optimizing a slow SQL query, scaling your database, and adding an index to your database.


Amazon Elastic Container Service Cluster Auto Scaling now supports specifying a custom warm-up time, for instance

Amazon Elastic Container Service (Amazon ECS) Cluster Auto Scaling (CAS) now supports specifying a custom instance warm-up time instead of the default 300 seconds, making scaling more responsive.

Once the specified warm-up time expires, the instance is counted toward the Auto Scaling group (ASG). The CAS then proceeds with its next iteration of calculations to estimate the number of instances required. This prevents the ASG from adding more instances than needed.