Amazon SQS makes it easier to manage lists of queues by allowing callers to iterate through the results of ListQueues and ListDeadLetterSourceQueues APIs using a multi-page format. You can check the status of your request and receive the results in multiple pages by setting the MaxResults parameter to a value between 1 and 1000. You can receive up to a maximum of 1000 results in a single page. If there are more than 1000 results to display, you will receive a Next Token. Use the Next Token to receive the next set of results until the Next Token is null. This enables you to get all the results from your list request in multiple pages. We recommend you to use paginated lists instead of getting all the results in a single request. Furthermore, you can continue filtering your results of list requests using QueueNamePrefix.

Today, AWS Global Accelerator announces the ability to easily obtain a fixed entry point for an Application Load Balancer and improve the performance for your user traffic by as much as 60%, with just a single click in the AWS Management Console. When you create a load balancer in the console, you can select a check box to enable Global Accelerator as an add-on service. Behind the scenes, Elastic Load Balancing and Global Accelerator work together to set up an accelerator in your account and put it in front of your load balancer. After you create your load balancer, choose the Integrated Services tab to see the static IP addresses and DNS name that you can use to start routing user traffic to the load balancer over the AWS global network.

Amazon Kinesis Data Firehose is now available in the Europe (Milan) and Africa (Cape Town) AWS Regions. Amazon Kinesis Data Firehose is the easiest way to load streaming data into data stores and analytics tools. You can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and Splunk, enabling near real-time analytics with existing business intelligence tools you are already using.

Amazon AppFlow is a fully managed integration service that enables customers to securely transfer data between AWS services and software-as-a-service (SaaS) applications in just a few clicks. Amazon AppFlow now supports automatic import of newly created Salesforce fields into Amazon S3 without requiring the user to update their flow configurations. Also, Amazon AppFlow now allows users to import deleted records from Salesforce to any supported destination.

The AWS SDK for Java v2 helps take the complexity out of coding by providing Java APIs for AWS services including Amazon S3, Amazon ECS, DynamoDB, AWS Lambda, and more. Today, we are pleased to announce the Metrics Module in AWS SDK for Java v2 as in Developer Preview.  

We’re excited to announce the launch of AWS Cloud Financial Management for Builders, a new three-day, intermediate-level, instructor-led training course. Built by AWS experts, it’s designed for all builders and technologists interested in learning to design cost-optimized architectures, particularly developers, solutions architects, DevOps, and systems administrators.

Starting today, customers considering AWS for running on-premises workloads can request a business case from Migration Evaluator (Formerly TSO Logic) at no cost. Creating business cases on your own can be a time-consuming process and does not always identify the least expensive deployment and purchasing options. With Migration Evaluator, you get access to AWS expertise, visibility into the costs associated with multiple migration strategies, and insights on how reusing your existing software licensing further reduces costs.

Amazon Elasticsearch Service now enables you to deploy your instances across three Availability Zones (AZs) providing better availability for your domains. If you enable replicas for your Elasticsearch indices, Amazon Elasticsearch Service distributes the primary and replica shards across nodes in different AZs to maximize availability. 

Amazon EMR cluster running G4dn instances is 5.4X cheaper and 4.5X faster compared to an Amazon EMR cluster running Amazon EC2 R5 Memory-optimized instances. To learn more, please see Nvidia Blog Post .  

AWS Content Analysis is an AWS Solutions Implementation that customers can use to obtain a broader understanding of their media content through machine learning. The solution brings together the capabilities of different AWS machine learning tools to generate meaningful insights from metadata gleaned through video analysis. Customers can use the solutions implementation, modify it to fit their own workflows and build their own analytical solutions for media in the AWS Cloud.