The AWS Serverless Application Model (SAM) Command Line Interface (CLI) lets you locally build, test, and debug serverless applications defined by AWS SAM templates. You can now use the sam logs command to fetch, tail, and filter logs generated by your AWS Lambda functions. You can also use the sam local start-lambda command to invoke local Lambda functions from your automated tests.
Amazon Redshift announces free upgrade for DC1 Reserved Instances to DC2
You can now upgrade your Amazon Redshift DC1 Reserved Instances to DC2 Reserved Instances for the remainder of your DC1 reserved term, and get up to twice the performance of DC1 at the same price. DC2 nodes are designed for demanding data warehousing workloads that require low latency and high throughput.
AWS Device Farm Adds Integration with AWS CodePipeline
You can now choose AWS Device Farm as a test provider in your software release pipelines modeled in AWS CodePipeline. This lets you create or select Device Farm projects in the test stage of your pipelines.
AWS Fargate Available in Singapore, Sydney, and Frankfurt Regions
AWS Fargate is now available in three new AWS Regions: Asia Pacific (Singapore), Asia Pacific (Sydney), and EU (Frankfurt).
AWS Fargate is a compute engine for Amazon ECS that lets you run containers in production without deploying or managing servers. Fargate lets you focus on designing and building your applications instead of managing the infrastructure that runs them.
For a full list of AWS Regions where Fargate is available, please visit our Region table
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AWS Systems Manager Run Command Now Streams Output to Amazon CloudWatch Logs
AWS Systems Manager, a unified experience to view operational data from multiple AWS services to automate operational tasks across your AWS resources, now allows streaming of Run Command output to Amazon CloudWatch logs, allowing you to track command execution in near real-time.
Deploy Aviatrix FQDN Egress Filtering on AWS with New Quick Start
This Quick Start builds a highly available, secure Fully Qualified Domain Name (FQDN) Egress Filtering service on the Amazon Web Services (AWS) Cloud in about 10 minutes. It automatically deploys an Aviatrix Controller for enabling Egress Filtering in a new or existing virtual private cloud (VPC). You can connect to VPCs in the AWS Cloud with enhanced security, and access your Amazon Elastic Compute Cloud (Amazon EC2) instances, applications, and services.
Amazon Kinesis Data Analytics is now available in EU (Frankfurt)
Amazon Kinesis Data Analytics is now available in the EU (Frankfurt) AWS Region. With the addition of this region, Kinesis Data Analytics is now available in 4 AWS Regions globally: US (Northern Virginia), US (Oregon), EU (Ireland), and EU (Frankfurt).
AWS Systems Manager Automation Conditional Branching for Step Failure
AWS Systems Manager now supports taking action for Automation step failure by allowing branching to another step within the Automation Document. This feature allows customers to perform graceful exits, send notifications, and a variety of clean up actions when an automation step fails. For example, when an Amazon Machine Image (AMI) update automation step fails midway, the customer can now call for automation to take a snapshot, close the EC2 instance, notify admin, and exit gracefully. Previously, there were only two choices, “Continue” and “Abort” upon failure of a step.
AWS Elemental MediaStore Now Available in Asia Pacific (Seoul) Region
AWS Elemental MediaStore is a video origination and storage service that offers the high performance, predictable low latency, and immediate consistency required for live streaming media combined with the security and durability AWS offers across its services. MediaStore offers an inexpensive method for pass-through and low-latency segmented video content delivery, with pay-as-you-go pricing.
Amazon SageMaker Now Supports Pipe Input Mode for Built-In TensorFlow Containers
Amazon SageMaker now supports Pipe Input Mode for the built-in TensorFlow containers. Pipe Input Mode enables data to stream directly from Amazon Simple Storage Service (Amazon S3) to the TensorFlow container on the training instance, using the TensorFlow dataset construct.