All posts by: Cloud Comrade

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Beginning today, you can use a new Amazon Route 53 Auto Naming API to update the health status of service instances manually. After you register a service instance with a new custom health check configuration, you can call the new API to mark the service instance healthy and start routing traffic to it. Alternatively, you can set the health status to “unhealthy,” and Route 53 will stop routing traffic to this service instance.

You now have more options to configure and deploy REST APIs using the AWS Serverless Application Model (SAM). You can now configure logging, metrics, CORS, and regional endpoints for Amazon API Gateway resources in your AWS SAM template. You can also configure APIs that support binary data and you can define method settings like throttling limits and CacheTTL. Visit the release notes for more details on these new features.

This new Quick Start, built in collaboration with Teradici, deploys a highly available architecture for cloud video editing on the Amazon Web Services (AWS) Cloud in about 30 minutes. Deploying on AWS yields a high-performing environment for transforming videos. Video editing involves large files and requires powerful graphics processing unit (GPU) workstations. Amazon Simple Storage Service (Amazon S3) provides durable, scalable object storage.  

Starting today, you can use the Reserved Instance (RI) Coverage report in AWS Cost Explorer to better understand and manage your Amazon RDS, Amazon Redshift, and Amazon ElastiCache reservations, in addition to your Amazon EC2 RIs. The RI Coverage report allows you to visualize the percentage of running instance hours that are covered by RIs against a user-defined coverage threshold and over a timeline that you define. You can view RI coverage at a high level (e.g., across all running hours) or dive into a detailed view by filtering on account, instance type, region, tags, and more. You can also access additional coverage-related information such as the number of On-Demand hours used, the node type, and the region in which it was used. From there, you can use this information to optimize your RI purchasing strategy (e.g., by identifying instance hours that are consistently running at on-demand rates and purchase matching RIs).

Today, we are excited to announce that customers can deploy Gluon models to their AWS DeepLens device. Gluon, is an open source deep learning interface which allows developers of all skill levels to prototype, build, train and deploy sophisticated machine learning models for the cloud, devices at the edge and mobile apps.