04Sep 2018

Amazon CloudWatch Metrics for Amazon S3 now includes storage metrics for Amazon Glacier and S3 OneZone-Infrequent Access (S3 One Zone-IA) storage classes in the AWS GovCloud (US) Region. Storage that has been uploaded to S3 One Zone-IA or transitioned to S3 One Zone-IA or Amazon Glacier from S3 Standard or S3 Standard-IA storage classes using S3 Lifecycle policies will be available in CloudWatch storage metrics. These storage metrics will also include object overhead bytes applied to objects in Amazon Glacier and small objects in S3 Standard-IA and S3 One Zone-IA.

04Sep 2018

Amazon SageMaker now supports a new HTTP header for the InvokeEndpoint API action called CustomAttributes, which can be used to provide additional information about an inference request or response. Using this header, it is easy to pass custom information such as trace ID, application specific identifier or other metadata to the inference request or response. This will help customers keep track of their requests or responses for audits or tracking metrics.

03Sep 2018

AWS Glue now supports data encryption at rest for ETL jobs and development endpoints. You can configure ETL jobs and development endpoints to use AWS Key Management Service (KMS) keys to write encrypted data at rest. You can also encrypt the metadata stored in the Glue Data Catalog using keys that you manage with AWS KMS. Additionally, you can use AWS KMS keys to encrypt job bookmarks and the logs generated by crawlers and ETL jobs.

30Aug 2018

AWS WAF now supports full logging of all web requests inspected by the service. Customers can store these logs in Amazon S3 for compliance and auditing needs as well as use them for debugging and additional forensics. The logs will help customers understand why certain rules are triggered and why certain web requests are blocked. Customers can also integrate the logs with their SIEM and log analysis tools. 

30Aug 2018

The Amazon Kinesis Video Streams Producer SDK is now available for Microsoft Windows to help you stream video into AWS from sources such as webcams, USB cameras, or RTSP (network) cameras connected to your Microsoft Windows machine.

Amazon Kinesis Video Streams makes it easy to securely stream video from millions of connected devices to AWS for real-time machine learning (ML), storage, and batch-oriented processing and analytics. It also durably stores, encrypts, and indexes video data in your streams, and allows you to access your data through easy-to-use APIs.

Amazon Kinesis Video Streams provides Producer SDKs in C++ and Java that you can build, configure, and install on devices. This software makes it easier to securely and reliably stream video into AWS frame-by-frame in real-time. In addition to Mac OS, Android, Linux, and Raspbian, the C++ Producer SDK is now also available for Microsoft Windows. Developers can use the Minimal GNU for Windows (MinGW) or the Microsoft Visual Studio C++ Compiler (MSVC) to build the producer SDK from source and start streaming from cameras connected to a Microsoft Windows machine. Additionally, we have also packaged the Producer SDK GStreamer Plug-in for Windows as a Docker image so you can simply do a Docker pull and get started with streaming video in minutes. Please refer the developer documentation to learn more.

Refer to the AWS global region table for Amazon Kinesis Video Streams availability. 

30Aug 2018

Amazon Route 53 Auto Naming is now available in five additional AWS regions: EU (Frankfurt), EU (London), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney).

Amazon Route 53 Auto Naming simplifies the management of DNS names and health checks for microservices that run on top of AWS when microservices scale up and down. You can call the Auto Naming APIs to create a service, and then register instances of that service with a single API call. Amazon Route 53 Auto Naming will automatically populate the DNS records and optionally create a health check for the service endpoint. When a new service instance is registered, you can access it by making a simple DNS query for the service name.

Amazon Route 53 Auto Naming API powers Amazon Elastic Container Service (Amazon ECS) service discovery functionality and enables unified service discovery for services managed by Amazon ECS and Kubernetes.

You can use Amazon Route 53 Auto Naming APIs in the following AWS regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), EU (Ireland), EU (Frankfurt), EU (London), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney) regions. For more information on AWS regions and services, please visit the AWS global region table.

To learn more about Amazon Route 53 Auto Naming, please see our documentation and product page.

29Aug 2018

Amazon Elastic Container Service (Amazon ECS) now includes integrated service discovery in EU (Frankfurt), EU (London), Asia Pacific (Tokyo), Asia Pacific (Sydney), and Asia Pacific (Singapore) regions.

Amazon ECS service discovery makes it easy for your containerized services to discover and connect with each other. Amazon ECS creates and manages a registry of service names using the Route53 Auto Naming API so you can refer to a service by name in your code and write DNS queries to have the service name resolve to the service’s endpoint at runtime.

Today, service discovery is availablefor all networking modes for EC2 launch type or with AWS Fargate.

To learn more, visit the Amazon ECS Service Discovery documentation.  

You can use Amazon ECS Service Discovery in all AWS regions where Amazon ECS and Amazon Route 53 Auto Naming are available. These now include EU (Frankfurt), EU (London), Asia Pacific (Tokyo), Asia Pacific (Sydney), and Asia Pacific (Singapore) regions in addition to US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), and EU (Ireland) regions where ECS service discovery was already available.

29Aug 2018

AWS CodeBuild now supports build projects with multiple input sources and output artifacts. Your projects can now use one or more sources from Amazon S3, AWS CodeCommit, GitHub, GitHub Enterprise, or Bitbucket and can upload multiple sets of artifacts to one or more Amazon S3 buckets. You can also configure your project to have no input source. You can now use the AWS CodePipeline integration with CodeBuild to create a pipeline with multiple input and output artifacts to a CodeBuild project.