[
    {
        "type": "api-change",
        "category": "ServiceDiscovery",
        "description": "AWS Cloud Map lets you define friendly names for your cloud resources so that your applications can quickly and dynamically discover them. When a resource becomes available (for example, an Amazon EC2 instance running a web server), you can register a Cloud Map service instance. Then your application can discover service instances by submitting DNS queries or API calls."
    },
    {
        "type": "api-change",
        "category": "SageMaker",
        "description": "Amazon SageMaker now has Algorithm and Model Package entities that can be used to create Training Jobs, Hyperparameter Tuning Jobs and hosted Models. Subscribed Marketplace products can be used on SageMaker to create Training Jobs, Hyperparameter Tuning Jobs and Models. Notebook Instances and Endpoints can leverage Elastic Inference accelerator types for on-demand GPU computing. Model optimizations can be performed with Compilation Jobs. Labeling Jobs can be created and supported by a Workforce. Models can now contain up to 5 containers allowing for inference pipelines within Endpoints. Code Repositories (such as Git) can be linked with SageMaker and loaded into Notebook Instances. Network isolation is now possible on Models, Training Jobs, and Hyperparameter Tuning Jobs, which restricts inbound\/outbound network calls for the container. However, containers can talk to their peers in distributed training mode within the same security group. A Public Beta Search API was added that currently supports Training Jobs."
    },
    {
        "type": "api-change",
        "category": "EC2",
        "description": "Adds the following updates: 1. You can now hibernate and resume Amazon-EBS backed instances using the StopInstances and StartInstances APIs. For more information about using this feature and supported instance types and operating systems, visit the user guide. 2. Amazon Elastic Inference accelerators are resources that you can attach to current generation EC2 instances to accelerate your deep learning inference workloads. With Amazon Elastic Inference, you can configure the right amount of inference acceleration to your deep learning application without being constrained by fixed hardware configurations and limited GPU selection. 3. AWS License Manager makes it easier to manage licenses in AWS and on premises when customers run applications using existing licenses from a variety of software vendors including Microsoft, SAP, Oracle, and IBM."
    },
    {
        "type": "feature",
        "category": "LicenseManager",
        "description": "AWS License Manager makes it easier to manage licenses in AWS and on premises when customers run applications using existing licenses from a variety of software vendors including Microsoft, SAP, Oracle, and IBM. AWS License Manager automatically tracks and controls license usage once administrators have created and enforced rules that emulate the terms of their licensing agreements. The capabilities of AWS License Manager are available through SDK and Tools, besides the management console and CLI."
    },
    {
        "type": "feature",
        "category": "AppMesh",
        "description": "AWS App Mesh is a service mesh that makes it easy to monitor and control communications between microservices of an application. AWS App Mesh APIs are available for preview in eu-west-1, us-east-1, us-east-2, and us-west-2 regions."
    },
    {
        "type": "api-change",
        "category": "Lightsail",
        "description": "This update adds the following features: 1. Copy instance and disk snapshots within the same AWS Region or from one region to another in Amazon Lightsail. 2. Export Lightsail instance and disk snapshots to Amazon Elastic Compute Cloud (Amazon EC2). 3. Create an Amazon EC2 instance from an exported Lightsail instance snapshot using AWS CloudFormation stacks. 4. Apply tags to filter your Lightsail resources, or organize your costs, or control access."
    }
]