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Amazon Gamelift Launches FleetIQ and Spot Instances
AWS previously launched Amazon GameLift, a scalable runtime environment where you can run multiplayer games on the cloud. You may upload a game to this environment and set the type of EC2 instance you want to host it on. GameLift with automatically scale the instances you require.
To help lower your player and hourly costs, Amazon GameLift has introduced a new feature: whereas these instances only used On-demand before, now you may use Amazon GameLift Spot Instances in GameLift fleets. This means they employ unused compute capacity, with prices that change over time. All in all, they may potentially give savings of 90% compared to On-demand instances.
Amazon ECS Introduces Integrated Discovery
AWS has introduced integrated service discovery to Amazon ECS. This allows ECS to automatically register itself with a DNS name in Amazon Route 53. Not only is the DNS name predictable and friendly, the service will also keep Route 53 hosted zone updated as necessary. This lets other services lookup where they need to make connections, depending on the state of each service.
Formerly, one had to configure traditional ways of service discovery like consul that need provisioning and added infrastructure, or perhaps agents installed in containers or instances. You would need to run your own discovery system or connect each service to a load balancer. Starting now, however, you may configure automated service discovery for containerized services using ECS console, AWS CLI or the ECS API.
Amazon Sagemaker Now Uses Auto-scaling
Amazon SageMaker has allowed users to create, train, and deploy their own machine learning models. SageMaker is designed to make machine learning much simpler and easier to manage. In the past, AWS clients have used it to successfully handle Jupyter notebooks and manage distributed training. They have also deployed models to SageMaker hosting for inferences in order to integrate machine learning with their applications.
Now, AWS has announced an easier means to manage production ML models. Amazon SageMaker will now have Auto Scaling, which will automatically scale the number of instances depending on a designated policy.
The post Cloud Month in Review–March 2018 appeared first on PolarSeven Cloud Consulting.