There are some incredible announcements this week which includes:
- Certified Cloud Practitioner exam from home or office.
- AWS launches Machine to Cloud Connectivity Framework.
- Amazon SageMaker supports Spot Instances.
- New release of MapReduce.
Take the Certified Cloud Practitioner exam online.
Now you can take the Certified Cloud Practitioner exam in the comfort of your own home or office at any hour of the day. The exam will be delivered online and will be supervised using your webcam. So you need a reliable internet connection as well as a webcam attached to the computer that you are using to take the exam. Along with these, a system compatibility check will also be run before you book the exam to make sure your home or office setup is compatible with testing software. This is a piece of great news for anyone wishing to take the exam and finding it difficult to attend the testing centre in person.
Machine to Cloud Connectivity Framework
AWS launches Machine to Cloud Connectivity Framework which is a great new solution that allows you to securely connect devices and equipment located in a factory to AWS. Manufacturing equipment, comparable packaging equipment and any kind of connected devices or even a robot that you might expect to see in a modern AWS factory can utilise this facility!
You can deploy the solution using already made CloudFormation Template which will provision number of services like AWS IoT core which handles communication between your devices in the cloud as well as AWS IoT Greengrass which enables your device to operate as an independent edge device and even execute Lambda functions or run machine learning models when they are disconnected from their network.
SageMaker supports Spot Instances
The Amazon SageMaker now supports EC2 Spot Instances with your machine learning models. SageMaker is a fully managed machine learning platform which allows you to build, train, and deploy machine learning models in AWS without the headache of having to provision and manage your infrastructure. Also, you can now lower your SageMaker machine learning training costs by up to 90% by using Spot Instances which like to take advantage of the unused EC2 capacity at significant discount compared to on-demand pricing. You do need to be careful with the EC2 Spot Instance that is getting a large discount because of the capacity that is getting spared and unused. Hence, at any time, the instance may be reclaimed by AWS if they need the capacity.
New release of Elastic MapReduce
EMR manages big data platform that supports Apache Spark, Apache HBase, Apache Hive and other big data frameworks. This new release enables you to achieve up to 60 times performance increase for Apache Sparks which is one of the most commonly used analytics engines for big data processing. The new release also includes Beta Integration with AWS Lake Formation allowing customers to integrate the data stored in Central Data Lakes with their EMR platforms.