AWS_SummitThe AWS Summit in New York this week made a series of product and customer announcements

Amazon debuted Macie and Glue at their AWS (Amazon Web Service) Summit in New York this week.

Sensitive data stored in AWS can now be identified and protected from breaches, data leaks and unauthorised access by Amazon Macie which utilises machine learning to do this.

Macie can discover and classify a user’s data that is stored in Amazon S3. It does this by assigning each data item a business value. This data item is then monitored and alerts you to unusual access patterns that could indicate a security threat.

The name Macie says it all about the new Amazon security service; the meaning being “weapon” and a person who is “bold, sporty and sweet”. It covers its job of using data security automation and monitoring to proactively prevent data loss perfectly.

Macie will also prove to be particularly useful for the GDPR in terms of providing customers with dashboards and alerts, as it can detect common sources of personally identifiable information. AWS said, “it will enable customers to comply with GDPR regulations around encryption and pseudonymisation of data.”

The introduction of Macie gives Amazon the market lead in this area. Microsoft’s Azure cloud and Google’s Alphabet are currently doing similar things but not quite as much as Amazon Macie.

CIO at AWS, Stephen Schmidt added, “By using machine learning to understand the content and user behaviour of each organisation, Amazon Macie can cut through huge volumes of data with better visibility and more accurate alerts, allowing customers to focus on securing their sensitive information instead of wasting time trying to find it.”

AWS Glue was also announced at the summit, which Amazon described as a “fully managed, serverless, and cloud-optimised extract, transform and load (ETL) service.”

With this, customers will be able to prepare and load their data into the Amazon Cloud with more ease. Glue will be able to classify associated metadata from a customer’s data, generate data transformative ETL scripts from this and then load the resultant data into a destination data store and complete the task by provisioning the necessary infrastructure.

Glue can carry out analysis in minutes and as it is serverless, so users won’t have to manage any resources. It is also cheap to run as users will only be paying for it when it is running.

Vice president of databases, AI and analytics Raju Gulabani at AWS said “We developed AWS Glue to eliminate much of the undifferentiated heavy lifting involved with ETL. By cataloguing all of a customer’s data and automating the ETL process, AWS Glue not only takes a lot of the hassle out of analytics.”

“It also makes it possible for customers to store their data in as many sources as they want, and very quickly start analysing all of it with whatever AWS service they choose.”

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