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Amazon Macie announces a slew of new capabilities including support for cross-account sensitive data discovery, scanning by Amazon S3 object prefix, improved pre-scan cost estimation, and added location detail in findings

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We are excited to announce a series of new capabilities that have been added to Amazon Macie to make it easier to configure, scope, and run sensitive data discovery in AWS, including support for scanning jobs that cover Amazon S3 buckets residing across multiple accounts, scoping of scans by object prefix, better cost estimation for visibility of spend before jobs are submitted, and sensitive data location information added to Macie findings.  

Insights is now generally available for AWS X-Ray

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Today, AWS X-Ray launches Insights , which helps customers proactively discover issues in applications by using anomaly detection. X-Ray Insights enables developers and DevOps engineers to detect anomalies in fault rate for an application and then notify their teams on these issues and why it occurred.

Amazon S3 Batch Operations adds support for Delete Object Tagging

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You can now perform S3 Delete Object Tagging operations using Amazon S3 Batch Operations to delete object tags across many objects with a single API request or a few clicks in the S3 Management Console. S3 Batch Operations lets you perform repetitive or bulk actions like copying objects or replacing tag sets across billions of objects. S3 Batch Operations handles all the manual work, including managing retries and displaying progress.  

Amazon Elastic File System triples read throughput

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Amazon Elastic File System (Amazon EFS) now allows you to drive up to 3x higher read throughput on your file system. For example, bursting mode file systems now provide 300MB/s of bursting read throughput, or 300MB/s per TiB of data stored in Amazon EFS standard, whichever is higher. If you have configured 1 GB/s of provisioned throughput, your application can now drive up to 3 GB/s for read operations (and continue to drive 1GB/s for write operations) without any application or configuration changes.  

Amazon Managed Blockchain now supports resource tagging and tag-based access control

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Amazon Managed Blockchain now supports assigning tags to networks, members, proposals, invitations, and nodes. Tags can be assigned to existing resources and to new resources at the time of creation. You can also define fine-grained access controls using tags and AWS Identity and Access Management (IAM) policies to control access to resources and actions. Tags are key-value pairs that you can assign to resources to easily organize and search for resources, automate resource activities, create cost allocation reports, and control access to resources.

Amazon GuardDuty introduces machine learning domain reputation model to expand threat detection and improve accuracy

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Amazon GuardDuty introduces a new machine learning domain reputation model that can categorize previously unseen domains as highly likely to be malicious or benign based on their behavioral characteristics. GuardDuty uses this new capability to alert customers when an EC2 instance in their AWS environment is communicating with a domain identified as malicious and to improve the accuracy of existing domain based threat detections.

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