In Cloud Computing This Week [Sept 24th 2021]

Amazon Macie now allows you to select which managed data identifiers  to use when you create a sensitive data discovery  job. This allows you to customize what data types you deem sensitive and would like Macie to alert on per specific data governance and privacy needs in your organization. When you create a job, choose from the growing list of managed data identifiers such as personally identifiable information (PII), financial information, or credential materials that you would like to target for each sensitive data discovery job you configure and run with Macie.

Amazon Connect Customer Profiles now supports out-of-the-box integration with product purchase history from Salesforce . When a customer calls or messages a contact center for service, Amazon Connect Customer Profiles equips contact center agents with the customer information they need to deliver personalized customer service and resolve issues quickly. Customer Profiles helps make it simple to bring together customer information (e.g., name, address, phone number, contact history, purchase history, open issues) from multiple applications into a unified customer profile, delivering the profile directly to the agent as soon as they begin interacting with the customer. If an agent wants to understand previous interactions to service a customer, they can visit Contact Trace Record (CTR)  details page by clicking “CTR Details”  to review information such as call categorization, call sentiments and transcripts. Customer Profiles  can be used out of the box by agents or embedded in your existing agent application .

AQUA (Advanced Query Accelerator) for Amazon Redshift is now generally available for Amazon Redshift RA3.xlplus nodes.

AWS WAF extends its regular expression (regex) support, allowing regex patterns to be expressed in-line within a rule statement. Previously, you had to create a regex pattern set, which provides a collection of regex patterns in a rule statement, even if you wanted to use just a single regex pattern in your WAF rule logic. With in-line regex, you can now include a single regex pattern directly inside a WAF rule statement, simplifying how WAF rules are expressed within your web ACL.

This week AWS announced the general availability of AWS Distro for OpenTelemetry (ADOT) for tracing, a secure, production-ready, AWS-supported distribution of the OpenTelemetry  project. With this launch, AWS customers can use OpenTelemetry APIs and SDKs in Java, .Net, Python, Go, and JavaScript to collect and send traces to AWS X-Ray and monitoring destinations supported by the OpenTelemetry Protocol (OTLP).

AWS Service Catalog AppRegistry and AWS Systems Manager Application Manager now provide an end-to-end AWS application management experience. With this release, customers can use AppRegistry to create applications within their infrastructure as code, CI/CD pipelines, and post-provisioning processes, and use Application Manager to view application operational data and perform operational actions. 

Amazon Simple Email Service (Amazon SES) is now available in the Asia Pacific (Osaka) AWS Region. Amazon SES is a scalable, cost-effective, and flexible cloud-based email service that allows digital marketers and application developers to send marketing, notification, and transactional emails from within any application. To learn more about Amazon SES, visit this page.

Amazon ElastiCache for Redis and Memcached now supports Graviton2 M6g and R6g instance families in additional regions: South America (Sao Paulo), Asia Pacific (Hong Kong, Seoul), Europe (London, Stockholm), North America (Montreal), US East (GovCloud US East), US West (GovCloud US West), and mainland China (Ningxia, Beijing). Customers choose Amazon ElastiCache for workloads that require blazing-fast performance with sub-millisecond latency and high throughput. Now, with Graviton2 M6g and R6g instances, customers can enjoy up to a 45% price/performance improvement over previous generation instances. Graviton2 instances are now the default choice for Amazon ElastiCache customers.

This week AWS launched Audit One-Click for AWS IoT Device Defender. Audit One-Click makes it easy for AWS IoT Core customers to improve their security baseline by making it possible to start auditing their account and IoT devices against security best practices with a single click.

This week, Amazon Elastic Container Registry (ECR) launched the ability to replicate specific repositories to accounts or regions, and see when images were replicated through the ECR API. This gives you granular control to replicate images within repositories you want, instead of replicating all images in a registry, and the ability to automate actions through the new DescribeImageReplicationStatus API  whenever images are replicated.

EMR Studio is an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug  big data and analytics applications written in R, Python, Scala, and PySpark. Today, we are excited to announce that from EMR 6.4.0 and later, you can use Python, Scala, SparkSQL, and R within the same Jupyter notebook in EMR Studio, providing flexibility to use different programming languages for Spark workloads.

Starting today, Amazon Lex  is available in the Asia Pacific (Seoul) and Africa (Cape Town) regions. Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex combines advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text. This enables you to build applications with engaging users experiences and lifelike interactions. With Amazon Lex, you can easily create sophisticated, natural language, conversational bots (“chatbots”), virtual agents and IVR systems.

Amazon Lex is a service for building conversational interfaces into any application using voice and text. Starting today, Amazon Lex makes utterances statistics available through the Amazon Lex V2 console and API. You can now use utterances statistics to tune bots built on Lex V2 console and APIs to further improve conversational experience for your users. With this launch, you can view and analyze utterance information processed by the bot. This information can be used to improve performance of your bot by adding new utterances to existing intents and helping you discover new intents that can be serviced by the bot. Utterances statistics also enable you to compare performance across multiple versions of a bot. 

Starting this week, you can use EC2 Fleet with targeted On-Demand Capacity Reservations. On-Demand Capacity Reservations enable you to reserve compute capacity for your Amazon EC2 instances in a specific Availability Zone for any duration. For targeted Capacity Reservations, instances must specifically target the Capacity Reservation to run in the reserved capacity. Until now, there was no option to use targeted Capacity Reservations when launching an EC2 Fleet.

AWS is announcing Licensing Accelerator, a new AWS Ground Station feature which provides commercial businesses, space start-ups, and universities access to resources to help them more efficiently secure spectrum licenses required for their operations and missions. Licensing accelerator is free-of-charge to AWS Ground Station customers. AWS Ground Station is a fully managed service that lets customers control satellite communications, process satellite data, and scale their satellite operations. With Licensing Accelerator, AWS Ground Station customers can launch and scale their spacecraft operations faster by leveraging the latest, centrally located information about satellite licensing regulations such as space station licensing, remote sensing licenses, and International Telecommunications Union (ITU) coordination.

AWS Single Sign-On is now available in the AWS GovCloud (US-West) Region. For a full list of the regions where AWS SSO is available, see the AWS Regional Services List.

You now can use AWS CloudTrail  to filter and retrieve Amazon DynamoDB Streams  data-plane API activity, giving you more granular control over which DynamoDB API calls you want to selectively log and pay for in CloudTrail and to help address compliance and auditing requirements.

Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning models based on your data, while allowing you to maintain full control and visibility. Starting today, SageMaker Autopilot generates additional metrics, along with the objective metric, for all model candidates. For binary classification problems, Autopilot now generates F1 score (harmonic mean of the precision and recall), accuracy, and AUC (area under the curve) for all model candidates. For multi-class classification, Autopilot now generates both F1 macro and accuracy for all model candidates. As previously supported, you can select any of these metrics as the objective metric to be optimized by your Autopilot experiment. By viewing additional metrics along with the objective metric, you can now quickly assess and compare multiple candidates to build a model that best meets your needs.

Amazon SageMaker announces a new set of capabilities that will enable interactive Spark based data processing from SageMaker Studio Notebooks. Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. With a single click, data scientists and developers can quickly spin up Studio Notebooks to interactively explore datasets and build ML models.

AWS have announced that in Amazon Forecast, you can now select the accuracy metric of your choice to direct AutoML to optimize training a predictor for the selected accuracy metric. Additionally, AWS have added three more accuracy metrics to evaluate your predictor – average weighted quantile loss (Average wQL), mean absolute percentage error (MAPE), and mean absolute scaled error (MASE).

Amazon Comprehend has launched a suite of features for Comprehend Custom  to enable continuous model improvements by giving developers the ability to create new model versions, to continuously test on specific test sets, and to migrate new models to existing endpoints. Using AutoML, custom entity recognition allows you to customize Amazon Comprehend to identify entities that are specific to your domain; custom classification enables you to easily build custom text classification models using your business-specific labels. Custom models can subsequently be used to perform inference on text documents, both in real-time and batch processing modes. Creating a custom model is simple - no machine learning experience required. Below is a detailed description of these features:

This week, AWS Site-to-Site VPN released an updated Download Configuration utility. With this update, Site-to-Site VPN customers can generate configuration templates for compatible Customer Gateway (CGW) devices, making it easier to create VPN connections to AWS. This update adds support for Internet Key Exchange version 2 (IKEv2) parameters for many popular CGW devices.

AWS Amplify offers a fully managed static web hosting service that accelerates your application release cycle by providing a simple CI/CD workflow for building and deploying full-stack static web applications. Simply connect your application's code repository in the console, and changes to your frontend and backend are deployed in a single workflow on every code commit.

This week, AWS announced the general availability (GA) of the Amazon GameLift Plug-in for Unity, making it easier to access GameLift resources and integrate GameLift into your Unity game. Trusted by some of the most successful game companies in the world like Ubisoft and Gungho, GameLift deploys, operates, and scales dedicated servers for multiplayer games. With this update, game developers can use the GameLift Plug-in for Unity to access GameLift APIs and deploy AWS CloudFormation templates for common gaming scenarios.

Amazon EMR Studio is an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug  data engineering and data science applications written in R, Python, Scala, and PySpark. Today, we are introducing additional authentication options with EMR Studio. Before this release, to login to EMR Studio, you needed to integrate your identity provider (IdP) with AWS Single Sign-on (AWS SSO). With this release, you can now choose to use AWS Identity and Access Management (IAM) authentication or use IAM federation with your corporate credentials to login to EMR Studio, in addition to using AWS SSO.

Amazon Detective expands security investigation support for Amazon Simple Storage Service (S3) and DNS-related findings on Amazon GuardDuty, providing full coverage of all detections from GuardDuty. Along with this, Detective now makes it even easier for a security analyst to investigate entities and behaviors using a revamped user experience. 

Amazon Connect Chat now supports passing a customer display name and contact attributes  through the chat user interface so you can personalize the chat customer experience. Contact attributes include relevant metadata associated with the contact such as customer ID, loyalty status, or even context about the webpage the customer was on when they started the chat. Contact attributes are available in Amazon Connect flows, making it easy to create unique and compelling customer experiences, such as prioritizing a platinum level customer or performing an agent screen pop with the relevant customer information displayed. In addition, you can also share the customer name using the chat user interface, ensuring that the name is visible to both the agent and customer throughout the interaction, enabling your agents to personalize the conversation.

AWS Elastic Beanstalk now supports dynamic instance type selection for Elastic Beanstalk’s environments. This means Elastic Beanstalk will automatically fetch all EC2 instance types based on region and availability zone for you to run a variety of applications. With dynamic instance type, you can choose the best suited instance type to optimize your application’s performance. For example, if you have machine learning applications, you can optimize performance by selecting an accelerated computing instance type such as p3, or p4d. On the Elastic Beanstalk console, you can navigate to the ‘Capacity’ tab in ‘Configure more options’ to select the instance type.

Amazon Redshift data sharing allows you to share live and transactionally consistent data across different Redshift clusters without the complexity and delays associated with data copies and data movement. Ability to share data across clusters that are in the same AWS account  is already available in AWS GovCloud(US) Regions. Now sharing data across Redshift clusters in different AWS accounts is also generally available in AWS GovCloud(US) Regions. Cross-account data sharing is supported on all Amazon Redshift RA3 node types. There is no additional cost to use cross-account sharing on your Amazon Redshift clusters.