In Cloud Computing This Week [Oct 21st 2022]

Customers in the AWS Asia Pacific (Jakarta) Region can now use Amazon FSx for Windows.

Amazon FSx makes it easy and cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Windows File Server provides fully managed, highly reliable file storage built on Windows Server and accessible via the industry-standard Server Message Block (SMB) protocol. 

Amazon Braket, the quantum computing service from AWS, aims to accelerate research and software development in quantum computing. This week, AWS are adding support for pulse-level access to superconducting quantum processors from Rigetti Computing and Oxford Quantum Circuits (OQC) by launching Braket Pulse, a new feature for running pulse-level quantum programs.

With this launch, Braket customers have more choice and can dive deeper in their research with the option to code their quantum programs using gates, pulses, or a combination of both.

To study and optimize the performance of today’s quantum computers, researchers often need access to the lowest level of control over the hardware in order to explore use cases such as studying noise or cross-talk, developing new and more robust gates, devising error mitigation schemes, and exploring novel quantum algorithms.

Braket Pulse enables customers to manipulate the low-level, analog signals or pulses, that control the qubits of a quantum processor. Customers can use Braket Pulse selectively within their gate-based quantum circuits by inserting blocks of pulse instructions in specific areas of the program to focus on optimizing individual operations and fine tune performance.

You can now view and filter the list of resources analyzed by Amazon DevOps Guru within the DevOps Guru console. You can view the list of resources on the ‘Analyzed resources’ page and sort and filter by resource name, DevOps Guru tag name (or tag value), CloudFormation stack name, or AWS Service name. You can optionally download the list via CSV file which also includes the Amazon Resource Names (ARN).  

Amazon DevOps Guru is an ML-powered service that makes it easier to improve an application’s operational performance and availability. By analyzing application metrics, logs, events, and traces, DevOps Guru identifies potential abnormal behaviors that deviate from normal operating patterns and creates an insight that alerts developers with issue details. When possible, DevOps Guru also provides potential remediation recommendations sent via Amazon Simple Notification Service (SNS), Amazon EventBridge, or partner integrations. 

To see the list of resources analyzed by DevOps Guru, you can navigate to the ‘Analyzed resources’ page from any of the following console locations:

• Click the ‘Analyzed resources’ link in the ‘System health summary’ at the top right of the Amazon DevOps Guru dashboard page.
• If you use CloudFormation stacks or tags, you can view a list of resources for a specific stack or tag by clicking on the ‘Analyzed resources’ link in the cards under ‘System health overview’.
• Click the ‘Analyzed Resources’ link on the left navigation pane of the DevOps Guru console.

Note that the option to edit or update resources analyzed by DevOps Guru is now under ‘Edit analyzed resources’ at the top of the Analyzed Resources page. 

Starting this week, AWS Service Management Connector for ServiceNow (version 4.7.5) enables customers to streamline the display of AWS Service Catalog portfolios and products by Account and Region in ServiceNow Service Portal. This feature enables ServiceNow Service Portal end users to identify and drill-down to the appropriate AWS Service Catalog product if they have access to shared portfolios from multiple accounts and regions.

Previously the drilldown feature was restricted to only portfolio names. This version also includes additional filter navigator modules for open incidents in AWS Systems Manager Incident Manager integration and displays timeline events as comments on the AWS incident in user-readable format. The AWS Support integration now introduces an optional configuration to create the support cases in an intermediate table for customers who want to leverage custom business workflows for managing support cases. The AWS Service Management Connector supports latest ServiceNow releases for Tokyo(T), San Diego(S) and Rome (R).

Customers can use the AWS Service Management Connector for ServiceNow to provision AWS resources and manage operations and incident response for AWS resources. ServiceNow administrators can configure the connector to work with new or existing AWS accounts, and associate one or more AWS accounts to ServiceNow.

The connector also provides integrations with AWS Service Catalog, AWS Config, AWS Health Dashboard, AWS Systems Manager OpsCenter, AWS Systems Manager Automation, AWS Systems Manager Incident Manager, AWS Change Manager Systems Manager, AWS Support and AWS Security Hub, which helps simplify cloud provisioning, operations and resource management as well as streamline Service Management governance and oversight over AWS services.

It’s easy to get started. The AWS Service Management Connector for ServiceNow is available at no charge in the ServiceNow Store. These new features are generally available in all AWS Regions where AWS Support, AWS Service Catalog, AWS Config, AWS Systems Manager, AWS Health Dashboard, AWS Systems Manager Incident Manager and AWS Security Hub services are available. For more information, please visit the documentation on the AWS Service Management Connector.

Amazon Relational Database Service (RDS) for MySQL, MariaDB and PostgreSQL now support 15 read replicas per instance, including up to 5 cross region read replicas, delivering up to 3X the previous read capacity.

Amazon RDS Read Replicas provide enhanced performance and durability for Amazon RDS database (DB) instances. They make it easy to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads.

You can create one or more replicas of a given source DB instance and serve high-volume application read traffic from multiple copies of your data, thereby increasing aggregate read throughput. For disaster recovery, read replicas can be promoted when needed to become standalone DB instances.

Using AWS IAM Identity Center (successor to AWS Single Sign-On), you now have more control over user session management. You can use the console to set customized session lengths (up to 7 days), based on your organization’s security requirements and desired end-user experience. With this feature, you can also terminate sessions, enabling you to manage sessions that are no longer needed or potentially suspicious.

Now, you can set the session duration between 15 minutes and 7 days (default 8 hours), enabling you to tune the duration in which signed-in users can access the AWS user portal and AWS accounts before authenticating again. In addition to supporting custom session durations up to 7 days, the new feature also enables you to look up active user portal sessions by user and terminate sessions as needed to remain secure against unwanted access.

For example, you can shut down sessions for recently terminated workforce members, sessions a user failed to sign out of on a second device, or sessions that you have determined have suspicious activity.

IAM Identity Center helps you securely create or connect your workforce identities and manage their access centrally across AWS accounts and applications. IAM Identity Center is the recommended approach for workforce authentication and authorization on AWS for organizations of any size and type.

The service is built on and included as part of AWS IAM at no additional cost in the AWS Regions listed here. To learn more about IAM Identity Center, see the feature page.

This week AWS announced up to 10x faster exports to Amazon S3 for snapshot exports for Amazon Aurora MySQL-Compatible Edition for MySQL 5.7 and 8.0. The performance improvement is automatically applied to all types of database snapshot exports, including manual snapshots, automated system snapshots, and snapshots created by the AWS Backup service.

With this capability, AWS customers can export data up to 10x faster from an Amazon Aurora database and store it in an Amazon S3 bucket using AWS CLI or AWS Management Console. After the data is exported, they can analyze the exported data using Amazon Athena and/or other tools and services. The export process runs in the background and doesn't affect the performance of active database instances.

Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services.

AWS Step Functions now provides a new console experience for viewing and debugging your Express Workflow executions that makes it easier to trace and root cause issues in your executions.

AWS Step Functions is a low-code, visual workflow service that developers can use to help build distributed applications, automate IT and business processes, and build data and machine learning pipelines using AWS services. Express Workflows are ideal for high-volume event processing workloads such as IoT data ingestion, streaming data processing and transformation, and high-volume microservices orchestration.

Now, Step Functions makes it easier to navigate through the details of your Express workflow executions in the AWS Console to identify issues, dive deeper into the context of a failure, and visually present information in a way that makes sense for you.

You can select from three different views for your workflow execution including a navigable workflow graph, a state transition table and the events table. You can search and filter your executions and the events in your executions using unique attributes such as state name and error type. Errors are now easier to root cause as the experience highlights the reason for failure in a workflow execution.

AWS Panorama customers can now remotely reboot their connected AWS Panorama Appliance from the AWS console or by using the AWS Panorama SDK. Before this launch, customers were only able to reboot Panorama Appliance by physically pressing the reboot button on the appliance.

As customers deploy Panorama Appliances across multiple sites, they want a scalable way to reboot the appliances from one central place. Remote reboot makes it easier for customers to recover from application or device issues and ensures high application uptime without needing to be physically present onsite. To learn more about Remote Reboot for AWS Panorama, click here.

AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision (CV) to on-premises internet protocol (IP) cameras. With AWS Panorama, customers can use compute power at the edge (without streaming video to the cloud) to improve their operations by automating visual inspection tasks like improving supply chain logistics, optimizing traffic management, and evaluating manufacturing quality.

Amazon Simple Queue Service (SQS) announces the general availability of an increased default quota for a high throughput mode for FIFO queues, allowing you to process up to 6,000 transactions per second, per API action in: US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Ireland), Europe (Frankfurt) regions. For Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo) regions, the default throughput quota has been increased to 3,000 transactions per second, per API action.

This is a twofold increase compared to the current SQS FIFO queue throughput quota. For a detailed breakdown of default throughput quotas per region, see SQS documentation.

Amazon SQS is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. Amazon SQS offers two types of message queues, standard and FIFO. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery.

FIFO queues support message groups to process distinct ordered message bundles and are designed to process messages only once, in the exact order that they are sent.

The increase of the default quotas for high throughput mode for FIFO queues enables customers to send and receive messages at a 2 times higher rate than was previously supported. The increased throughput quota makes it easy for developers to build applications that synchronously process a high volume of business-critical transactional data without writing complex error handling and message ordering code.

Example use cases include bank transaction logs, stock tickers, flight trackers, price updates, news broadcasting, and inventory management.

Getting started with the high throughput mode for FIFO queues is easy. Simply navigate to the Amazon SQS console and enable the high throughput FIFO option for either a new or existing FIFO queue. You can also enable it through the SQS API.

The high throughput mode for FIFO queues is available in all commercial and AWS GovCloud (US) Regions where Amazon SQS is available. To learn more about Amazon SQS FIFO queues, see the Amazon SQS FAQ and the Amazon SQS Developer Guide.

Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, you can quickly and easily build sophisticated, natural language, conversational bots (“chatbots”), virtual agents, and IVR systems. Today, Amazon Lex launches the FreeFormInput built-in slot type.

You can easily design bots to capture free form input from your customers. The new built-in slot type can recognize strings made up of words or characters. The resolved value is the complete free form entry provided by the user.

For example, following a phone conversation, you may need to collect the caller’s feedback. With the FreeFormInput built-in slot type, bot builders can easily capture commentary, which they can analyze later. The FreeFormInput slot type is available in all locales and regions where Lex operates. It can be accessed via both Lex V2 console and SDKs.

AWS Panorama customers can now pause and resume existing camera stream connections within applications deployed on the AWS Panorama Appliance using the AWS Panorama APIs. As customers deploy Panorama Appliances across multiple sites, they want a scalable way to manage individual camera streams without the overhead of a full application deployment.

Using this capability, customers can achieve failover between redundant camera streams, thereby meeting their high availability requirements. They can also dynamically swap between multiple camera streams to meet their business needs. To learn more, visit the AWS Panorama documentation.

AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision (CV) to on-premises internet protocol (IP) cameras. With AWS Panorama, companies can use compute power at the edge (without streaming video to the cloud) to improve their operations, by automating visual inspection tasks like improving supply chain logistics, optimizing traffic management, and evaluating manufacturing quality.

The AWS Panorama service is available in the US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Ireland), and Asia Pacific (Sydney and Singapore) regions. The AWS Panorama Appliance is available for purchase on Amazon.com, Amazon Business and AWS Elemental in the United States, Canada, Mexico, Australia, New Zealand, Singapore, New Zealand, Malaysia, United Kingdom, and the European Union.

Amazon Simple Email Service (Amazon SES) announces the launch of a new model of Dedicated IPs (managed) which helps customers to grow, manage and maintain their sending reputation via exclusive IP addresses without all of the heavy lifting associated with provisioning and managing dedicated IPs.

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.

Compared to using traditional shared IPs, leasing dedicated IPs is a common way to help increase delivery rate because it ensures customers are the sole exclusive sender and do not share their IPs with other senders. SES offers dedicated IP addresses for lease and customers pay for per IP address, which until today, required manual setup and management.

The new managed feature will help customers to quickly and easily provision dedicated IP addresses and maintain their sending reputation. The entire process of leasing, warming-up, scaling and managing email sending on exclusive IP addresses is all handled by Dedicated IPs (managed).

SES uses recent sending performance and historical forecast models to continuously re-adjust the sending volume and routing across the IP space with the goal of maximizing reputation and minimizing the impact of undelivered or bounced emails.

With this launch, customers are automatically provided with the correct amount of dedicated IPs that they require and complete the warmup quicker so that they don’t pay more than they need to and can start sending their email quickly. Dedicated IPs (managed) helps reduce the overheads associated with email sending via a dedicated IP.

Customers can access Dedicated IPs (managed) via the AWS console and public APIs. Customers can get started with dedicated IPs managed with one click in the console, and will be guided through the setup process to help them start sending quickly.

AWS GovCloud (US) enables U.S. government agencies and contractors to move more sensitive workloads into the cloud by addressing their specific regulatory and compliance requirements. By expanding AWS Control Tower to the AWS GovCloud (US) Regions, AWS Control Tower now provides customers on the GovCloud (US) Region and their partners the ability to architect their secure cloud solutions.

Due to the secure and regulated nature of the AWS GovCloud (US) Regions, certain AWS Control Tower functionality is different or may not be available in the AWS GovCloud (US) Regions. For details, please refer to the documentation on AWS Control Tower in GovCloud (US) Regions.

AWS Control Tower offers the easiest way to set up and govern a new, secure, multi-account AWS environment based on AWS best practices. To learn more, visit the AWS Control Tower homepage or see the AWS Control Tower User Guide. For a full list of AWS Regions where AWS Control Tower is available, see the AWS Region Table.

This week Amazon WorkDocs, a fully managed product for creating, sharing, and enriching digital content, announced the General Availability of an Apple Silicon (M1, M2) compatible WorkDocs Drive. Apple Silicon support for WorkDocs makes it easy for customers with Apple Silicon MacBooks to install and sync WorkDocs files on their devices.

Amazon WorkDocs Drive is a mounted drive that enables customers to open and work with Amazon WorkDocs files on their desktops. Customers can copy a shareable link, lock, unlock, or open a file in the web client with one click. WorkDocs Drive automatically syncs any changes made to Amazon WorkDocs and vice versa.

WorkDocs Drive is available to anyone with a WorkDocs subscription. For more information, see the Amazon WorkDocs web page. To get started with WorkDocs Drive, download the installer by visiting the Amazon WorkDocs Client Downloads page and selecting WorkDocs for Mac (Apple Silicon).

This week Amazon WorkDocs, a fully managed product for creating, sharing, and enriching digital content, announced the General Availability of an Apple Silicon (M1, M2) compatible WorkDocs Drive. Apple Silicon support for WorkDocs makes it easy for customers with Apple Silicon MacBooks to install and sync WorkDocs files on their devices.

Amazon WorkDocs Drive is a mounted drive that enables customers to open and work with Amazon WorkDocs files on their desktops. Customers can copy a shareable link, lock, unlock, or open a file in the web client with one click. WorkDocs Drive automatically syncs any changes made to Amazon WorkDocs and vice versa.

WorkDocs Drive is available to anyone with a WorkDocs subscription. For more information, see the Amazon WorkDocs web page. To get started with WorkDocs Drive, download the installer by visiting the Amazon WorkDocs Client Downloads page and selecting WorkDocs for Mac (Apple Silicon).

Amazon Connect Wisdom now delivers improved machine learning capabilities to continuously understand issues throughout a call and to deliver the right knowledge article to contact center agents. Wisdom analyzes contact center calls in real-time and proactively delivers agents the information they need to solve customer issues, improving agent productivity and caller satisfaction. 

With these enhancements that were developed after training machine learning models on hundreds of thousands of contacts, Wisdom is able to more accurately distinguish a caller's issue from the rest of the conversation and continuously detects new issues a caller may raise (for example, distinguishing pleasantries such as “we got a lot of snow this weekend” from weather-related issues such as “my flight was cancelled because of snow and I need to be re-booked”).

In addition, Wisdom's new machine learning models have a deeper, semantic understanding of the issues detected and how they relate to your organization's own knowledge articles (for example, if your knowledge articles only refer to “potential fraud” and a caller asks about or an agent manually searches for “unauthorized charge,” Wisdom can understand those terms refer to the same thing and return the most relevant article for the issue.). 

Amazon SageMaker Canvas announces Quick build support for time-series forecasting models, enabling faster prototyping and experimentation to select the best performing machine learning (ML) model. SageMaker Canvas is a visual point-and-click interface that enables business analysts to generate accurate machine learning (ML) predictions on their own — without requiring any machine learning experience or having to write a single line of code.

SageMaker Canvas allows you to train ML models through two different methods; 1/ Quick build that produces a trained model in less than 20 minutes, prioritizing speed over accuracy, and 2/ Standard build that produces a trained model in under 4 hours, prioritizing accuracy over latency after going through the complete ML cycle including pre-processing, feature engineering, and exploring the hyper-parameter space to select the best model.

Previously, ML models for time-series forecasting use cases in Canvas supported only Standard build models. Starting today, you can also use Quick build models to experiment rapidly, generate predictions, and validate hypotheses faster for time-series forecasting data.

This week, AWS are excited to announce the general availability of Amplify Library for Swift (previously Amplify iOS). This release allows Swift developers to easily build cloud-connected iOS apps. Since its Developer Preview release in April 2022, AWS have re-written their APIs to support idiomatic Swift features like async/await that makes it easier for developers to implement structured concurrency.

AWS also want to take this opportunity to introduce beta availability of macOS support--one of their most requested features--with watchOS and tvOS support coming in future releases. As with the Preview, the Amplify Library for Swift is open source on GitHub, and AWS deeply appreciate the feedback they have gotten from the community.

Starting this week, developers can use Amplify Library for Swift via the Swift Package Manager to build apps for iOS and macOS (currently in beta) platforms with Auth, Storage, Geo and more features. Developers will continue to have access to the same Command Line Interface (CLI) tools to configure and manage their cloud resources. With the Amplify Library for Swift, you will also have direct access to the underlying AWS SDK for Swift through the escape hatch to unlock additional capabilities from AWS services.

AWS are announcing the launch of Red Hat Enterprise Linux (RHEL) Workstation for accelerated GPU instances on AWS Marketplace. RHEL Workstation is a cloud-based remote desktop solution that allows end users from anywhere in the world to access a workstation instance to do their work and collaborate with team members.

RHEL Workstation is designed for advanced Linux users working on more powerful hardware, and is optimized for activities such as animation, computer-aided design and engineering, scientific research, medical imaging etc. It is delivered via NICE DCV, a secure, high-performance remote display protocol.

RHEL Workstation on AWS allows customers to provide high-end hardware capabilities to a distributed workforce, without the need for large capital investments in expensive workstation equipment.

The RHEL Workstation Amazon Machine Images (AMIs) are built on RHEL version 8.6 with NICE DCV remote display software and support both Tesla and GRID NVIDIA drivers. RHEL Workstation is available on AWS Marketplace for GPU Accelerated instance families including the G3, G4dn, G5, P2, and P3 instances for Tesla drivers and G3, G4dn, G5, and P3 instances for GRID drivers.

RHEL Workstation is now available in all AWS Commercial regions, and AWS provides tier 1 and tier 2 support for this product. To get started, search for RHEL Workstation on AWS Marketplace or in the EC2 console AMI Catalog. 

AWS announced an enhanced Snowball Edge Compute Optimized with expanded compute, memory and storage options. The AWS Snowball Edge Compute Optimized device doubled the compute capacity up to 104 vCPUs, doubled the memory capacity up to 416GB RAM, and is now fully SSD with 28TB NVMe storage.

AWS Snowball Edge Compute Optimized is a secure, rugged device that brings AWS computing and storage capabilities, such as Amazon EC2, Amazon EBS, Amazon S3, AWS IoT Greengrass, AWS Lambda functions, and AWS IAM to your rugged edge environments.

AWS Snowball Edge is available in two device types. Snowball Edge Compute Optimized with more computing capabilities, suited for higher performance workloads, and Snowball Edge Storage Optimized with more storage, which is suited for large-scale data migrations and capacity-oriented workloads.

You can use Snowball Edge devices in environments with intermittent connectivity (like manufacturing, industrial, and transportation) or in extremely remote locations (like military or maritime operations). Snowball Edge Compute Optimized capabilities now include double the available compute to 104 vCPUs and 416GB RAM with an all SSD (28TB NVMe) storage architecture for Amazon S3 compatible object storage or EBS-compatible block volumes.

The updated Snowball Edge Compute Optimized device is ideal when you need dense compute resources to run complex workloads such as AI/ML inference, video analytics, or to deploy private 5G wireless networks at the rugged, mobile edge, and in high-vibration environments on mobile platforms such as trucks, aircraft or ships.

Amazon Interactive Video Service (Amazon IVS) now provides SDKs for stream chat with support for web, Android and iOS. The Amazon IVS stream chat SDKs support common functions for chat room resource management, sending, and receiving messages, and managing chat room participants.

Visit the Amazon IVS chat documentation to learn more. Using the Amazon IVS stream chat SDKs incurs no additional charges beyond standard Amazon IVS usage costs.

Amazon IVS stream chat is built for large scale, real-time messaging conversations and handles the natural variation in message volume without customers needing to manage the underlying infrastructure. With this feature, customers can build chat into their web and mobile applications to drive engagement with thousands of users at once.

Amazon Interactive Video Service (Amazon IVS) is a managed live streaming solution that is designed to be quick and easy to set up, and ideal for creating interactive video experiences. Send your live streams to Amazon IVS using the broadcast SDKs or standard streaming software such as Open Broadcaster Software (OBS) and the service is designed to provide everything you need to make low-latency live video available to any viewer around the world, letting you focus on building interactive experiences alongside the live video.

Amazon Elastic File System (Amazon EFS) is now available in the Middle East (UAE) Region.

Amazon EFS is a serverless, fully elastic file system that makes it easy to set up, scale, and cost-optimize file storage in the AWS Cloud. It is built to scale on demand to store petabytes of data, growing and shrinking automatically as you add and remove files, eliminating the need to provision and manage capacity to accommodate growth.

Amazon RDS for PostgreSQL 15 Release Candidate 2 (RC2) is now available in the Amazon RDS Database Preview Environment, allowing you to test the release candidate of PostgreSQL 15 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 15 RC2 for development and testing in the Amazon RDS Database Preview Environment without the hassle of installing, provisioning, and managing the database. 

The PostgreSQL community released PostgreSQL 15 RC2 on October 6, 2022. New features in PostgreSQL 15 RC2 include the SQL standard "MERGE" command for conditional SQL queries, performance improvements for both in-memory and disk-based sorting, and support for two-phase commit and row/column filtering for logical replication. The PostgreSQL 15 RC2 release also adds support for server-side compression with Gzip, LZ4, or Zstandard (zstd) using pg_basebackup. Please refer to the PostgreSQL community announcement for more details about the release.

The Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes, and can be encrypted at rest using KMS keys. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use standard PostgreSQL dump and load functionality to import or export your databases from the preview environment.

On October 18th, 2022 Amazon announced quarterly security and critical updates for Amazon Corretto Long-Term Supported (LTS) versions of OpenJDK. Corretto 19.0.1, 17.0.5, 11.0.17, 8u352 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK.

Click on the Corretto home page to download Corretto 8, Corretto 11, Corretto 17, or Corretto 19. You can also get the updates on your Linux system by configuring a Corretto Apt or Yum repo. 

This week, AWS are excited to announce the second release of FreeRTOS Long Term Support (LTS) - FreeRTOS 202210.00 LTS. This release includes new libraries such as AWS IoT Fleet Provisioning and Cellular LTE-M Interface for easier device provisioning and cellular connectivity. It also includes coreMQTT and FreeRTOS-Plus-TCP libraries with improved modularity and robustness.

All libraries included in this FreeRTOS LTS version, summarized in this post, will receive security and critical bug fixes until October 2024. With an LTS release, you can continue to maintain your existing FreeRTOS code base and avoid any potential disruptions resulting from FreeRTOS version upgrades.

Similar to the previous FreeRTOS LTS release, FreeRTOS 202210.00 LTS includes libraries that have been validated for memory safety with the C Bounded Model Checker (CBMC) automated reasoning tool to help mitigate code security issues such as buffer overflow.

In addition, all LTS libraries have undergone certain code quality checks including MISRA-C compliance and Coverity static analysis to help improve code safety, portability, and reliability in embedded systems (see LTS Code Quality Checklist).

The support period for the previous LTS release will end on March-2023, providing you a six-month overlap between the LTS releases for easy migration of your project. See the migration guide and corresponding validation tests to upgrade your project to FreeRTOS 202210.00 LTS.

If you prefer not to upgrade and want to continue receiving critical fixes on the previous LTS version beyond its expiry, you can consider the FreeRTOS Extended Maintenance Plan.

AWS Database Migration Service (AWS DMS) now supports Amazon EC2 C6i and R6i instance types. These instances are powered by 3rd Generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.5 GHz, offering up to 15% better compute price performance over comparable Generation5 instances for a wide variety of workloads, and always-on memory encryption using Intel Total Memory Encryption (TME).

Designed for a wide variety of workloads, C6i and R6i instances are built on the AWS Nitro System, a combinationof dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances.

C6i instances are an ideal fit for compute-intensive workloads and R6i instances are an ideal fit for memory intensive workloads. To meet customer demands for increased scalability, these instances provide new 32xlarge size with 128 vCPUs, 33% more than the largest Generation5 instance. They also give customers up to 50 Gbps of networking speed and 40 Gbps of bandwidth to the Amazon Elastic Block Store, twice that of Generation5 instances.

This week, AWS are excited to announce support to refit transforms with Amazon SageMaker Data Wrangler. To make data usable by algorithms such as XgBoost, data scientists must transform non-numeric values to numeric values using transforms such as one-hot encoding.

Since transforms like one-hot encoding depend on the data, these transforms are frequently referred to as fitted transforms. These transforms must be updated or re-fitted to account for changes in the data as data continues to change over time. Additionally, when working on a sample data set, transforms must be updated to account for changes between a sample data set and the larger data set.

Use of transforms like one-hot encoding generates additional information, which needs to be tracked and captured in the data preparation pipeline. Omitting or incorrectly tracking this information can lead to errors in the data preparation process.

Without support to refit transforms, many data scientists did not have an easy way to specify when to use a fitted version of a transform or to refit their transform on new data. Data scientists also lacked an easy way to generate updated versions of their transformation pipelines when refitting on new datasets. 

Data Wrangler now tracks fitted transforms in data flows for all applicable transforms. These fitted transforms can now be used to more easily prepare new data as required. Users can specify when they want to re-use transforms or refit new transforms on their data.

The refit feature is available both in the Data Wrangler visual interface when launching a Data Wrangler processing job and also within the create job notebook. Simply select “refit” under “trained parameters” in the create job workflow to refit transforms in your flow. Data Wrangler will also automatically generate a new flow file containing updated values for refit transforms.

AWS IAM Identity Center (successor to AWS Single Sign-On) now supports higher default quotas to help you scale your environment. With the increased quota you can create and assign up to 2,000 permission sets in an Identity Center instance.

You can also assign up to 100,000 users and 100,000 groups to as many as 3,000 applications and accounts (combined) that are accessible via the AWS access portal.

Starting this week, increased default quota’s for IAM Identity Center are available in all regions where IAM Identity Center is supported.

Remote functions, which let you invoke functions from Cloud Functions or Cloud Run in your Google Standard SQL queries, are now generally available (GA).

• Update cloud client dependencies (#2335) (f8053d7)
• Update cloud client dependencies (#2337) (1194eac)
• Update dependency com.google.api.grpc:proto-google-cloud-bigqueryconnection-v1 to v2.5.6 (#2336) (a86c759)

Support for Eventarc triggers for Workflows is generally available (GA).

Generally available: SFTP support for Azure Blob Storage

Azure Blob Storage now supports provisioning an SFTP endpoint with just one click.

General availability: Azure Premium SSD v2 Disk Storage

Premium SSD v2 is the next generation Azure Premium SSD Disk Storage. It offers the most advanced general-purpose block storage solution with the best price-performance.

General availability: OpenTelemetry exporter for Azure Data Explorer

Azure Data Explorer now supports ingestion of data from many receivers via the OpenTelemetry exporter.

General availability: Stream Analytics no-code editor in Event Hubs

Stream Analytics no-code editor enables you to develop a Stream Analytics job in minutes with drag and drop experience. Now, it is generally available with several new capabilities added.

Generally available: Auto Extension upgrade for Arc enabled Servers

Azure Arc can now provide high availability and automatic protection against zero-day or critical vulnerabilities in Azure extensions to your Arc enabled Servers

General availability: Azure savings plan for compute

This week, Microsoft are officially announcing the general availability for Azure savings plan for compute.

General availability: Zone-redundant storage support by Azure Backup

Azure Backup enables you to configure cost-efficient backups while meeting your data residency requirements.

Public preview: Exactly once delivery for Azure Data Lake Storage Gen2

Stream Analytics now supports end-to-end exactly once semantics when writing to Azure Data Lake Storage Gen2.

Generally available: Azure Stream Analytics in one new region Qatar Central

Azure Stream Analytics is a fully managed, real-time analytics service designed to help you analyze and process fast moving streams of data.