10/17/2024, 12:00:00 AM ~ 10/18/2024, 12:00:00 AM (UTC)
Recent Announcements
Amazon DataZone launches support for AWS IAM Identity Center account instance
Today, Amazon DataZone announced support for account instances of AWS IAM Identity Center. Amazon DataZone administrators can now setup single sign-on (SSO) users through AWS IAM Identity Center without needing to have an organization configured through AWS Organizations.\n As an Amazon DataZone administrator, you can now enable AWS IAM Identity Center for a single AWS account instead of the entire AWS organization. When creating an Amazon DataZone domain, choose to enable AWS IAM Identity Center for a single AWS account. With the account instance option, decide whether to allow all authorized AWS IAM Identity Center users and groups access to the domain or explicitly assign them. For example, an AWS account administrator, who doesn’t have access to the management account for their organization and needs to set up SSO access, can provide access to the Amazon DataZone portal for individual users or groups in that AWS account. Amazon DataZone support of AWS IAM Identity Center account instance is available in all AWS Regions where Amazon DataZone is available. To learn more, visit Amazon DataZone, and get started with AWS IAM Identity Center account instance documentation.
Amazon DynamoDB announces user experience enhancements to organize your tables
Amazon DynamoDB is excited to announce enhancements to the DynamoDB console that enable customers to easily find frequently used tables. Now, customers can favorite their tables in the console’s tables page for quicker table access.\n Customers can click the favorites icon to view their favorited tables in the console’s tables page. With this update, customers have a faster and more efficient way to find and work with tables that they often monitor, manage, and explore. The favorite tables console experience is now available in all AWS Regions at no additional cost. Customers can start using favorite tables immediately. Get started with creating a DynamoDB table from the AWS Management Console.
Amazon Aurora PostgreSQL now supports local write forwarding
Amazon Aurora PostgreSQL-Compatible Edition now lets you forward write requests from Aurora read replicas to the writer instance, simplifying scaling read workloads that require read-after-write consistency. With this launch, local write forwarding is now available for both Aurora MySQL and Aurora PostgreSQL.\n With write forwarding, your applications can simply send both read and write requests to a read replica, and Aurora will take care of forwarding the write requests to the writer instance in your cluster. This way your applications can scale read workloads on Aurora Replicas without the need to maintain complex application logic to separates reads from writes. You can also select from different consistency levels to meet your application read-after-write consistency needs. Local write forwarding is supported on Aurora PostgreSQL versions 14.13, 15.8, 16.4 or higher. You can enable the feature using the AWS Management Console, Command Line Interface (CLI), or API by turning on the “local write forwarding” option. See our documentation to learn more. Amazon Aurora combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. To get started with Amazon Aurora, take a look at our getting started page.
Amazon Relational Database Service (Amazon RDS) Multi-AZ deployments with two readable standbys now supports using AWS Identity and Access Management (IAM) for database authentication. With IAM support, you can now centrally manage access to your RDS Multi-AZ deployments with two readable standbys along with other RDS deployments, instead of managing access individually. In addition, AWS IAM eliminates the need for storing password-based login credentials in the database.\n Amazon RDS Multi-AZ deployments with two readable standbys is ideal when your workloads require lower write latency and more read capacity. This deployment option also supports minor version upgrades and system maintenance updates with typically less than one second of downtime when using Amazon RDS Proxy or open source tools such as AWS Advanced JDBC Driver, PgBouncer, or ProxySQL. To learn more about IAM authentication support, see settings for creating Multi-AZ DB clusters in the Amazon RDS User Guide. For a full list of the Amazon RDS Multi-AZ with two readable standbys regional availability and supported engine versions, see supported Regions and DB engines for Multi-AZ DB clusters in Amazon RDS in the Amazon RDS User Guide. You can create or update fully managed Amazon RDS Multi-AZ databases with two readable standby instances in the Amazon RDS Management Console.
Ubuntu Pro for EC2 Spot Instances
Starting today, you can launch Amazon EC2 Spot Instances using Ubuntu Pro based Amazon Machine Images (AMIs). You can now easily deploy Ubuntu Pro Spot instances and get five additional years of security updates from Canonical. You will be charged on a per-second basis for Ubuntu Pro EC2 AMI instances. For any new Ubuntu Pro EC2 AMI deployments, you will now see Ubuntu Pro charges in the Elastic Compute Cloud section of your AWS bill.\n Amazon EC2 Spot Instances let you take advantage of unused EC2 capacity available in the AWS cloud. Spot Instances are available at up to a 90% discount compared to On-Demand prices. You can use Spot Instances for various stateless, fault-tolerant, or flexible applications such as big data, containerized workloads, CI/CD, web servers, high-performance computing (HPC), and other test & development workloads. Spot Instances are easy to launch, scale, and manage through AWS services like Amazon ECS and Amazon EMR, or integrated third parties like Terraform and Jenkins. Spot Instances can be launched via RunInstances API with a single additional parameter. You can also provision compute capacity across Spot Instances, RIs, and On-Demand instances to optimize performance and cost using EC2 Fleet and Auto Scaling Groups APIs. To learn more about Amazon EC2 Spot Instances, visit Amazon EC2 Spot page or technical documentation.
AWS Lambda console now supports real-time log analytics via Amazon CloudWatch Logs Live Tail
The AWS Lambda console now supports Amazon CloudWatch Logs Live Tail, an interactive log streaming and analytics capability which provides real-time visibility into logs, making it easier to develop and troubleshoot Lambda functions.\n Customers building serverless applications using Lambda want visibility into the behavior of their Lambda functions in real time. For example, developers want to instantly see the result of their code or configuration changes, and operators want to quickly troubleshoot any critical issues which would prevent the function from operating smoothly. Previously, you had to visit the CloudWatch console to access detailed Lambda function logs or real-time log streams. Now, with Live Tail in Lambda console, you can view and analyze Lambda logs in real time as they become available. This makes it easier for developers to quickly test and validate code or configuration changes in real time, accelerating the author-test-deploy cycle (also known as the “inner dev loop”) when building applications using Lambda. The Live Tail experience also makes it easier and faster for operators and DevOps teams to detect and debug failures and critical errors in Lambda function code, reducing the mean time to recovery (MTTR) when troubleshooting Lambda function errors. To get started, visit the Lambda console and click “Open CloudWatch Live Tail” button in the code editor. To learn more, visit the launch blog post and Lambda developer guide. The Live Tail experience in Lambda console is available in all commercial AWS Regions where Lambda and CloudWatch Logs are available. For more information, see the AWS Region table.
The AWS Lambda console now surfaces key metrics about Lambda functions in your AWS account via a built-in Amazon CloudWatch Metrics Insights dashboard, enabling you to easily identify and troubleshoot the source of errors or performance issues.\n To efficiently operate distributed serverless applications built using Lambda, it is crucial to easily identify the source of errors or performance anomalies, such as spike in critical metrics like errors or invocation duration for Lambda functions in your AWS account. Previously, you had to navigate to CloudWatch console and query metrics or create custom dashboards, which caused context switching and added friction for operators and DevOps teams to effectively monitor and optimize Lambda-based applications. Now, the Lambda console features a new built-in dashboard, which leverages CloudWatch Metrics Insights capability and provides you with instant visibility into the following critical insights — most-invoked Lambda functions, functions with highest number of errors, and functions taking the longest to run. This reduces friction due to context switching and enables your operator teams to easily identify and fix the source of errors or performance anomalies without leaving the Lambda console. To get started, simply navigate to the “Dashboard” page in the Lambda console to access the insights surfaced by Metrics Insights dashboard. To learn more, visit the launch blog post. The Metrics Insights dashboard in Lambda console is available in all commercial AWS Regions where Lambda and CloudWatch metrics are available, including the AWS GovCloud (US) Regions, at no additional cost. For more information, see the AWS Region table.
QuickSight now supports subfolders in restricted folders to enable governed data sharing
Amazon QuickSight now supports subfolders in restricted folders for asset organization and permissions management. QuickSight assets created in restricted folders and subfolders cannot be removed from the folder tree, creating a data sharing boundary. Enterprise administrators can deploy restricted folders and subfolders to govern sharing of data in business intelligence assets across their organization. With this launch, users with the folder Contributor permission can create content in restricted folders and subfolders but cannot manage permissions on folders and assets contained in the restricted folder. Additionally, administrators can now use the QuickSight RestoreAnalysis API to restore deleted analyses into a restricted folder.\n Users with the Contributor permission can create content in restricted folders and subfolders. Administrators can set Viewer and Contributor permissions for users and groups on folders and subfolders. This enables a subset of content to be shared with specific users. For example, data sources can be created in a restricted subfolder with Viewer permissions for analysts. They can use these data sources to create Datasets, Topics and Analyses in another subfolder where they have Contributor permissions. Dashboards can be published in another subfolder where a broader audience of business users have the Viewer permission. Restricted folder subfolders and the RestoreAnalysis to folder API are available in all AWS Regions where Amazon QuickSight is available. To learn more, see Organizing assets into folders for Amazon QuickSight.
AWS Blogs
AWS Japan Blog (Japanese)
- How to walk on a cloud journey (Part 2)
- NICE DCV is now Amazon DCV with 2024.0 release
- AWS Console-to-Code is now generally available to convert AWS console actions into reusable code
AWS Cloud Operations Blog
AWS Big Data Blog
- Get started with Amazon DynamoDB zero-ETL integration with Amazon Redshift
- Elevate your search and analytics skills with the new Amazon OpenSearch Service YouTube channel
- Migrate from Amazon Kinesis Data Analytics for SQL to Amazon Managed Service for Apache Flink and Amazon Managed Service for Apache Flink Studio
AWS Compute Blog
AWS Database Blog
Desktop and Application Streaming
AWS HPC Blog
The Internet of Things on AWS – Official Blog
AWS Machine Learning Blog
- Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations
- Use Amazon SageMaker Studio with a custom file system in Amazon EFS
- Summarize call transcriptions securely with Amazon Transcribe and Amazon Bedrock Guardrails