12/8/2022, 12:00:00 AM ~ 12/9/2022, 12:00:00 AM (UTC)

Recent Announcements

AWS IoT TwinMaker launches asset synchronization with AWS IoT SiteWise

Starting today, AWS IoT TwinMaker will support asset synchronization with AWS IoT SiteWise, making it easier for AWS IoT SiteWise customers to bring their assets and asset models into AWS IoT TwinMaker.

Amazon EC2 Auto Scaling now supports Metric Math for Target Tracking Policies

EC2 Auto Scaling customers can now use Amazon CloudWatch Metric Math to customize the metrics they use with Target Tracking policy without actually having to publish and pay for customized metrics. Customers can use both arithmetic operators (such as +, -, /, and *) and mathematical functions (such as Sum and Average) to easily create custom metrics based on existing CloudWatch metrics. Target Tracking, like other EC2 Auto Scaling policies, helps customers maintain high availability while reducing costs by auto scaling their environments to meet changing demand. Specifically, Target Tracking works like a thermostat: it constantly changes the capacity of an Auto Scaling group to maintain the specified metric at a customer-defined target level. Today’s release makes it easier and cheaper to configure Target Tracking with custom metrics.

AWS Systems Manager Change Manager now displays AWS CloudTrail events associated with change requests

Starting today, customers can view AWS CloudTrail event logs of a change request using AWS Systems Manager Change Manager. The feature helps customers understand which resources were impacted by the change request which provides customers with more visibility into the change request process. Change Manager already helps customers request, approve, implement, and report on operational changes to their application configuration and infrastructure on AWS and on-premises. With this launch, customers can now get the CloudTrail events associated with the change requests within the Change Manager console which offers them more visibility into their changes. For example, if a change was made to restart an EC2 instance, customers can now see which instances were actually impacted as part of the execution and the APIs that were invoked.

AWS Cost Management introduces 1-click experience to refresh Savings Plans Recommendations

AWS Cost Management now offers a 1-click experience to refresh Savings Plans Recommendations, so you can generate new Savings Plans Recommendations at any time to reduce costs and accelerate your cloud optimization journey. Savings Plans is a flexible pricing model offering lower prices compared to On-Demand pricing, in exchange for a specific usage commitment (measured in $/hour) for a one or three-year period.

Amazon RDS Proxy now supports creating proxies in Aurora Global Database primary and secondary regions

Amazon RDS Proxy, a fully managed, highly available database proxy for Amazon Relational Database Service (RDS), now supports creating proxies in Amazon Aurora Global Database primary and secondary regions. An Aurora Global Database is a single database that spans multiple AWS regions, enabling low latency global reads and disaster recovery from region-wide outages. With today’s launch, you can use RDS Proxy to make your applications more scalable, more resilient to database failures, and more secure in both the primary and secondary Global Database regions.

AWS Cost Anomaly Detection adds account name and other important details to its alert notifications

We are pleased to announce that as of today, customers will see additional details in AWS Cost Anomaly Detection’s console, alerting emails, and SNS topics posted to Slack and Chime. AWS Cost Anomaly Detection is a cost management service that leverages advanced machine learning to identify anomalous spend and root causes, so customers can quickly take action to avoid runaway spend and bill shocks. With this launch, customer can spend less effort trying to understand what account and monitor is tied to a cost anomaly, which in turn helps them take necessary actions more quickly.

Amazon VPC IP Address Manager (IPAM) is now available in the AWS GovCloud (US) Regions

Amazon VPC IP Address Manager (IPAM) is now available in both AWS GovCloud (US) Regions. VPC IPAM makes it easier for you to plan, track, and monitor IP addresses for your AWS workloads.

AWS Config enables drift detection in Config Recorder

AWS Config now supports configuration recorder as a configuration item. Configuration recorder must be enabled before AWS Config can detect changes to your resource configurations and capture these changes as configuration items. With this launch, you can now monitor configuration changes to the configuration recorder in your AWS account.

Amazon SageMaker Data Wrangler now supports Amazon EMR Presto as a big data query engine

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface. Starting today, you can connect to Amazon EMR Presto as a big query engine to bring in very large dataset, and prepare data for ML in minutes in Data Wrangler visual interactive.

Amazon Kinesis Data Firehose now delivers to Logz.io

Amazon Kinesis Data Firehose now supports streaming data delivery to Logz.io, enabling Logz.io users to ingest streaming metrics and logs without having to manage applications or write code.

Amazon QuickSight supports billion-row dataset with SPICE

Amazon QuickSight now supports even larger SPICE datasets on the Enterprise Edition. Today, all new SPICE datasets can accommodate up to 1 billion rows (or 1TB) of data in the Enterprise Edition and 25 million rows (or 25GB) for Standard Edition. Before the launch, each SPICE dataset could hold up to 500 million rows and 500GB of data. Customers who want to use QuickSight’s rich visualizations to explore very large datasets had to rely on data engineers to manually orchestrate data between QuickSight and another data store, which made it challenging to access and analyze very large datasets quickly. With billion-row support in SPICE, it’s easier to connect to data stores and ingest data into SPICE. Users now have greater autonomy to visually analyze large datasets directly in QuickSight, without coordinating with engineering teams to manually orchestrate data among services. See here for details.

YouTube

AWS Developer Live Show (Japanese)

AWS Blogs

AWS Japan Blog (Japanese)

AWS Big Data Blog

Containers

AWS Database Blog

Front-End Web & Mobile

AWS HPC Blog

AWS for Industries

AWS Machine Learning Blog

Networking & Content Delivery

AWS Security Blog

Open Source Project

AWS CLI

Karpenter