11/21/2023, 12:00:00 AM ~ 11/22/2023, 12:00:00 AM (UTC)
Recent Announcements
AWS Lake Formation data filters now support permissions on nested data
AWS Lake Formation now allows customers to apply permissions on subfields of their nested tables using data filters. Permissions can be granted on more granular fields such as on particular columns inside of structs. Permissions on nested fields provide customers more fine grained permissions to better match their business needs with greater flexibility to how they structure their data.
Amazon QuickSight supports SPICE capacity auto-purchase
Amazon QuickSight is excited to announce the launch of SPICE capacity auto-purchase feature, offering an improved solution for the automatic management of SPICE capacity. Previously, customers had to manually purchase SPICE capacity, and insufficient capacity could lead to data ingestion failures, hindering the intended use of QuickSight. Now, customers can effortlessly opt in to the capacity auto-purchase with just one click. This new SPICE auto-purchase capability eliminates the need for customers to estimate usage and manually purchase SPICE capacity each time. Instead, they can seamlessly ingest data and use SPICE worry free, as QuickSight will automatically acquire the necessary capacity to meet their usage requirements. For further details, visit here.
Amazon CloudFront announces CloudFront KeyValueStore, a globally managed key value datastore
Amazon CloudFront announces general availability of CloudFront KeyValueStore, a global, low-latency, key value datastore. KeyValueStore allows you to retrieve key value data from within CloudFront Functions making functions more customizable by allowing independent data updates. The key value data is available across all CloudFront edge locations and provides a highly efficient, in-memory, key-value store with fast reads from within CloudFront Functions. With KeyValueStore you can now implement lookup use cases such as feature flags, A/B testing, and storing environment variables with low latency.
Amazon Verified Permissions now provides an enhanced visual mode for schema editing
Amazon Verified Permissions now provides customers with a new visual schema editor, in addition to the existing JSON editor, in the Verified Permissions console. Customers can now visualize the relationships between the entities used to model principals, resources and actions.
AWS announces Amazon DocumentDB I/O-Optimized
Today, we are announcing the general availability of Amazon DocumentDB (with MongoDB compatibility) I/O-Optimized, a new storage configuration for database clusters that provides improved price performance and predictable pricing for customers with I/O-intensive applications. Amazon DocumentDB I/O-Optimized offers improved performance, increasing write throughput and reducing latency for customers’ most demanding workloads. With Amazon DocumentDB I/O-Optimized, there are zero charges for read and write I/O operations—you only pay for your database instances and storage usage, making it easy to predict your database spend up front. Amazon DocumentDB I/O-Optimized offers up to 40% cost savings for I/O-intensive applications where I/O charges exceed 25% of the total Amazon DocumentDB database spend.
Amazon DocumentDB now supports no-code machine learning with Amazon SageMaker Canvas
Amazon DocumentDB (with MongoDB compatibility) now integrates with Amazon SageMaker Canvas to enable no-code Machine learning (ML) with data stored in Amazon DocumentDB. Customers can now build ML models for regression and forecasting needs and use foundation models for content summarization and generation using data stored in Amazon DocumentDB without writing a single line of code. The new integration removes the undifferentiated heavy lifting when customers connect and access data in Amazon DocumentDB and accelerates ML development with a no-code experience.
Amazon S3 server access logging now supports automatic date-based partitioning
Amazon S3 server access logging now supports automatic date-based partitioning for log delivery. Amazon S3 server access logging provides detailed records for requests made to your S3 buckets including object size, total time, turn-around time, HTTP referer, and more. Now, with date-based partitioning, Amazon S3 automatically generates either event time or delivery time prefixes when delivering access logs to your destination bucket, which allows services like Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum to improve performance and reduce cost when querying logs.
Amazon Elastic Block Store announces io2 Block Express volumes available on all EC2 Nitro instances
Today, Amazon Elastic Block Store (EBS) announced that io2 Block Express volumes are available on all EC2 instances built on the Nitro system. All new io2 volumes used with EC2 Nitro instances will automatically benefit from the latest generation of EBS storage server architecture designed to deliver consistent sub-millisecond latency and 99.999% durability. With a single io2 Block Express volume, customers can achieve 256,000 IOPS, 4GB/s of throughput, and storage capacity of 64 TiB. io2 Block Express has the lowest p99.9 I/O latency and the best outlier latency control among major cloud providers, making it the ideal choice for the most I/O-intensive, mission-critical deployments of SAP HANA, Oracle, Microsoft SQL Server, and IBM DB2.
AWS Amplify launches next generation of backend building capabilities
Today, AWS Amplify announces a public preview of its code-first developer experience (Gen 2), enabling developers to build full-stack apps using TypeScript. Gen 2 shifts to a code-first approach that allows developers to express app requirements - data model, business logic, authorization rules - in TypeScript. The necessary cloud infrastructure is automatically deployed based on the app code, without explicit infrastructure definitions.
Apache Flink is now generally available for Amazon EMR on EKS
Today, we are excited to announce that Apache Flink is now generally available for Amazon EMR on EKS. With Apache Flink for Amazon EMR on EKS, customers can transform and analyze streaming data in real time with Apache Flink, an open-source framework for stateful computations over data streams. Amazon EMR on EKS is a deployment option for Amazon EMR that makes it easy for customers to run their big data applications and data lake analytics workloads on EKS. Customers already using Amazon EKS can run their Apache Flink application along with other types of applications on the same Amazon EKS cluster, helping improve resource utilization and simplify infrastructure management.
EC2 Image Builder now supports image lifecycle management and deletion
Customers can now manage the lifecycle of their custom Amazon Machine Images (AMIs) and Container images created on EC2 Image Builder. Customers can save costs by deleting unused images that accumulate storage charges on AWS. You no longer have to keep track of their custom images distributed across AWS accounts and AWS regions, and manually retire them as the images become outdated. With this launch, we provide customers an automated way to identify and remove outdated images, avoiding accidental usage of those images.
Customers can now launch their Amazon EMR on EC2 clusters in 5 minutes or less
Today, we are excited to announce that Amazon EMR has made it up to 35% faster, year on year, to launch an Amazon EMR on EC2 cluster. With these improvements, majority of the customer can launch their Amazon EMR on EC2 clusters in 5 mins or less.
AWS Blogs
AWS Japan Blog (Japanese)
- Reduce Microsoft SQL Server licensing costs with AWS Compute Optimizer
- [Event Report] Practice on AWS! Analytics Stories ~Case Study Festival~
- Best Practice: Managing Call Recordings with Amazon Connect
- Take full advantage of integrated business intelligence with Google Cloud BigQuery and Amazon QuickSight
- AWS re:Invent 2023 Amazon EKS and Kubernetes session guide
- Amazon Mexico FP&A Uses QuickSight for Financial Analysis
- Providing intuitive, high-performance business intelligence to Amazon solution architects
- Large Database Backup and Restore Strategies for Amazon RDS for SQL Server
- How contact center leaders evaluate customer experiences powered by generative AI
AWS News Blog
AWS Startups Blog
- How Snorkel AI achieved over 40% cost savings by scaling machine learning workloads using Amazon EKS
AWS Big Data Blog
- Introducing persistent buffering for Amazon OpenSearch Ingestion
- Build scalable and serverless RAG workflows with a vector engine for Amazon OpenSearch Serverless and Amazon Bedrock Claude models
- Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics
- Introducing AWS Glue serverless Spark UI for better monitoring and troubleshooting
Containers
AWS DevOps Blog
Front-End Web & Mobile
AWS for Industries
- Accelerate connected vehicle deployment with the Connected Mobility Solution on AWS
- AWS Clean Rooms: Privacy-enhanced collaboration use cases
- How payment companies are building SoftPOS solutions on AWS
AWS Machine Learning Blog
- How Amazon Music uses SageMaker with NVIDIA to optimize ML training and inference performance and cost
- Machine Learning with MATLAB and Amazon SageMaker
- Text embedding and sentence similarity retrieval at scale with Amazon SageMaker JumpStart
- Amazon Textract’s new Layout feature introduces efficiencies in general purpose and generative AI document processing tasks