AWS re:Invent 2022, New AWS Services

The annual conference of AWS celebrated its 11th anniversary, reaching both in-person and virtual audiences.

With multiple sessions and keynotes, the cloud provider AWS announced new services and features focusing on business solutions and data options this year. Here are highlights from the news Amazon announced:

Top 5 Highlights

Amazon Security Lake: Automatically centralize security data from the cloud- premises to create a purpose-built data lake that can be stored in your account for a complete understanding of your security data across your organization. 

AWS Glue Delivery: This release of AWS Glue includes Python 3.10 and Apache 3.30 in addition to native support for the Cloud Shuffle Service Plugin for Spark so that users can scale their disk usage. 

AWS Elastic Disaster Recovery:  New automated support provides a simple and accelerated experience to return a failed Amazon EC2 instance to its original region, providing both failover and failback processes (either locally or for recovery within AWS) that can be conveniently run from the AWS Management console.

Amazon EC2 instances: The new EC2 instance families are designed to provide better performance for running high-performance computing workloads at scale and the capacity to handle double the packets per second (PPS) compared to earlier instances.

Amazon Macie Automated Data Discovery: Automatically sample and analyze objects across S3 buckets, inspecting them for sensitive data such as PII, financial data, and AWS credentials to help you continuously identify and remediate data security risks without manual configuration.

20 New AWS Services and Features from re:Invent 2022

1. 1. Features flags and runtime configuration for AWS AppConfig: Intending to make feature fags and runtime configuration more straightforward with improved performance, AWS AppConfig has been released. Source.

1. 1. AWS CodeCatalist (under review): Throughout the development lifecycle, AWS CodeCatalist enables software development teams so that you to quickly and easily plan, develop, collaborate on, build, and deliver applications on AWS, reducing friction. Link.

1. 1. EventBridge Pipes: Point-to-point plug-and-play integrations between consumers and producers. After that, it is easier to stitch many different services or data-driven applications. Link.

1. 1. Single-step APIs for Amazon Comprehend: An NLP service lets users extract data from unstructured data and images. Link.

1. 1. Step Function Distributed Map: Easily coordinate large-scale parallel workloads within the serverless applications. Link.

1. 1. AWS re:post-integration: Without managing multiple login credentials, let the customer work the AWS management console. Source.

1. 1. AWS Application Composer: To build serverless applications, it’s a low code drag-and-drop hub. Link.

1. 1. Amazon Gamelift Anywhere: It’s a hosting service for the multiplayer game server to deploy their hardware in a hybrid setup. Link.

1. 1. Amazon Sagemaker Data Wrangler: Reduces the time to aggregate and prepare data from weeks to minutes. This is one of the most potent updates, I think. Link.

1. 1. Amazon Athena Supports Apache Spark now: With Amazon Athena for Apache spark, users get the streamlined, interactive, serverless experience of Athena. Source.

1. 1. New ML Governance tool for SageMaker: It’s a machine learning service. Additionally, it includes custom permissions. Link.

1. 1. Real-time Collaboration for Amazon SageMaker: It’s a fully integrated development environment (IDE) for Machine Learning that enables ML practitioners to perform every step of the machine learning workflow, from preparing data to building, training, and many other tasks in Sagemaker studio to accelerate real-time collaboration. Source.

1. 1. Trusted Language Extensions for PostgreSQL: It’s a new open-source development kit to help users build high-performance extensions that run safely on PostgreSQL. Link.

1. 1. AWS AI Service Cards: It’s a unique and new resource to increase transparency and help customers better understand. Link.

1. 1. AWS Glue Delivery: It helps AWS Partners with deep expertise and proven success delivering AWS Glue for data integration, pipeline, and catalog use cases. Link.

1. 1. Data Exchange for Amazon S3: It’s a preview of AWS data exchange for S3 that enables subscribers to access third Party data files from data providers directly. Source.

1. 1. Auto Conversion Notebook code to production-ready jobs: While moving the notebook into production, users manually copy the snippets of code from the notebook into a script, package the hand with all its dependencies into a container, and then schedule the container to run as a job. In addition, if the job needs to be run on a schedule, they must set up, configure, and manage a continuous integration and continuous delivery (CI/CD) pipeline to automate their deployments. Link.

1. 1. New EC2 Inf2 Instances: AWS Inferentia2 is the second version of the AWS Inferentia accelerator and is optimized to deploy the complex model.

1. 1. Amazon QuickSight Q: supports automated data preparation to make it faster and straightforward. Link.

1. 1. Amazon Omics: With the help of Omics, you can bring genomic, biological, and population health data together to generate insights and offer more personalized care with multimodal analysis. Link.