AWS New Announcement Sept 2023

AWS Partner network launches new AWS Automotive Competency

AWS has introduced the AWS Automotive Competency program, recognizing APN Partners who excel in the automotive journey. AWS Automotive Competency Partners have shown their AWS competency across at least one of eight automotive strategic workloads:

1. Autonomous Mobility (AM)
2. Software Defined Vehicle (SDV)
3. Connected Mobility
4. Sustainability
5. Digital Customer Experience (DCE)
6. Product Engineering
7. Manufacturing
8. Supply Chain

AWS Automotive Competency Partners offer advanced solutions and services that enable customers to bring innovative products to market efficiently. They serve a wide range of clients, from AutoTech startups to major Automakers, with a global presence. These partners undergo rigorous technical evaluation to ensure a consistent, high-quality customer experience. If you're an APN Partner experienced in working with automotive clients on AWS, you can explore this opportunity further.

To learn more click here

Amazon CloudWatch Logs announces regular expression filter pattern syntax support

Amazon CloudWatch Logs has introduced regular expression support for filter patterns, simplifying log searching and matching. This enhancement allows customers to use powerful regular expressions like‘{ $.statusCode=%4[0-9]{2}% }’within filter patterns to customize operations such as log searching, metric extraction, and log routing. With this feature, users can create flexible filters, reducing the need for multiple filters to handle variations like IP subnets or HTTP status codes. There's a quota of 5 regular expression patterns per log group and 2 within a specific filter pattern for metric and subscription filters. This capability is available in all AWS Commercial regions where Amazon CloudWatch Logs is offered.

For more details, refer to the Filter and Pattern Syntax documentation.

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AWS WAF Bot Control now protects against distributed proxy-based attacks

AWS WAF Bot Control for Targeted Bots has introduced predictive Machine Learning (ML) technology to defend against distributed, proxy-based attacks. It builds upon the existing protection against sophisticated evasive bots and now extends to blocking, challenging, and Captcha rules for distributed bot attacks, like those using residential and mobile proxies. Threat actors often exploit compromised residential computers to create bots and use residential proxies to avoid detection. They frequently rotate IP addresses to evade rate limiting rules and source traffic from global proxies.

AWS WAF Bot Control now employs managed ML to combat these threats automatically, providing bot confidence levels to help customize enforcement actions. This feature is available to all users at no additional cost, with standard charges applying. For more information, consult the documentation.

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Amazon has introduced new EC2 R7iz instaces, M6id and R6id database instances

AWS has launched Amazon EC2 R7iz instances, featuring memory-optimized and high CPU performance. These instances are powered by 4th generation Intel Xeon Scalable-based (Sapphire Rapids) processors, offering a sustained all-core turbo frequency of 3.9 GHz. They outperform previous z1d instances by up to 20% and are part of the AWS Nitro System, ensuring efficiency, security, isolated multi-tenancy, private networking, and fast local storage. R7iz instances are well-suited for Electronic Design Automation (EDA), high per-core licensing fee relational databases, financial modeling, data analytics simulations, and similar workloads demanding high compute performance and substantial memory capacity. They are available in eight sizes with up to 128 vCPUs and 1,024 GiB of memory, using DDR5 memory for increased memory bandwidth. Additionally, they offer fast networking and Amazon Elastic Block Store (EBS) bandwidth. These instances are accessible in US East (N. Virginia) and US West (Oregon) AWS Regions. For more details, visit Amazon EC2 R7iz instances.

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In addition, Amazon RDS now supports M6id and R6id database instances for PostgreSQL, MySQL, and MariaDB, delivering up to a 24% performance boost and a 13% price/performance improvement over previous models. These instances offer local block storage of up to 7.6 TB SSD and support Optimized Reads and Optimized Writes, enhancing query speed and write throughput. They are available in various AWS Regions, and you can find detailed pricing and availability information on the Amazon RDS pricing page.

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Announcing incremental export to S3 for Amazon DynamoDB

Amazon DynamoDB now offers incremental export to S3, allowing users to export only changed data within a specified timeframe, whether it's inserts, updates, or deletions, in manageable increments. This feature is available in all AWS commercial regions and GovCloud and supports data formats like DynamoDB JSON and Amazon Ion. It simplifies the process of updating downstream data lakes or analytics targets without requiring full table exports each time, and it's fully managed, not affecting your DynamoDB table capacity.

To learn more about incremental export to S3, see Data Exports and the Incremental export from Amazon DynamoDB to Amazon S3 blog. For information about pricing and regional availability, see Amazon DynamoDB pricing.

For more detail click here.

Optimize G4dn and P3 Instances with AWS Compute Optimizer's Rightsizing Support

AWS Compute Optimizer has expanded its support to include 11 new types of Amazon EC2 instances, including accelerated computing ones like G4dn and P3. These new recommendations are designed to help customers improve the efficiency of their Machine Learning, High-performance computing, and graphic-intensive tasks. Now, customers can use these recommendations to find the right accelerated computing options, instance types, GPU numbers, and storage settings for their existing resources. They can make their underperforming workloads run better and reduce costs for workloads that have too many resources.

Compute Optimizer will also provide suggestions for supported accelerated computing instances that have the AWS CloudWatch agent with NVIDIA driver for extra data. You can explore further details about AWS Compute Optimizer by visiting the site.

Link Foundation Models to Your Company's Data Sources Using Amazon Bedrock Agents

In July, AWS unveiled a preview of Amazon Bedrock's agents, a feature that empowers developers to build AI applications that can complete tasks. Now they have introduced a new feature that enables secure connections between foundation models (FMs) and your company's data sources using agents.

This feature allows agents to provide FMs in Bedrock with access to extra data, helping the model generate more accurate and context-aware responses without the need for constant retraining. Agents, based on user input, pinpoint the relevant knowledge base, fetch the necessary information, and incorporate it into the input, providing the model with more context to generate more informed responses.

Agents in Amazon Bedrock use something called 'retrieval augmented generation' (RAG) to make this happen. To set up a knowledge base, you'll need to specify where your data is stored in Amazon S3, choose an embedding model, and give the information about your vector database. Bedrock will transform your data into embeddings and save them in the vector database. Afterward, you can link the knowledge base to agents to enable RAG workflows.

To learn more about it, visit the documentation

Introducing Amazon EC2 M2 Pro Mac Instances Powered by Apple Silicon M2 Pro Mac Mini

AWS announces the availability of Amazon EC2 M2 Pro Mac instances. These new instances are designed to be faster, offering a 35 percent performance boost compared to the previous M1 Mac instances when you're working on Apple platform applications.

The EC2 M2 Pro Mac instances are powered by Apple's M2 Pro Mac Mini computers, which come with a 12-core CPU, a 19-core GPU, 32 GB of memory, and a 16-core Apple Neural Engine. What's unique is that these Mac Minis are integrated into the AWS Nitro System through high-speed Thunderbolt connections. This makes them fully managed compute instances with fast network and storage capabilities, providing up to 10 Gbps of Amazon VPC network bandwidth and up to 8 Gbps of Amazon EBS storage bandwidth. You can use these instances with macOS Ventura (version 13.2 or later) as AMIs for your projects.

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Amazon MSK Unveils Streamlined Data Delivery from Apache Kafka to your Data Lake

Amazon has introduced a new feature of Amazon Managed Streaming for Apache Kafka (Amazon MSK). It allows you to transfer data from an Apache Kafka cluster to Amazon S3. AWS achieves this by using Amazon Kinesis Data Firehose, a service that extracts, transforms, and loads (ETL) data. It reads data from a Kafka topic, makes necessary changes to the records, and stores them in Amazon S3. The best part is that Kinesis Data Firehose is completely managed, and you can set it up easily through the console without the need for coding or infrastructure setup.

Kafka is used to build real-time data pipelines that move large volumes of data between different systems or applications. It offers a highly scalable and fault-tolerant messaging system for publishing and subscribing to data. Many AWS customers have adopted Kafka to capture streaming data like click-stream events, transactions, IoT events, and logs from applications and machines. They use this data for real-time analytics, continuous transformations, and immediate distribution to data lakes and databases.

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AWS Backup introduces the capability to provide continuous backup support for Amazon Aurora

AWS Backup takes care of keeping your data safe across different AWS services and even in mixed environments with both cloud and on-premises systems. AWS Backup is making it easier for customers who use Amazon Aurora databases to protect their data. They've added a feature that lets users restore their database to a specific point, as long as it's within the last 35 days.

Now, if you use Amazon Aurora and AWS Backup together, you can go into the AWS Backup console or use API or CLI to bring your database back to a specific moment in time. This new feature is available in all the places where AWS Backup and Amazon Aurora are offered, so you can start using it right away.

For additional information, you can click the link