Every week, there’s a new Amazon Web Services (AWS) community event where you can network, learn something new, and immerse yourself in the community. When you’re in a community, everyone grows together, and no one is left behind. Last week was no exception. I can highlight the Dach AWS Community Day where Viktoria Semaan closed with a talk titled How to Create Impactful Content and Build a Strong Personal Brand, and the Peru User Group, who organized two days of talks and learning opportunities: UGCONF & SERVERLESSDAY 2024, featuring Jeff Barr, who spoke about how to Create Your Own Luck. The community events continue, so check them out at Upcoming AWS Community Days.

Last week’s launches
Here are the launches that got my attention.

Jamba 1.5 family of models by AI21 Labs is now available in Amazon Bedrock – The Jamba 1.5 Large and 1.5 Mini models feature a 256k context window, one of the longest on the market, enabling complex tasks like lengthy document analysis. With native support for structured JSON output, function calling, and document processing, they integrate into enterprise workflows for specialized AI solutions. To learn more, read Jamba 1.5 family of models by AI21 Labs is now available in Amazon Bedrock, visit the AI21 Labs in Amazon Bedrock page, and read the documentation.

AWS Lambda now supports Amazon Linux 2023 runtimes in AWS GovCloud (US) Regions – These runtimes offer the latest language features, including Python 3.12, Node.js 20, Java 21, .NET 8, Ruby 3.3, and Amazon Linux 2023. They have smaller deployment footprints, updated libraries, and a new package manager. Additionally, you can also use the container base images to build and deploy functions as a container image.

Amazon SageMaker Studio now supports automatic shutdown of idle applications – You can now enable automatic shutdown of inactive JupyterLab and CodeEditor applications using Amazon SageMaker Distribution image v2.0 or newer. Administrators can set idle shutdown times at domain or user profile levels, with optional user customization. This cost control mechanism helps avoid charges for unused instances and is available across all AWS Regions where SageMaker Studio is offered.

Amazon S3 is implementing a default 128 KB minimum object size for S3 Lifecycle transition rules to any S3 storage class – Reduce transition costs for datasets with many small objects by decreasing transition requests. Users can override the default and customize minimum object sizes. Existing rules remain unchanged, but the new default applies to new or modified configurations.

AWS Lake Formation centralized access control for Amazon Redshift data sharing is now available in 11 additional Regions – Enabling granular permissions management, including table, column, and row-level access to shared Amazon Redshift data. It also supports tag-based access control and trusted identity propagation with AWS IAM Identity Center for improved security and simplified management.

Llama 3.2 generative AI models now available in Amazon Bedrock – The collection includes 90B and 11B parameter multimodal models for sophisticated reasoning tasks, and 3B and 1B text-only models for edge devices. These models support vision tasks, offer improved performance, and are designed for responsible AI innovation across various applications. These models support a 128K context length and multilingual capabilities in eight languages. Learn more about it in Introducing Llama 3.2 models from Meta in Amazon Bedrock.

Share AWS End User Messaging SMS resources across multiple AWS accounts – You can use AWS Resource Access Manager (RAM), to share phone numbers, sender IDs, phone pools, and opt-out lists. Additionally, Amazon SNS now delivers SMS text messages through AWS End User Messaging, offering enhanced features like two-way messaging and granular permissions. These updates provide greater flexibility and control for SMS messaging across AWS services.

AWS Serverless Application Repository now supports AWS PrivateLink – Enabling direct connection from Amazon Virtual Private Cloud (VPC) without internet exposure. This enhances security by keeping communication within the AWS network. Available in all Regions where AWS Serverless Application Repository is offered, it can be set up using the AWS Management Console or AWS Command Line Interface (AWS CLI).

Amazon SageMaker with MLflow now supports AWS PrivateLink for secure traffic routing – Enabling secure data transfer from Amazon Virtual Private Cloud (VPC) to MLflow Tracking Servers within the AWS network. This enhances protection of sensitive information by avoiding public internet exposure. Available in most AWS Regions, it improves security for machine learning (ML) and generative AI experimentation using MLflow.

Introducing Amazon EC2 C8g and M8g Instances – Enhanced performance for compute-intensive and general-purpose workloads. With up to three times more vCPUs, three times more memory, 75 percent more memory bandwidth, and two times more L2 cache, these instances improve data processing, scalability, and cost-efficiency for various applications including high performance computing (HPC), batch processing, and microservices. Read more in Run your compute-
intensive and general purpose workloads sustainably with the new Amazon EC2 C8g, M8g instances.

Llama 3.2 models are now available in Amazon SageMaker JumpStart – These models offer various sizes from 1B to 90B parameters, support multimodal tasks, including image reasoning, and are more efficient for AI workloads. The 1B and 3B models can be fine-tuned, while Llama Guard 3 11B Vision supports responsible innovation and system-level safety. Learn more in Llama 3.2 models from Meta are now available in Amazon SageMaker JumpStart.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Other AWS news
Here are some additional projects, blog posts, and news items that you might find interesting:

Deploy generative AI agents in your contact center for voice and chat using Amazon Connect, Amazon Lex, and Amazon Bedrock Knowledge Bases – This solution enables low-latency customer interactions, answering queries from a knowledge base. Features include conversation analytics, automated testing, and hallucination detection in a serverless architecture.

How AWS WAF threat intelligence features help protect the player experience for betting and gaming customers – AWS WAF enhances bot protection for betting and gaming. New features include browser fingerprinting, automation detection, and ML models to identify coordinated bots. These tools combat scraping, fraud, distributed denial of service (DDoS) attacks, and cheating, safeguarding player experiences.

How to migrate 3DES keys from a FIPS to a non-FIPS AWS CloudHSM cluster – Learn how to securely transfer Triple Data Encryption Algorithm (3DES) keys from Federal Information Processing Standard (FIPS) hsm1 to non-FIPS hsm2 clusters using RSA-AES wrapping, without backups. This enables using new hsm2.medium instances with FIPS 140-3 Level 3 support, non-FIPS mode, increased key capacity, and mutual TLS (mTLS).

Upcoming AWS events
Check your calendars and sign up for upcoming AWS events:

AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. These events offer technical sessions, demonstrations, and workshops delivered by experts. There is only one event left that you can still register for: Ottawa (October 9).

AWS Community Days – Join community-led conferences featuring technical discussions, workshops, and hands-on labs driven by expert AWS users and industry leaders from around the world. Upcoming AWS Community Days are scheduled for October 3 in the Netherlands and Romania, and on October 5 in Jaipur, Mexico, Bolivia, Ecuador, and Panama. I’m happy to share with you that I will be joining the Panama community on October 5.

AWS GenAI Lofts – Collaborative spaces and immersive experiences that showcase AWS’s expertise with the cloud and AI, while providing startups and developers with hands-on access to AI products and services, exclusive sessions with industry leaders, and valuable networking opportunities with investors and peers. Find a GenAI Loft location near you and don’t forget to register. I’ll be in the San Francisco lounge with some demos on October 15 at the Gen AI Developer Day. If you’re attending, feel free to stop by and say hello!

Browse all upcoming AWS led in-person and virtual events and developer-focused events.

That’s all for this week. Check back next Monday for another Weekly Roundup!

Thanks to Dmytro Hlotenko and Diana Alfaro for the photos of their community events.

— Eli

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Today, we are announcing the availability of AI21 Labs’ powerful new Jamba 1.5 family of large language models (LLMs) in Amazon Bedrock. These models represent a significant advancement in long-context language capabilities, delivering speed, efficiency, and performance across a wide range of applications. The Jamba 1.5 family of models includes Jamba 1.5 Mini and Jamba 1.5 Large. Both models support a 256K token context window, structured JSON output, function calling, and are capable of digesting document objects.

AI21 Labs is a leader in building foundation models and artificial intelligence (AI) systems for the enterprise. Together, AI21 Labs and AWS are empowering customers across industries to build, deploy, and scale generative AI applications that solve real-world challenges and spark innovation through a strategic collaboration. With AI21 Labs’ advanced, production-ready models together with Amazon’s dedicated services and powerful infrastructure, customers can leverage LLMs in a secure environment to shape the future of how we process information, communicate, and learn.

What is Jamba 1.5?
Jamba 1.5 models leverage a unique hybrid architecture that combines the transformer model architecture with Structured State Space model (SSM) technology. This innovative approach allows Jamba 1.5 models to handle long context windows up to 256K tokens, while maintaining the high-performance characteristics of traditional transformer models. You can learn more about this hybrid SSM/transformer architecture in the Jamba: A Hybrid Transformer-Mamba Language Model whitepaper.

You can now use two new Jamba 1.5 models from AI21 in Amazon Bedrock:

• Jamba 1.5 Large excels at complex reasoning tasks across all prompt lengths, making it ideal for applications that require high quality outputs on both long and short inputs.
• Jamba 1.5 Mini is optimized for low-latency processing of long prompts, enabling fast analysis of lengthy documents and data.

Key strengths of the Jamba 1.5 models include:

• Long context handling – With 256K token context length, Jamba 1.5 models can improve the quality of enterprise applications, such as lengthy document summarization and analysis, as well as agentic and RAG workflows.
• Multilingual – Support for English, Spanish, French, Portuguese, Italian, Dutch, German, Arabic, and Hebrew.
• Developer-friendly – Native support for structured JSON output, function calling, and capable of digesting document objects.
• Speed and efficiency – AI21 measured the performance of Jamba 1.5 models and shared that the models demonstrate up to 2.5X faster inference on long contexts than other models of comparable sizes. For detailed performance results, visit the Jamba model family announcement on the AI21 website.

Get started with Jamba 1.5 models in Amazon Bedrock
To get started with the new Jamba 1.5 models, go to the Amazon Bedrock console, choose Model access on the bottom left pane, and request access to Jamba 1.5 Mini or Jamba 1.5 Large.

To test the Jamba 1.5 models in the Amazon Bedrock console, choose the Text or Chat playground in the left menu pane. Then, choose Select model and select AI21 as the category and Jamba 1.5 Mini or Jamba 1.5 Large as the model.

By choosing View API request, you can get a code example of how to invoke the model using the AWS Command Line Interface (AWS CLI) with the current example prompt.

You can follow the code examples in the Amazon Bedrock documentation to access available models using AWS SDKs and to build your applications using various programming languages.

The following Python code example shows how to send a text message to Jamba 1.5 models using the Amazon Bedrock Converse API for text generation.

import boto3
from botocore.exceptions import ClientError

# Create a Bedrock Runtime client.
bedrock_runtime = boto3.client("bedrock-runtime", region_name="us-east-1")

# Set the model ID.
# modelId = "ai21.jamba-1-5-mini-v1:0"
model_id = "ai21.jamba-1-5-large-v1:0"

# Start a conversation with the user message.
user_message = "What are 3 fun facts about mambas?"
conversation = [
    {
        "role": "user",
        "content": [{"text": user_message}],
    }
]

try:
    # Send the message to the model, using a basic inference configuration.
    response = bedrock_runtime.converse(
        modelId=model_id,
        messages=conversation,
        inferenceConfig={"maxTokens": 256, "temperature": 0.7, "topP": 0.8},
    )

    # Extract and print the response text.
    response_text = response["output"]["message"]["content"][0]["text"]
    print(response_text)

except (ClientError, Exception) as e:
    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
    exit(1)

The Jamba 1.5 models are perfect for use cases like paired document analysis, compliance analysis, and question answering for long documents. They can easily compare information across multiple sources, check if passages meet specific guidelines, and handle very long or complex documents. You can find example code in the AI21-on-AWS GitHub repo. To learn more about how to prompt Jamba models effectively, check out AI21’s documentation.

Now available
AI21 Labs’ Jamba 1.5 family of models is generally available today in Amazon Bedrock in the US East (N. Virginia) AWS Region. Check the full Region list for future updates. To learn more, check out the AI21 Labs in Amazon Bedrock product page and pricing page.

Give Jamba 1.5 models a try in the Amazon Bedrock console today and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

Visit our community.aws site to find deep-dive technical content and to discover how our Builder communities are using Amazon Bedrock in their solutions.

— Antje

AWS Community Days have been in full swing around the world. I am going to put the spotlight on AWS Community Day Argentina where Jeff Barr delivered the keynote, talks and shared his nuggets of wisdom with the community, including a fun story of how he once followed Bill Gates to a McDonald’s!

I encourage you to read about his experience.

Last week’s launches
Here are the launches that got my attention, starting off with the GA releases.

Amazon EC2 X8g Instances are now generally available – X8g instances are powered by AWS Graviton4 processors and deliver up to 60% better performance than AWS Graviton2-based Amazon EC2 X2gd instances. These instances offer larger sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 3TiB) than Graviton2-based X2gd instances.

Amazon Q generative SQL for Amazon Redshift is now generally available – Amazon Q generative SQL in Amazon Redshift Query Editor is an out-of-the-box web-based SQL editor for Amazon Redshift. It uses generative AI to analyze user intent, query patterns, and schema metadata to identify common SQL query patterns directly within Amazon Redshift, accelerating the query authoring process for users and reducing the time required to derive actionable data insights.

AWS SDK for Swift is now generally available – AWS SDK for Swift provides a modern, user-friendly, and native Swift interface for accessing Amazon Web Services from Apple platforms, AWS Lambda, and Linux-based Swift on Server applications. Now that it’s GA, customers can use AWS SDK for Swift for production workloads. Learn more in the AWS SDK for Swift Developer Guide.

AWS Amplify now supports long-running tasks with asynchronous server-side function calls – Developers can use AWS Amplify to invoke Lambda function asynchronously for operations like generative AI model inferences, batch processing jobs, or message queuing without blocking the GraphQL API response. This improves responsiveness and scalability, especially for scenarios where immediate responses are not required or where long-running tasks need to be offloaded.

Amazon Keyspaces (for Apache Cassandra) now supports add-column for multi-Region tables – With this launch, you can modify the schema of your existing multi-Region tables in Amazon Keyspaces (for Apache Cassandra) to add new columns. You only have to modify the schema in one of its replica Regions and Keyspaces will replicate the new schema to the other Regions where the table exists.

Amazon Corretto 23 is now generally available – Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK. Corretto 23 is an OpenJDK 23 Feature Release that includes an updated Vector API, expanded pattern matching and switch expression, and more. It will be supported through April, 2025.

Use OR1 instances for existing Amazon OpenSearch Service domains – With OpenSearch 2.15, you can leverage OR1 instances for your existing Amazon OpenSearch Service domains by simply updating your existing domain configuration, and choosing OR1 instances for data nodes. This will seamlessly move domains running OpenSearch 2.15 to OR1 instances using a blue/green deployment.

Amazon S3 Express One Zone now supports AWS KMS with customer managed keys – By default, S3 Express One Zone encrypts all objects with server-side encryption using S3 managed keys (SSE-S3). With S3 Express One Zone support for customer managed keys, you have more options to encrypt and manage the security of your data. S3 Bucket Keys are always enabled when you use SSE-KMS with S3 Express One Zone, at no additional cost.

Use AWS Chatbot to interact with Amazon Bedrock agents from Microsoft Teams and Slack – Before, customers had to develop custom chat applications in Microsoft Teams or Slack and integrate it with Amazon Bedrock agents. Now they can invoke their Amazon Bedrock agents from chat channels by connecting the agent alias with an AWS Chatbot channel configuration.

AWS CodeBuild support for managed GitLab runners – Customers can configure their AWS CodeBuild projects to receive GitLab CI/CD job events and run them on ephemeral hosts. This feature allows GitLab jobs to integrate natively with AWS, providing security and convenience through features such as IAM, AWS Secrets Manager, AWS CloudTrail, and Amazon VPC.

We launched existing services in additional Regions:

• Amazon Aurora PostgreSQL Optimized Reads is now available in the AWS GovCloud (US) Regions.
• Amazon DocumentDB is now available in Europe (Spain), and Africa (Cape Town) Regions.
• Amazon MSK now extends support for Graviton3 based M7G instances in Europe (London) Region.
• Amazon EC2 G6 instances now available in Spain region and, High Memory instances now available in Africa (Cape Town) Region.

Other AWS news
Here are some additional projects, blog posts, and news items that you might find interesting:

Secure Cross-Cluster Communication in EKS – It demonstrates how you can use Amazon VPC Lattice and Pod Identity to secure cross-EKS-cluster application communication, along with an example that you can use as a reference to adapt to your own microservices applications.

Improve RAG performance using Cohere Rerank – This post focuses on improving search efficiency and accuracy in RAG systems using Cohere Rerank.

AWS open source news and updates – My colleague Ricardo Sueiras writes about open source projects, tools, and events from the AWS Community; check out Ricardo’s page for the latest updates.

Upcoming AWS events
Check your calendars and sign up for upcoming AWS events:

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world. Upcoming AWS Community Days are in Italy (Sep. 27), Taiwan (Sep. 28), Saudi Arabia (Sep. 28)), Netherlands (Oct. 3), and Romania (Oct. 5).

Browse all upcoming AWS led in-person and virtual events and developer-focused events.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— Abhishek

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!