7/19/2024, 12:00:00 AM ~ 7/22/2024, 12:00:00 AM (UTC)

Recent Announcements

Productionize Fine-tuned Foundation Models from SageMaker Canvas

Amazon SageMaker Canvas now supports deploying fine-tuned Foundation Models (FMs) to SageMaker real-time inference endpoints, allowing you to bring generative AI capabilities into production and consume outside the Canvas workspace. SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate ML predictions and use generative AI capabilities.\n SageMaker Canvas provides access to fine-tuning FMs powered by Amazon Bedrock and SageMaker JumpStart such as Amazon Titan Express, Falcon-7B-Instruct, Falcon-40B-Instruct, and Flan-T5 variants. You can upload a dataset, select a FM to fine-tune, and SageMaker Canvas automatically creates and tunes the model to adapt the FMs to the patterns and nuances of your specific use-case enhancing the performance of the model’s responses. Starting today, you can deploy fine-tuned FMs to SageMaker endpoints making it easier to integrate generative AI capabilities into your applications outside the SageMaker Canvas workspace. To get started, log in to SageMaker Canvas to access the fine-tuned FMs Select the desired model and deploy it with the appropriate endpoint configurations such as indefinitely or for a specific duration of time. SageMaker Inferencing charges will apply to deployed models. A new user can access the latest version by directly launching SageMaker Canvas from their AWS console. An existing user can access the latest version of SageMaker Canvas by clicking “Log Out” and logging back in. The expanded feature is now available in all AWS regions where SageMaker Canvas is supported. To learn more, refer to the SageMaker Canvas product documentation.

Amazon Connect launches search API for hierarchy groups

Amazon Connect now provides an API to search for hierarchy groups by name, group ID, tag, or other criteria. Hierarchy groups describe your organization’s structure, and are used for reporting and access control. With this new API, you can now answer questions such as, “How many teams operate in the northwest region?” and, “What groups have a tag indicating they can access performance reviews?” and see a response with details like name, description, hierarchy level, ARN, and when a record was last updated.\n The SearchUserHierarchyGroups API is supported in all AWS regions where Amazon Connect is offered. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website. To learn more about the new search APIs, see the API documentation. To learn more about hierarchy groups, see the Amazon Connect Administrator Guide.

Amazon Connect launches search API for agent status

Amazon Connect now provides an API to search an agent status by name, ID, tag, or other criteria. Agent statuses are used in the Contact Control Panel (CCP) to indicate if an agent is available to handle contacts or not, for example because they are away for lunch or in training. With this new API, you can now answer questions such as, “How many of our statuses are disabled?”, and, “What statuses have ‘break’ in their description?”, and see a response with details like name, description, display order, and ARN.\n The SearchAgentStatuses API is supported in all AWS regions where Amazon Connect is offered. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website. To learn more about the new search APIs, see the API documentation. To learn more about agent statuses, see the Amazon Connect Administrator Guide.

Simplify Your AWS Marketplace Catalog API (CAPI) Integration with Strongly-Typed API Schemas

We’re excited to announce the introduction of a GitHub library that will host the schemas for the DetailsDocument used in StartChangeSet, DescribeChangeSet, and DescribeEntity APIs in Catalog API (CAPI). This new feature aims to simplify the integration process for developers working with the Catalog API.\n Today, as a developer in seller/partner organizations, you need to construct the API request structure manually when integrating with Catalog API for operations such adding pricing dimensions. This involves reviewing the API documentation and experimenting to understand the schema of the “DetailsDocument” for the request. With the new schema library, you can directly import the Java and Python libraries to create a strongly-typed response, without having to refer to the documentation or experiment with the JSON structure. This will save time and reduce the risk of errors during both integration testing and implementation. Additionally, if there are changes to the DetailsDocument schema, you can simply download the new version of the library, review the changes, and make the necessary updates to your code. This new functionality will exist alongside sending and receiving a string object in the “Details” attribute of the StartChangeSet, DescribeChangeSet, and DescribeEntity APIs. If you’ve already integrated with these APIs, you can continue using the “Details” attribute. However, newly onboarding sellers and sellers onboarding new API actions are advised to use the schema library to make integration with Catalog API faster. For information on how to download the shape library and use it, refer to StartChangeSet API, DescribeChangeSet API and DescribeEntity API.

Amazon CloudWatch Logs Infrequent Access log class available in GovCloud Regions

Amazon CloudWatch Logs Infrequent Access (Logs IA), a log class for cost-effectively consolidating all your logs natively on AWS, is now available in all GovCloud regions. Logs IA helps improve visibility into your overall application health with a subset of CloudWatch Logs’ capabilities including managed ingestion, cross-account log analytics, and encryption with a lower per GB ingestion price. This makes Logs IA ideal for ad-hoc querying and after-the-fact forensic analysis on infrequently accessed logs.\n With Logs IA, you can choose the log class that best aligns with your use case. While you can use CloudWatch Logs Standard for logs requiring real-time operational visibility, anomaly detection, or real-time logs analysis, Logs IA is best suited for logs that require infrequent querying. By consolidating your logs natively in CloudWatch, you can eliminate the operational overhead of managing multiple solutions and reduce your Mean Time to Resolution (MTTR) by analyzing all your logs in one place. CloudWatch Logs IA is now available in all AWS GovCloud (US) regions. With a few clicks in the AWS Management Console, you can start using CloudWatch Logs IA to send logs to CloudWatch. Alternatively, you can use AWS Command Line Interface (AWS CLI), AWS CloudFormation, AWS Cloud Development Kit (AWS CDK), and AWS SDKs. Learn more about CloudWatch Logs IA pricing and read the user guide here.

AWS Lambda now supports Amazon MQ for ActiveMQ and RabbitMQ in five new regions

AWS Lambda now supports Amazon MQ for ActiveMQ and RabbitMQ in the Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Europe (Spain), Europe (Zurich), and Israel (Tel Aviv) regions, enabling you to build serverless applications with Lambda functions that are invoked based on messages posted to Amazon MQ message brokers.\n Amazon MQ is a managed message broker service for Apache ActiveMQ Classic and RabbitMQ that makes it easy to migrate to a message broker in the cloud. Lambda makes it easy to read from Amazon MQ message brokers and process messages without needing to create and manage a consumer application that monitors Amazon MQ queues for updates. Your Lambda function is invoked when the messages exceed the batch size or batch window, or when the payload exceeds 6MB. Lambda manages connectivity with your Amazon MQ message brokers on your behalf. This feature incurs no additional charge. You pay for the Lambda function invocations triggered by the event source mapping connected to Amazon MQ message brokers. To learn more, see the Lambda developer Guide for Amazon MQ.

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