OpenTelemetry is a set of APIs, libraries, agents, and instrumentation that empower developers to observe, collect, and manage telemetry data (metrics, logs, and traces) from their services for improved reliability, understandability, and debuggability. The project is a merger of two formerly separate projects: OpenTracing and OpenCensus. By combining the best features from both, OpenTelemetry aims […]

Today we are excited to announce the general availability of SaaS Quick Launch, a new feature in AWS Marketplace that makes it easy and secure to deploy SaaS products. Before SaaS Quick Launch, configuring and launching third-party SaaS products could be time-consuming and costly, especially in certain categories like security and monitoring. Some products require […]

Australia pioneered water rights trading in the early 1900s, becoming a world leader in water sharing between valleys. The initiative extended throughout the states of Australia across the Murray-Darling Basin (MDB). However, findings from the water market’s inquiry of the MDB, completed by the Australian Consumer and Competition Commission (ACCC) and the Department of Climate […]

I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference […]

Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, […]

Today, we are announcing new Amazon SageMaker inference capabilities that can help you optimize deployment costs and reduce latency. With the new inference capabilities, you can deploy one or more foundation models (FMs) on the same SageMaker endpoint and control how many accelerators and how much memory is reserved for each FM. This helps to […]

Today, I’m excited to introduce a new capability in Amazon SageMaker Canvas to use foundation models (FMs) from Amazon Bedrock and Amazon SageMaker Jumpstart through a no-code experience. This new capability makes it easier for you to evaluate and generate responses from FMs for your specific use case with high accuracy. Every business has its […]

You can use the new OR1 instances to create Amazon OpenSearch Service clusters that use Amazon Simple Storage Service (Amazon S3) for primary storage. You can ingest, store, index, and access just about any imaginable amount of data, while also enjoying a 30% price/performance improvement over existing instance types, eleven nines of data durability, and […]

I’m happy to share that Amazon SageMaker Clarify now supports foundation model (FM) evaluation (preview). As a data scientist or machine learning (ML) engineer, you can now use SageMaker Clarify to evaluate, compare, and select FMs in minutes based on metrics such as accuracy, robustness, creativity, factual knowledge, bias, and toxicity. This new capability adds […]

I’m happy to share that you can now evaluate, compare, and select the best foundation models (FMs) for your use case in Amazon Bedrock. Model Evaluation on Amazon Bedrock is available today in preview. Amazon Bedrock offers a choice of automatic evaluation and human evaluation. You can use automatic evaluation with predefined metrics such as […]