Field Notes: Inference C++ Models Using SageMaker Processing

By Dustin Ward

Amazon Web Services FeedField Notes: Inference C++ Models Using SageMaker Processing Machine learning has existed for decades. Before the prevalence of doing machine learning with Python, many other languages such as Java, and C++ were used to build models. Refactoring legacy models in C++ or Java could be forbiddingly expensive and time consuming. Customers need…

Safely deploying and monitoring Amazon SageMaker endpoints with AWS CodePipeline and AWS CodeDeploy

By Dustin Ward

Amazon Web Services FeedSafely deploying and monitoring Amazon SageMaker endpoints with AWS CodePipeline and AWS CodeDeploy As machine learning (ML) applications become more popular, customers are looking to streamline the process for developing, deploying, and continuously improving models. To reliably increase the frequency and quality of this cycle, customers are turning to ML operations (MLOps),…

Announcing preview of Java Message Service 2.0 over AMQP on Azure Service Bus

By Dustin Ward

Azure Service Bus simplifies enterprise messaging scenarios by leveraging familiar queue and topic subscription semantics over the industry-driven AMQP protocol. It offers customers a fully managed platform as a service (PaaS) offering with deep integrations with Azure services to provide a messaging broker with high throughput, reliable latency while ensuring high availability, secure design, and…

New Azure SQL Learning Tools help reduce the global technology skills gap

By Dustin Ward

Microsoft’s learning solutions pave the way toward data-centric jobs of the future “It’s been forecasted 800 million people need to learn new skills for their jobs by 2030. In this time of change, people are hungry to learn, gain new skills, and grow their economic opportunity.”—Satya Nadella, CEO, Microsoft Across Microsoft, we are helping a…