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),…

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…

Vortexa delivers real-time insights on Amazon MSK with Lenses.io

By Dustin Ward

Amazon Web Services FeedVortexa delivers real-time insights on Amazon MSK with Lenses.io This is a guest post by Lenses.io. In their own words, “Lenses.io is a group of engineers, designers, developers, data analysts, tinkerers, writers, and open-source contributors. We specialize in the democratizing of data technologies. That’s why we developed Lenses.io (Lenses-eye-oh) to help enterprises…