Configure alerts of high CPU usage in applications using Amazon OpenSearch Service anomaly detection: Part 1

By Dustin Ward

AWS FeedConfigure alerts of high CPU usage in applications using Amazon OpenSearch Service anomaly detection: Part 1 Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) is a fully managed service that makes it easy to deploy, secure, and run Elasticsearch cost-effectively at scale. Amazon OpenSearch Service supports many use cases, including application monitoring, search, security…

Amazon Lex launches support for AWS CloudFormation

By Dustin Ward

AWS FeedAmazon Lex launches support for AWS CloudFormation Amazon Lex now supports AWS CloudFormation, allowing you to create bots and organize Amazon Lex resources using CloudFormation stack templates. Amazon Lex is a service for building conversational interfaces into any application using voice and text. With CloudFormation support, you can easily model resources on Lex V2 APIs –…

Experience Digital’s Purpose-Built Assessment Tool Created Using AWS Lambda

By Dustin Ward

AWS FeedExperience Digital’s Purpose-Built Assessment Tool Created Using AWS Lambda By Holly Hudson, AWS Community Lead – Experience Digital Experience Digital Many industries are beginning to recognize the vast value proposition of serverless architecture, which drives observability, lowers cost, and increases the potential for scalability. In the medical industry, paper-based resources were traditionally the preferred…

Identify operational issues quickly by using Grafana and Amazon CloudWatch Metrics Insights (Preview)

By Dustin Ward

AWS FeedIdentify operational issues quickly by using Grafana and Amazon CloudWatch Metrics Insights (Preview) Amazon CloudWatch has recently launched Metrics Insights (Preview) – a fast, flexible, SQL-based query engine that enables you to identify trends and patterns across millions of operational metrics in real-time. With Metrics Insights, you can easily query and analyze your metrics to…

Applying Federated Learning for ML at the Edge

By Dustin Ward

AWS FeedApplying Federated Learning for ML at the Edge Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the…