AWS Cloud Operations & Migrations Blog
Category: Amazon Machine Learning
Automate the creation of AWS Support cases using Amazon CloudWatch alarms and Amazon Bedrock
For production applications, the Mean-Time-To-Recovery (MTTR) is critical. In line with this, AWS offers Business, Enterprise On-Ramp and Enterprise support plans where AWS customers can benefit from shorter response time for cases related to production and business critical workloads. However, without having an automated way to notify AWS support, creating a case is a manual […]
Monitoring Generative AI applications using Amazon Bedrock and Amazon CloudWatch integration
Amazon Bedrock is an easy way to build and scale generative AI applications with foundation models (FMs). As a fully managed service, it offers a choice of high-performing FMs from leading AI companies including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon. It also offers a broad set of capabilities needed to build generative […]
Simplify analysis of AWS CloudTrail data leveraging Amazon CloudWatch machine learning and advanced capabilities
AWS CloudTrail tracks user and API activities across AWS environments for governance and auditing purposes and allows customers to centralize a record of these activities. Customers have the option to send AWS CloudTrail logs to Amazon CloudWatch that simplifies and streamlines the analysis and monitoring of AWS CloudTrail recorded activities. Amazon CloudWatch anomaly detection allows […]
Setting up secure, well-governed machine learning environments on AWS
When customers begin their machine learning (ML) journey, it’s common for individual teams in a line of business (LoB) to set up their own ML environments. This provides teams with flexibility in their tooling choices, so they can move fast to meet business objectives. However, a key difference between ML projects and other IT projects is […]