AWS Cloud Operations & Migrations Blog

Category: Artificial Intelligence

Custom Post-launch actions and Deployment scripting using AWS Systems Manager and Amazon CodeWhisperer

In Part 1 of this series, you learned about Blue/Green testing and deployment on AWS, a key strategy that increases application availability and reduces deployment risk by simplifying the rollback process if a deployment fails. We explored live replication using AWS Application Migration Service (AWS MGN) and introduced prebuilt post-launch actions with AWS Systems Manager […]

Accelerating Blue/Green Deployments with AWS MGN Post-Launch Actions

Customers are becoming more aware of the benefits of migrating to AWS in a world increasingly pivoting towards cloud adoption. A recent whitepaper by IDC found that customers who migrate to AWS can experience a 51% reduction in the cost of operations, a 62% increase in IT staff productivity, and a 94% reduction in downtime. […]

Automate the creation of AWS Support cases using Amazon CloudWatch alarms and Amazon Bedrock

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 […]

Leverage generative AI to create custom dashboard widgets in Amazon CloudWatch using Amazon CodeWhisperer

Observability describes how well you can understand what is happening in a system, often by instrumenting it to collect metrics, logs, and traces. To achieve operational excellence and meet business objectives, you need to understand how your systems are performing. In order to accomplish this, many customers use Amazon CloudWatch to get real-time monitoring, alerts […]

Analyzing Amazon Lex conversation log data with Amazon Managed Grafana

To support business and internal processes, organizations are increasing their use of conversational interfaces. They offer opportunities for more availability, improved service levels, and reduced costs. As these conversational services become more important, so, does the need to monitor performance and effectiveness of these interfaces with analytics and dashboards. This analysis is used to drive […]

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 […]

How to Automate Incident Response with PagerDuty and AWS Systems Manager Incident Manager

Incident response is a core operations capability for organizations to develop, and a core element in the AWS Cloud Adoption Framework (AWS CAF). Responding to operations incidents quickly is important to minimize their impacts. Automating incident response helps you scale your capabilities, rapidly reduce the recovery time, and reduce repetitive work by your cloud operations teams. […]

Automate AIOps for your microservices in AWS using Amazon DevOps Guru and AWS Systems Manager Incident Manager

Artificial intelligence operations (AIOps) is the process of using machine learning techniques to solve operational problems. The goal of AIOps is to reduce human intervention in IT operations processes. By using advanced machine learning techniques, you can reduce operational incidents and increase service quality, and AIOps can help you predict incidents before they happen. Amazon […]

Create speech-enabled products using AWS Service Catalog and Amazon Polly

In this post, we’ll show how enterprises can use AWS Service Catalog to create AWS Service Catalog products based on AWS machine learning (ML) services, such as Amazon Polly and Amazon Rekognition. These products are packaged in AWS Service Catalog portfolios that customers can use for their use cases. These portfolios can generate revenue for […]