Category: Artificial Intelligence

Modern distributed systems route business transactions through dozens of microservices, message queues, and event streams. When a message fails to process or processing exceeds SLA thresholds, troubleshooting requires correlating logs from tools like Elasticsearch, metrics from Datadog, and infrastructure change events in AWS CloudTrail. Correlating these signals manually across heterogeneous backends, each with different query […]

Learn how to build CLI tools that extend themselves through natural language using Amazon Bedrock, the Strands Agents SDK, and Model Context Protocol. This post walks through a meta-tooling pattern where generated CLIs can create, refine, and version new commands at runtime—turning days of manual development into minutes of conversational iteration, all without touching source code.

Learn how AWS Transform custom can help migrate Excel VBA applications to modern Python code while overcoming context window limitations, preserving functional equivalence, and enabling cloud-native deployment—turning weeks of manual rewriting into hours of AI-guided transformation. Introduction Many organizations maintain dozens of Excel VBA applications built over decades, containing business-critical logic trapped in workbooks—budget planning […]

Introduction Modernizing applications by upgrading language runtimes, migrating SDKs, and refactoring frameworks is important for cloud adoption but can be labor-intensive at scale. Each repository requires analysis of dependencies and transformation needs; custom transformation logic must be built and validated, and changes are often executed sequentially across codebases. If you have hundreds of applications, this […]

Enterprise modernization has reached an inflection point. You can transform one repository easily. Existing tools, including AWS Transform custom, work well for individual repositories, and the process is understood. But what about 50 repositories? 100? 200? When you need to modernize at enterprise scale, transforming code is only part of the challenge. Coordinating people, capturing […]

Introduction AWS Elastic Beanstalk simplifies the process of deploying and scaling web applications. You upload your code, and Elastic Beanstalk handles capacity provisioning, load balancing, auto scaling, and application health monitoring. Elastic Beanstalk now offers AI Analysis to help troubleshoot environment health issues. When you request an analysis, Elastic Beanstalk triggers a script on the […]

Introduction Teams running distributed workloads face a persistent operational challenge: when something breaks, the information needed to resolve it is scattered across logs, deployment pipelines, configuration histories, and third-party monitoring tools. A Site Reliability Engineer (SRE) responding to a 2 AM page must manually correlate telemetry from multiple sources, trace dependencies across services, and form […]

Introduction Organizations carry a growing burden of technical debt — aging codebases, outdated runtimes, and legacy frameworks that slow innovation, increase security risk, and inflate maintenance costs. Addressing this debt requires tackling a wide range of code transformation challenges: version upgrades, runtime migrations, framework transitions, and language translations, all of which must be repeated across […]

Introduction Software maintenance and modernization is a critical challenge for enterprises managing hundreds or thousands of repositories. Whether upgrading Java versions, migrating to new AWS SDKs, or modernizing frameworks, the scale of transformation work can be overwhelming. AWS Transform custom uses agentic AI to perform large-scale modernization of software, code, libraries, and frameworks to reduce […]

In today’s rapidly evolving software landscape, maintaining and modernizing Java applications is a critical challenge for many organizations. As new Java versions are released and best practices evolve, the need for efficient code transformation becomes increasingly important. Organizations today face significant challenges when modernizing their Java applications. Legacy codebases often contain outdated patterns, deprecated APIs, […]