Ibrahim Mama Cisse

Over the past few weeks, I’ve been diving into AWS’s PartyRock platform as part of the AWS AI Future Engineer Scholarship Program. My goal was simple: to learn, experiment, and build small but meaningful AI applications that solve real-world problems. While I’m still early in my AI journey, I wanted to share two projects I built during Phase 1 of the program. These aren’t polished products, but learning experiments that helped me understand how AI can be applied in practical scenarios.

GitHub Repository: 🔗 OpenTelemetry ToDo App GitHub Repo Note: All code and configuration referenced in this article is available in the GitHub repo above. In this hands-on guide, we’ll explore how OpenTelemetry enables deep observability in a sample ToDo application built using Spring Boot, Flask, PostgreSQL, and Dockerized components. You’ll see how each part is instrumented, how telemetry flows through the system, and how it’s visualized using Jaeger and Prometheus. Core Components 1.

Devops.dev is a community of DevOps enthusiasts sharing insight, stories, and the latest development in the field. Follow publication Effective monitoring and alerting are crucial for maintaining the reliability of modern applications. In this guide, I will walk through an end-to-end setup of Prometheus, Grafana, and PagerDuty, ensuring that system metrics are visualized and critical alerts are promptly delivered. I will cover: Setting up Prometheus for metrics collection.