The FactCheck framework aims to address the issue of conflicting data on the Web by providing a systematic approach to detect and resolve such discrepancies. It encompasses the entire fact comparison process, including data acquisition, comparison, presentation of results, and advanced analysis features. As a pioneering research initiative of our research group, FactCheck presents several challenging aspects and opportunities in its development and implementation.
Observability (O11y) describes the ability to understand the internal state of a system using only its outputs (e.g., logs, or metrics such as CPU usage or average response time). As the FactCheck framework grows and becomes more distributed, the ability to debug and troubleshoot from persisted logs alone becomes increasingly difficult and time-consuming. Your task is it to implement a robust, scalable O11y framework using Grafana tools (e.g., Alloy, Loki) and other technologies (e.g., Prometheus). In your project, you will...
- gain an overview of the FactCheck prototype, and choose one component [P1] / at least two components from which you will collect telemetry data
- learn about key O11y concepts, and familiarize yourself with potential technologies to be used
- leverage existing telemetry data (e.g., logs), and/or implement new telemetry data for your chosen component(s) using zero-code and/or code-based instrumentation
- analyze and visualize the collected data by means of Grafana's dashboard creator
Technologies: Python; JavaScript; OpenTelemetry; OpenMetrics; Grafana; Prometheus; Docker
Tags: Aichinger; FactCheck; Observability; Telemetry; Docker; Framework
