Pallav Jain | Searcharxiv

arXiv2026

From Ad-Hoc Scripts to Orchestrated Pipelines: Architecting a Resilient ELT Framework for Developer Productivity Metrics

Developer Productivity Dashboards are essential for visualizing DevOps performance metrics such as Deployment Frequency and Change Failure Rate (DORA). However, the utility of these dashboards is frequently undermined by data reliability issues. In early iterations of our platform, ad-hoc ingestion scripts (Cron jobs) led to "silent failures," where data gaps went undetected for days, eroding organizational trust. This paper reports on our experience migrating from legacy scheduling to a robust Extract-Load-Transform (ELT) pipeline using Directed Acyclic Graph (DAG) orchestration and Medallion Architecture. We detail the operational benefits of decoupling data extraction from transformation, the necessity of immutable raw history for metric redefinition, and the implementation of state-based dependency management. Our experience suggests that treating the metrics pipeline as a production-grade distributed system is a prerequisite for sustainable engineering analytics.

cs.SE↗

arXiv2025

MetricSynth: Framework for Aggregating DORA and KPI Metrics Across Multi-Platform Engineering

In modern, large-scale software development, engineering leaders face the significant challenge of gaining a holistic and data-driven view of team performance and system health. Data is often siloed across numerous disparate tools, making manual report generation time-consuming and prone to inconsistencies. This paper presents the architecture and implementation of a centralized framework designed to provide near-real-time visibility into developer experience (DevEx) and Key Performance Indicator (KPI) metrics for a software ecosystem. By aggregating data from various internal tools and platforms, the system computes and visualizes metrics across key areas such as Developer Productivity, Quality, and Operational Efficiency. The architecture features a cron-based data ingestion layer, a dual-schema data storage approach, a processing engine for metric pre-computation, a proactive alerting system, and utilizes the open-source BI tool Metabase for visualization, all secured with role-based access control (RBAC). The implementation resulted in a significant reduction in manual reporting efforts, saving an estimated 20 person-hours per week, and enabled faster, data-driven bottleneck identification. Finally, we evaluate the system's scalability and discuss its trade-offs, positioning it as a valuable contribution to engineering intelligence platforms.

cs.SE↗