Enterprise Quality Intelligence Engine & DORA Metrics Analytics Platform

Principal Quality Architect · Year 3 · Q12 (Previous SaaS)

Platform & InfrastructureYear 3 · Q12 (Previous SaaS)

Built a unified enterprise quality telemetry platform that aggregated pipeline signals, testing outcome histories, and production incidents into real-time quality scorecards and DORA metric dashboards.

⚡45% Reduction in Change Failure Rate (CFR)
⚡Sub-15-Minute MTTR for Automated Rollbacks
⚡100% Engineering Org Alignment on Quality SLAs
PythonGoClickHouseApache SupersetOpenTelemetryGraphQLDocker

Situation

As the engineering organization expanded to over 250 engineers across 30 feature teams, executive leadership lacked centralized visibility into software release quality, testing health, and system risk. Teams measured quality inconsistently using fragmented spreadsheets and localized test output files, leading to undetected quality degradation and unpredictable production outages.

Task

Architect an automated enterprise quality analytics platform that ingests real-time telemetry from GitHub, ArgoCD, Jira, and test runners to compute unified quality metrics, track DORA metrics, and calculate dynamic risk scores for every production release candidate.

Action

  • Event-Driven Telemetry Ingestion Pipeline: Built a high-throughput event ingestor in Go that consumed Webhooks and OpenTelemetry traces from CI/CD pipelines, storing structured execution events into a ClickHouse columnar analytical database.
  • Dynamic Release Risk Model: Developed a weighted scoring algorithm analyzing code churn, author change density, test coverage delta, and historic component flakiness to output a real-time risk score ($R \in [0, 100]$) for every pending deployment pull request.
  • Executive Quality Scorecards & Automated Guardrails: Designed interactive executive dashboards in Apache Superset that tracked DORA metrics across teams, automatically triggering deployment blocks for feature branches attempting to release with elevated risk scores or unresolved blocking defects.

Result

  • Reduced production Change Failure Rate by 45% over two quarters through proactive risk-based deployment gating.
  • Provided executive transparency across all 30 engineering teams with real-time quality analytics and automated governance.