
Marcello Alexandre enhanced observability for the weni-ai/flows Django application by implementing Prometheus-based monitoring and introducing a secure, authenticated /metrics endpoint. He integrated middleware to collect real-time metrics, enabling faster incident response and improved system reliability. Using Python and Django, Marcello updated dependencies and incorporated Poetry for deterministic builds and reproducible deployments. He also addressed minor import path and code quality issues to ensure seamless operation of the new monitoring features. This work provided the foundation for proactive alerting and dashboarding, reducing mean time to recovery and strengthening the backend’s monitoring capabilities through robust API development and system monitoring practices.

In April 2025, delivered Prometheus-based observability enhancements for the weni-ai/flows Django app, adding a secure /metrics endpoint, middleware-based collection, and dependency updates to support the feature. This enables real-time visibility, faster incident response, and stronger reliability. Minor fixes to import paths and typos were addressed to ensure smooth operation, with poetry.lock added for deterministic builds and reproducible deployments. Overall, the work strengthens monitoring, reduces MTTR, and positions the service for proactive alerting and dashboards.
In April 2025, delivered Prometheus-based observability enhancements for the weni-ai/flows Django app, adding a secure /metrics endpoint, middleware-based collection, and dependency updates to support the feature. This enables real-time visibility, faster incident response, and stronger reliability. Minor fixes to import paths and typos were addressed to ensure smooth operation, with poetry.lock added for deterministic builds and reproducible deployments. Overall, the work strengthens monitoring, reduces MTTR, and positions the service for proactive alerting and dashboards.
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