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ChargeSmart Insight

ChargeSmart Insight

Observability Dashboard

Built a real-time observability platform from scratch monitoring 70+ pipelines across 7 countries, integrated into the existing production stack.

70+

Pipelines monitored

Across 7 countries

Hours → mins

Incident detection

Via automated Slack alerts

2 weekends

Time to ship

End-to-end, from scratch

~90%

AI-written code

Using agentic coding workflows

About this project

Built a real-time observability platform entirely from scratch and integrated it into the existing ChargeSmart Insight production stack, covering data modelling, backend monitoring, a React dashboard, and Slack alerting.

The trigger was clear: incidents were discovered through manual checks and user reports, which meant failures sat undetected for hours. The goal was to make the system aware of itself.

I owned every layer: designed the data model to capture pipeline health across 7 countries, built the backend monitoring logic, wired up automated Slack notifications, and shipped a React dashboard surfacing live pipeline status and trends.

Shipped the entire system in 2 weekends. Around 90% of the codebase was written using AI agentic coding workflows, which compressed what would normally be a multi-week effort into two intense sessions.

The outcome was immediate: incident detection dropped from hours to minutes, data leaks and pipeline failures were surfaced proactively before reaching end users, and manual monitoring was eliminated entirely.

Tech stack

TypeScriptReactPythonPostgreSQLSlack APIAWS LambdaGitHub Actions

Key achievements

70+ pipelines monitored across 7 countries

Designed a data model and monitoring layer covering the full pipeline fleet, spanning every active market.

Hours → minutes incident detection

Automated Slack alerting replaced manual checks and user reports. The team now knows about failures before end users do.

Shipped in 2 weekends

Full system (data model, backend, dashboard, alerting) delivered in two focused weekends with ~90% of the code written via AI agentic coding workflows.

Proactive leak and failure detection

Surfaced data leaks and pipeline failures before they reached end users, turning reactive firefighting into proactive monitoring.

Screenshots