A serverless, data-driven Git metrics dashboard using Amazon Quick Sight

What happened

You won’t know whether AI is speeding things up, only padding the commit counts, or quietly introducing quality issues you did not expect. Git activity is one of the richest signals engineering teams produce that can provide continuous observability into development analytics.

The challenge is extracting these Git metrics at scale, which has traditionally required hand-rolled extract, transform, and load (ETL) jobs, dedicated infrastructure, and ongoing maintenance. Further, with modern development tools becoming more prevalent, teams need a clear way to measure whether these tools are making developers faster, or if the investment is not paying off. What Whether you’re tracking sprint velocity, assessing release readiness, or you need visibility into team patterns, this solution provides includes near-real-time insights into your Git platform activities. If no changes are detected, the processing is skipped entirely.

Key facts

• Git activity is one of the richest signals engineering teams produce that can provide continuous observability into development analytics.
• The challenge is extracting these Git metrics at scale, which has traditionally required hand-rolled extract, transform, and load (ETL) jobs, dedicated infrastructure, and ongoing maintenance.
• Further, with modern development tools becoming more prevalent, teams need a clear way to measure whether these tools are making developers faster, or if the investment is not paying off.
• You won’t know whether AI is speeding things up, only padding the commit counts, or quietly introducing quality issues you did not expect.
• Whether you’re tracking sprint velocity, assessing release readiness, or you need visibility into team patterns, this solution — provides: near-real-time insights into your Git platform activities