Production · SaaS LegalTech
One view of data and bugs across 5 SaaS products
Airflow pipelines on AWS and a real-time Power BI × Sentry dashboard that took bug detection from hours to minutes.
- 5SaaS apps consolidated
- ~12KPIs in real time
- h → minbug detection time
Architecture
- 015 SaaS appslogs · usage · customers
- 02Sentry APIerrors & issues
- 03Airfloworchestration on EC2
- 04S3consolidated data lake
- 05Power BI~12 KPIs, self-service
Context
VirtuoSys builds several LegalTech SaaS applications. Each one produced its own logs, customer data and usage metrics — in different shapes, in different places — and bugs were reported by hand.
The challenge
Give product and engineering teams one reliable, real-time view of usage and errors across five products — without compromising GDPR obligations on customer data.
What I built
- Airflow DAGs on AWS EC2 that extract logs, customer records and usage metrics from 5 heterogeneous applications and land them in S3.
- A Power BI ↔ Sentry API integration powering a self-service dashboard: 3 pages, 5 projects, ~12 KPIs, refreshed in real time.
- GDPR compliance designed in from the start rather than patched on afterwards.
- GitLab CI/CD to ship pipeline changes safely, plus the documentation and data-governance conventions the team now works with.
Outcomes
- 01Bug detection went from several hours to a few minutes.
- 02Manual bug reporting replaced by a self-service dashboard.
- 03One consolidated dataset across 5 products instead of 5 silos.
Stack
- Airflow
- AWS S3
- AWS EC2
- Python
- SQL
- Power BI (DAX)
- Sentry API
- GitLab CI/CD
- Docker
Facing a similar problem?
I’m happy to talk it through — whether you’re hiring or need a freelance mission.