Bank BRI

Python-based test automation for critical banking APIs at Bank BRI. Automated functional, regression, and load testing plus reporting, keeping core financial endpoints stable under production-scale traffic.

Role

QA Automation

Duration

April 2026 - Present

Client

Bank BRI (Vendor under IGLO)

Impact

Results

Efficiency

Cut manual reporting effort by roughly 80 percent through the custom reporter and Confluence automation.

Stability

Validated stability up to 175 TPS at production scale.

Automated

Automated functional, regression, and performance testing across critical APIs.

Monitoring

Surfaced bottlenecks early using Grafana and Elastic APM.

The Problem

High-volume banking APIs needed verification for correctness and stability before release. Testing and reporting were manual, making the process slow, error-prone, and hard to repeat across releases.

The Solution

Built a Python suite automating functional and regression testing, including JSON response validation, PDF-to-baseline comparison, and field checks against prior versions.

Added JMeter and Locust load tests and automated the full reporting pipeline.

System Design

Python drives functional and regression tests auto-publishes to Confluence, with Postman for manual checks.

JMeter and Locust handle load testing, feeding a custom JTL reporter

Everything runs across AWS and GCP, using S3 for artifacts and Systems Manager for bastion access.

Test data is pulled from banking databases via SSMS.

Grafana with Elastic APM monitors resources during performance testing runs.

Challenges

Test data had to come from the correct source across multiple databases.

Multi-step request, cancel, and status flows had to be sequenced reliably to test correctly.

Load tests needed to simulate real production pressure up to 175 TPS on critical endpoints.