The Vision
Most tutorials teach you how to build a system when everything goes right. The Backend Engineering Simulator teaches you what to do when everything goes wrong.
This portfolio version is a compact browser-native scenario inspired by the larger Backend Engineering Lab project. It does not connect to live infrastructure; the logs, metrics, dependency health, and command responses are scripted to demonstrate the investigation workflow.
The full lab is designed around Spring Boot services, PostgreSQL, Redis, Kafka, Prometheus, Grafana, fault injection, scenario catalogs, dependency health, and exportable incident reports.
- Source code
- Live hosted demo: not deployed yet. The portfolio page above is the lightweight browser simulation; the full lab currently runs locally with Docker and the project scripts.
Scenario Model
The simulator follows a senior incident-response loop:
- Identify the affected user journey.
- Inspect service health and dependency boundaries.
- Collect logs, metrics, and trace evidence.
- Test a hypothesis without making the outage worse.
- Apply an immediate mitigation.
- Write the root cause and long-term remediation.
Why The Terminal Exists
Visitors do not need to open their real terminal. The browser terminal is a teaching interface. It turns backend concepts into concrete investigation actions:
statusreveals service health.logs auth-serviceexposes the failing boundary.metrics auth-db-primaryshows saturation.trace loginfollows one failed request.inspect batch-jobidentifies the upstream cause.kill batch-jobapplies mitigation.resolveprints the final RCA.
The interaction demonstrates how a backend engineer narrows a production incident from symptoms to evidence-backed diagnosis.
Connection To The Larger Lab
The local Backend Engineering Lab expands this idea into a full training platform with multiple fault-injection scenarios:
- API contract regression
- OpenAPI schema drift
- API latency degradation
- Database connection failure
- Cache stampede
- Write-path failure
- Memory leak
- Kafka consumer lag
- Saga boundary failure
- Rate limiting
The portfolio keeps one guided incident polished enough for recruiters, engineering managers, and founders to understand the engineering judgment behind the larger project.