Systems exhibition

Diagnostic workflow · Structured analysis

Log Intelligence Tool

A rule-driven analysis service that correlates database traces, kernel errors, and Java stack traces into structured root-cause reports.
Java 17Spring BootPostgreSQLRESTDockerPrometheusGrafanaOpenTelemetry
ORA-00600 → KERNELdeadlock → CONCURRENCYGC overhead → MEMORY
logsparsepatternsdiagnostics
01 / Problem

The constraint.

Production incident triage means correlating signals that live in different places — application logs, database traces, kernel errors — and doing it manually under time pressure.

02 / Architecture

How it is shaped.

A Spring MVC API feeds type detection, specialized parsers, pattern matching, layer classification, and root-cause analysis. Uploaded files run on a bounded async executor; PostgreSQL stores history.

03 / How it works

Decisions made explicit.

  • Format-specific parsers behind one pipeline
  • Async file processing with pollable status
  • Deterministic patterns and explainable remediation text
04 / Failure thinking

Where it can break.

Uploads begin as PENDING and transition to COMPLETED or FAILED. Validation and structured API errors keep bad inputs out of the parser pipeline.

05 / Reflection

What I learned.

Diagnostic automation is credible when every conclusion can be traced back to evidence in the input.

Inspect the sourceLog Intelligence Tool on GitHub