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2024 / Internal ops tooling

BetterLogs

A log analysis tool built to cut through operational noise and turn large log volumes into usable answers quickly.

Stack

Python / FastAPI / Parsing / Internal tooling

Proof

Recognition for internal impact

Overview

BetterLogs was built for a real operational bottleneck: teams were wasting time digging through heavy log files manually when what they actually needed was a fast path from symptom to likely cause.

Problem

What needed to change.

Large log files were slowing down debugging and forcing engineers into repetitive manual triage. The job was not to store more logs, but to shorten the path from noise to usable answers.

Constraints

The edges that shaped the solution.

  • The workflow had to be useful during real incidents, not just for clean demo scenarios.
  • The interface needed to reduce cognitive load rather than adding another observability surface.
  • Querying and summarization had to stay fast enough to be trusted under pressure.

What I owned

The parts I was directly responsible for.

  • Product shaping around the real debugging workflow
  • Backend design for ingestion and query performance
  • Response design focused on operational readability

Key decisions

Choices that defined the project shape.

  • Optimized for fast ingestion and focused querying rather than broad observability features.
  • Kept the output surface narrow so the tool answered likely causes instead of overwhelming users with raw detail.
  • Designed the system as a practical internal tool, not a platform trying to look complete.

Outcome

What changed after the work shipped.

The tool reduced time-to-answer during debugging work, gave teams a faster path to likely root causes, and was recognized internally for the value it created.

  • Improved speed from symptom to likely cause
  • Recognized internally for engineering impact
  • Built around a real operational bottleneck instead of a generic feature set