# ongardie/dissertation

Sources for my PhD dissertation on the Raft consensus algorithm

Repository: https://github.com/ongardie/dissertation
Canonical: https://ross.abutalabs.com/products/dissertation
Language: TeX
License: NOASSERTION
License Family: other
Topics: raft
Last push: 2016-05-24T23:22:04+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4375, "days_push": 3753, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1082, forks 131 (observed 2026-08-28T04:03:30.930649+00:00)

## What it is
Source materials and pre-built PDFs for Diego Ongaro's 2014 Stanford PhD dissertation 'Consensus: Bridging Theory and Practice', the definitive reference on the Raft consensus algorithm. It includes LaTeX sources, figures, and errata, buildable with make, pdflatex, bibtex, and Inkscape.

## Use cases
- learn how the raft consensus algorithm works
- read the original raft dissertation
- cite raft in a distributed systems paper
- reformat raft dissertation sections for other documents
- study cluster membership change algorithms
- find errata and updates to the raft specification

## When to choose
- you want the authoritative, in-depth explanation of Raft from its creator
- you need citable source material on consensus algorithm design
- you want to reuse or reformat dissertation content under CC-BY

## When to avoid
- you need a runnable Raft implementation or library
- you want a short tutorial rather than a full dissertation
- you need actively maintained protocol documentation

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, markdown
- domain: microservices, tutorials
- platform: cross-platform
- tags: raft, consensus, dissertation, latex, phd-thesis, algorithms

## Member repositories
- ongardie/dissertation (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:30.930649+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:51:17.232654+00:00, confidence not recorded.
  - readme: https://github.com/ongardie/dissertation (fetched 2026-08-28T04:03:30.930649+00:00, sha b962be5c8b3e)
- Data as of 2026-08-30T08:39:29.467469+00:00.