# onebirdrocks/geektime-ELK

ELK Training

Repository: https://github.com/onebirdrocks/geektime-ELK
Canonical: https://ross.abutalabs.com/products/geektime-elk
Language: HTML
License Family: other
Last push: 2023-12-19T11:21:15+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2627, "days_push": 988, "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 1210, forks 2480 (observed 2026-08-28T04:04:00.079500+00:00)

## What it is
Companion repository for a Chinese Geektime video course on Elasticsearch core technology and the ELK stack, containing course outlines, examples, and setup instructions. It covers search, aggregation, cluster administration, and hands-on projects like building a movie search service.

## Use cases
- learn elasticsearch from scratch
- prepare for elastic certification
- learn how to run and manage an elk stack
- understand elasticsearch cluster operations and scaling
- build a search service with elasticsearch
- learn kibana dashboards and logstash pipelines

## When to choose
- you want a structured, project-based Elasticsearch curriculum
- you are preparing for the Elastic engineer certification
- you prefer Chinese-language learning materials

## When to avoid
- you need production-ready software rather than course materials
- you want up-to-date content for the latest Elasticsearch versions
- you need English-language instruction

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: search-engine, data-visualization, etl, monitoring
- domain: big-data, developer-tools, tutorials
- platform: self-hosted, cross-platform
- tags: elasticsearch, elk-stack, kibana, logstash, course-materials, chinese-language, search, data-engineering, docker

## Member repositories
- onebirdrocks/geektime-ELK (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:00.079500+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 2026-08-30T06:18:32.079790+00:00, confidence not recorded.
  - readme: https://github.com/onebirdrocks/geektime-ELK (fetched 2026-08-28T04:04:00.079500+00:00, sha 0e88dfee188b)
- Data as of 2026-08-30T08:39:29.467469+00:00.