# etsy/skyline

It'll detect your anomalies! Part of the Kale stack.

Repository: https://github.com/etsy/skyline
Canonical: https://ross.abutalabs.com/products/skyline
Homepage: http://codeascraft.com/2013/06/11/introducing-kale/
Language: Python
License: NOASSERTION
License Family: other
Topics: non-sox
Archived: true
Last push: 2016-02-22T14:22:44+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4832, "days_push": 3845, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2129, forks 329 (observed 2026-08-28T04:06:17.057804+00:00)

## What it is
Skyline is a real-time anomaly detection system for passively monitoring hundreds of thousands of high-resolution time series metrics without per-metric configuration. It ingests metric streams from sources like StatsD or Graphite, automatically analyzes them for anomalies, and surfaces results via a webapp with alerting support.

## Use cases
- detect anomalies in server metrics automatically
- monitor hundreds of thousands of time series without configuring thresholds
- surface anomalous metrics from statsd or graphite streams
- get alerts when a metric behaves abnormally
- passive real-time monitoring of high-resolution timeseries

## When to choose
- you have a large volume of high-resolution time series metrics and no per-metric thresholds
- you want automatic anomaly detection on a statsd or graphite metric stream
- you need a self-hosted anomaly detection pipeline with a web UI and alerting

## When to avoid
- you need actively maintained software with recent fixes and support
- you want a modern anomaly detection stack with current Python dependencies
- you need a managed or cloud-native monitoring solution

## Facets
- artifact type: application
- maturity: abandoned
- function: monitoring, alerting, analytics, data-science
- domain: monitoring, analytics, time-series
- platform: python, self-hosted
- tags: anomaly-detection, time-series, real-time, metrics, redis, graphite, statsd, archived, devops, linux

## Member repositories
- etsy/skyline (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:17.057804+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 2026-08-30T02:52:24.605381+00:00, confidence not recorded.
  - readme: https://github.com/etsy/skyline (fetched 2026-08-28T04:06:17.057804+00:00, sha a3070a748b78)
- Data as of 2026-08-30T08:39:29.467469+00:00.