add worked skyline fork, add some recipes for Clickhouse and Prometheus (#10)

* add worked skyline fork, add some recipes for Clickhouse and Prometheus

* Replace Skyline, remove articles

I opted to remove the unsupported Skyline altogether, and replace it with the supported fork.
As for the articles, for now I'd prefer to keep the repo focused on tools - e.g. software or datasets. If in the future I have a substantial collection of useful articles I might add a section for those as well. Thanks for the PR!

* Remove floating char

Co-authored-by: Roberto <[email protected]>

Author: Slach

README.md

@@ -27,7 +27,7 @@ A repository is considered "not maintained" if the latest commit is > 1 year old
 | [oddstream](https://github.com/pridiltal/oddstream)| R | oddstream (Outlier Detection in Data Streams) provides real time support for early detection of anomalous series within a large collection of streaming time series data. | GPL-3 |  :heavy_check_mark:
 | [PyOdds](https://github.com/datamllab/pyodds)| Python | PyODDS is an end-to end Python system for outlier detection with database support. PyODDS provides outlier detection algorithms, which support both static and time-series data.  | MIT |  :heavy_check_mark:
 | [rrcf](https://github.com/kLabUM/rrcf) | Python | Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams. | MIT |  :heavy_check_mark:
-| Etsy's [Skyline](https://github.com/etsy/skyline)                        | Python |Skyline is a real-time anomaly detection system, built to enable passive monitoring of hundreds of thousands of metrics. | MIT  | ❌ 
+| EarthGecko [Skyline](https://github.com/earthgecko/skyline)              | Python3 | Skyline is a real-time anomaly detection system, built to enable passive monitoring of hundreds of thousands of metrics. | MIT | :heavy_check_mark:
 | Netflix's [Surus](https://github.com/netflix/surus)                      | Java   |Robust Anomaly Detection (RAD) - An implementation of the Robust PCA.   | Apache-2.0 | ❌ 
 | NASA's [Telemanom](https://github.com/khundman/telemanom)| Python | A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.  | [custom](https://github.com/khundman/telemanom/blob/master/LICENSE.txt) |  :heavy_check_mark: