From c3c46f41dd38c429f13b908e4e1930d0539d6f07 Mon Sep 17 00:00:00 2001 From: Sharat Sharma Date: Wed, 8 Feb 2017 01:32:24 +0530 Subject: [PATCH] Added overview document for meteos Adding the overview document and changed a few documents to make the docs better. Change-Id: Ia1fd7f037f85cc1363678f16232c1d9371fdb292 Partial-Implements: blueprint meteos-docs --- README.rst | 38 +++++++++++++++++++++----------- doc/source/index.rst | 48 ++++++++--------------------------------- doc/source/overview.rst | 36 +++++++++++++++++++++++++++++++ 3 files changed, 71 insertions(+), 51 deletions(-) create mode 100644 doc/source/overview.rst diff --git a/README.rst b/README.rst index 4f7f984..25d24e9 100644 --- a/README.rst +++ b/README.rst @@ -1,27 +1,41 @@ +======================== +Team and repository tags +======================== + +.. image:: http://governance.openstack.org/badges/mistral.svg + :target: http://governance.openstack.org/reference/tags/index.html + ====== Meteos ====== +.. image:: https://img.shields.io/pypi/v/meteos.svg + :target: https://pypi.python.org/pypi/meteos/ + :alt: Latest Version + +.. image:: https://img.shields.io/pypi/dm/meteos.svg + :target: https://pypi.python.org/pypi/meteos/ + :alt: Downloads + You have come across an OpenStack Machine Learning service. It has identified itself as "Meteos." It was abstracted from the Manila project. -* Wiki: https://wiki.openstack.org/Meteos -* Developer docs: http://docs.openstack.org/developer/meteos +Project Resources +----------------- -Getting Started ---------------- +* `Meteos Official Documentation `_ -If you'd like to run from the master branch, you can clone the git repo: +* Project status, bugs, and blueprints are tracked on + `Launchpad `_ - git clone https://github.com/openstack/meteos.git +* Additional resources are linked from the project + `Wiki `_ page -For developer information please see -`HACKING.rst `_ +* Apache License Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 -You can raise bugs here http://bugs.launchpad.net/meteos +* `Source Code `_ -Python client -------------- +* For developer information please see `HACKING.rst `_ -https://github.com/openstack/python-meteosclient.git +* `Python Client `_ diff --git a/doc/source/index.rst b/doc/source/index.rst index 228997b..f12d15b 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -1,50 +1,20 @@ -.. - Copyright 2010-2012 United States Government as represented by the - Administrator of the National Aeronautics and Space Administration. - All Rights Reserved. - - Licensed under the Apache License, Version 2.0 (the "License"); you may - not use this file except in compliance with the License. You may obtain - a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, WITHOUT - WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the - License for the specific language governing permissions and limitations - under the License. - -Welcome to Meteos's developer documentation! -============================================ +Welcome to Meteos's documentation! +================================== Meteos is an OpenStack project to provide "Machine Learning as a service". +Meteos allows users to analyze huge amount of data and predict a value by data +mining and machine learning algorithms. Meteos create a workspace of Machine +Learning via sahara spark plugin and manage some resources and jobs regarding +Machine Learning. -* **Component based architecture**: Quickly add new behaviors -* **Highly available**: Scale to very serious workloads -* **Fault-Tolerant**: Isolated processes avoid cascading failures -* **Recoverable**: Failures should be easy to diagnose, debug, and rectify -* **Open Standards**: Be a reference implementation for a community-driven api -* **API Compatibility**: Meteos strives to provide API-compatible with popular systems like Amazon EC2 - -This documentation is generated by the Sphinx toolkit and lives in the source -tree. Additional draft and project documentation on Meteos and other components of OpenStack can -be found on the `OpenStack wiki`_. Cloud administrators, refer to `docs.openstack.org`_. - -.. _`OpenStack wiki`: http://wiki.openstack.org -.. _`docs.openstack.org`: http://docs.openstack.org - - -Developer Docs -============== +Overview +======== .. toctree:: :maxdepth: 1 + overview architecture - devref/index - man/index - api/autoindex Admin Docs ========== diff --git a/doc/source/overview.rst b/doc/source/overview.rst new file mode 100644 index 0000000..1456556 --- /dev/null +++ b/doc/source/overview.rst @@ -0,0 +1,36 @@ +Meteos Overview +============== + +What is Meteos? +~~~~~~~~~~~~~~~ + +Meteos is an OpenStack project to provide "Machine Learning as a service". + +* **Component based architecture:** Quickly add new behaviors +* **Highly available:** Scale to very serious workloads +* **Fault-Tolerant:** Isolated processes avoid cascading failures +* **Recoverable:** Failures should be easy to diagnose, debug, and rectify +* **Open Standards:** Be a reference implementation for a community-driven api +* **API Compatibility:** Meteos strives to provide API-compatible with popular systems like Amazon EC2 + + +Main use cases +~~~~~~~~~~~~~~ + +Machine Learning consists of the following phases. + +* **Learning Phase** - Analyze huge amounts of data and create a Prediction Model +* **Prediction Phase** - Predict a value according to the input value by using Prediction Model + +Use case in Learning Phase +-------------------------- + +* Upload Raw Data - Upload a raw data to Object Storage +* Parse Raw Data - Parse a raw data to enable MLllib (Apache Spark's scalable + machine learning library) to handle it. Users are allowed to parse the parsed data again. +* Create Prediction Model - Create a Prediction Model by using MLlib + +Use case in Prediction Phase +---------------------------- + +* Predict - Input any value and retrieve predicted value