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