Improve readme

- Added background section
- Added table of Contents section
- Added install section
- Added usage section
- Added contribute section

1 files changed, 61 insertions, 18 deletions

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@@ -1,20 +1,70 @@
 <!-- Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -->
-# Vespa
-Vespa is an engine for low-latency computation over large data sets.
-It stores and indexes your data such that queries, selection and processing over the
-data can be performed at serving time.
 
-This README describes how to build and develop the Vespa engine. To get started, read the
-[quick start](http://docs.vespa.ai/documentation/vespa-quick-start.html), or find the full
-documentation at http://docs.vespa.ai/.
+[![#Vespa](https://vespa.ai/img/VespaLogoBlack.png)](https://vespa.ai)
+
+The big data serving engine - Store, search, rank and organize big data at user serving time.
+Vespa is an engine for low-latency computation over large data sets.
+It stores and indexes your data and executes distributes queries including evaluation of
+machine-learned models over many data points in real time.
 
 Code licensed under the Apache 2.0 license. See [LICENSE](LICENSE) for terms.
 
 Travis-CI build status: [![Build Status](https://travis-ci.org/vespa-engine/vespa.svg?branch=master)](https://travis-ci.org/vespa-engine/vespa)
 
-## Get started developing
+## Table of contents
+
+- [Background](#background)
+- [Install](#install)
+- [Usage](#usage)
+- [Contribute](#contribute)
+- [Building](#building)
+   
+## Background
+
+Use cases such and search, recommendation and personalization need to select a subset of data in a large corpus,
+evaluate machine-learned models over the selected data, organize and aggregate it and return it, typically in less
+than 100 milliseconds, all while the data corpus is continuously changing. 
+
+This is hard to do, especially with large corpuses that needs to be distributed over multiple nodes and evaluated in 
+parallel. Vespa is is a platform which performs these operations for you. It has been in development for many years 
+and is used on a number of large internet services and apps which serve hundreds of thousands of queries from 
+Vespa per second.
+
+## Install
+
+To get started using Vespa pick one of the quick start documents:
+
+- [Run on a Mac or Linux machine using Docker](https://docs.vespa.ai/documentation/vespa-quick-start.html)
+- [Run on a Windows machine using Docker](https://docs.vespa.ai/documentation/vespa-quick-start-windows.html)
+- [Run on a Mac or Linux machine using VirtualBox+Vagrant](https://docs.vespa.ai/documentation/vespa-quick-start-centos.html)
+- [Multinode install on AWS EC2](https://docs.vespa.ai/documentation/vespa-quick-start-multinode-aws.html)
+- [Multinode install on AWS ECS](https://docs.vespa.ai/documentation/vespa-quick-start-multinode-aws-ecs.html)
+
+## Usage 
+
+- The application created in the quickstart is fully functional and production ready, but you may want to [add more nodes](https://docs.vespa.ai/documentation/multinode-systems.html) for redundancy.
+- Try the [Blog search and recommendation tutorial](https://docs.vespa.ai/documentation/tutorials/blog-search.html) to learn more about using Vespa
+- See [developing applications](https://docs.vespa.ai/documentation/jdisc/developing-applications.html) on adding your own Java components to your Vespa application.
+- [Vespa APIs](https://docs.vespa.ai/documentation/api.html) is useful to understand how to interface with Vespa
+- Explore the [sample applications](https://github.com/vespa-engine/sample-apps/tree/master)
+
+Full documentation is available on [https://docs.vespa.ai](https://docs.vespa.ai).
+
+## Contribute
+
+We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) to learn how to contribute.
+
+If you want to contribute to the documentation, see
+[https://github.com/vespa-engine/documentation](https://github.com/vespa-engine/documentation)
+
+
+## Building
+
+You do not need to build Vespa to use it, but if you want to contribute you need to be able to build the code.
+This section explains how to build and test Vespa.
+
+### Set up the build environment
 
-### Setup build environment
 C++ and Java building is supported on CentOS 7. The Java source can also be built on any platform having Java 8 and Maven installed. 
 We recommend using the following environment: [Create C++ / Java dev environment on CentOS using VirtualBox and Vagrant](vagrant/README.md).
 You can also setup CentOS 7 natively and install the following build dependencies:
@@ -33,6 +83,7 @@ You can also setup CentOS 7 natively and install the following build dependencie
     mvn -T <num-threads> install
 
 ### Build C++ modules
+
 Replace `<build-dir>` with the name of the directory in which you'd like to build Vespa.
 Replace `<source-dir>` with the directory in which you've cloned/unpacked the source tree.
 
@@ -42,13 +93,5 @@ Replace `<source-dir>` with the directory in which you've cloned/unpacked the so
     ctest3 -j <num-threads>
 
 ### Create RPM packages
-    sh dist.sh VERSION && rpmbuild -ba ~/rpmbuild/SPECS/vespa-VERSION.spec
 
-
-## Run Vespa on a local machine
-A basic, single-node install is found in the 
-[quick start](http://docs.vespa.ai/documentation/vespa-quick-start.html).
-For multi-node and using Node Admin, read [node-admin/README.md](node-admin/README.md).
-
-## Write documentation
-Update user documentation at https://github.com/vespa-engine/documentation
+    sh dist.sh VERSION && rpmbuild -ba ~/rpmbuild/SPECS/vespa-VERSION.spec