# Docklet 

http://docklet.unias.org

## intro

Docklet is an operating system for mini-datacener. Its goal is to help
multi-user share cluster resources effectively. Unlike the "application
framework oriented" cluster manager such as Mesos and Yarn, Docklet is
**user oriented**. In Docklet, every user has their own private
**virtual cluster (vcluster)**, which consists of a number of virtual
Linux container nodes distributed over the physical cluster. Every
vcluster is separated from others and can be operated like a real
physical cluster. Therefore, most applications, especially those
requiring a cluster environment, can run in vcluster seamlessly. 

Docklet provides a base image for creating virtual nodes. This image has
pre-installed a lot of mainstream development tools and frameworks,
including gcc/g++, openjdk, python3, R, MPI, scala, ruby, php, node.js,
texlive, mpich2, spark,
scipy/numpy/matplotlib/pandas/sympy/scikit-learn, jupyter notebook, etc.
Users can get a ready vcluster with just one click within 1 second.

The users are free to install their specific software in their vcluster.
Docklet supports operating through **web terminal**. Users can do their
work as an administrator working on a console. The base image system is
ubuntu. The recommended way of installing new software is by
**apt-get**.

The users manage and use their vcluster all through web. The only client
tool needed is a modern web browser, like safari, firefox, chrome. The
integrated *jupyter notebook* provides a web workspace. By visiting the
workspace, users can do coding, debugging and testing of their programs
online. The **python scipy** series of tools can even display graphical
pictures in the browser. Therefore, it is ideal for data analysis and
processing.

Docklet only need **one** public IP address. The vclusters are
configured to use private IP address range, e.g., 172.16.0.0/16,
192.168.0.0/16, 10.0.0.0/8. A proxy is setup to help
users visit their vclusters behind the firewall/gateway. 

The Docklet system runtime consists of four components:

- distributed file system server
- etcd server
- docklet master
- docklet worker

## install

Currently the docklet runtime is recommend to run in Unbuntu 15.10+.

Ensure that python3.5 is the default python3 version.

Unpack the docklet tarball to a directory ( /root/docklet as an
example), will get

```
readme.md
prepare.sh
conf/
    container.conf
    docklet.conf.template
    lxc-script/
bin/
    docklet-master
    docklet-worker
src/
    httprest.py
    worker.py
    ...
web/
    web.py
dep/
    etcd-multi-nodes.sh
    etcd-one-node.sh
doc/
tools/
    update-basefs.sh
    start_jupyter.sh
```

If it is the first time install, users should run **prepare.sh** to
install necessary packages automatically. Note it may need to run this 
script several times to successfully install all the needed packages.

A *root* users will be created for managing the system. The password is
recorded in `FS_PREFIX/local/generated_password.txt` .

## config ##

The main configuration file of docklet is conf/docklet.conf. Most
default setting works for a single host environment. 

First copy docklet.conf.template to get docklet.conf.

The following settings should be taken care of:

- NETWORK_DEVICE : the network device to use. 
- ETCD : the etcd server address. For distributed muli hosts
  environment, it should be one of the ETCD public server address.
  For single host environment, the default value should be OK.
- STORAGE : using disk or file to storage persistent data, for
  single host, file is convenient.
- FS_PREFIX: the working dir of docklet runtime. default is
  /opt/docklet.
- CLUSTER_NET: the vcluster network ip address range, default is
  172.16.0.1/16. This network range should all be allocated to  and 
  managed by docklet. 
- PROXY_PORT : the public port of docklet. Users use
  this port to visit the docklet system.
- PORTAL_URL : the portal of the system. Users access the system
  by visiting this address. If the system is behind a firewall, then
  a reverse proxy should be setup.

## start ##

### distributed file system ###

For multi hosts distributed environment, a distributed file system is
needed to store global data. Currently, glusterfs has been tested. 
Lets presume the file system server export filesystem as nfs
**fileserver:/pub** :

In each physical host to run docklet, mount **fileserver:/pub** to
**FS_PEFIX/global** .

For single host environment, it need not to configure distributed
file system.

### etcd ###

For single host environment, start **dep/etcd-one-node.sh** . Some recent
Ubuntu releases have included **etcd** in the repository, just `apt-get
install etcd`, and it need not to start etcd manually.

For multi hosts distributed environment, start
**dep/etcd-multi-nodes.sh** in each etcd server hosts. This scripts
requires users providing the etcd server address as parameters.

### master ###

First, select a server with 2 network interface card, one having a
public IP address/url, e.g., docklet.info; the other having a private IP
address, e.g., 172.16.0.1. This server will be the master.

If it is the first time you start docklet, run `bin/docklet-master init`
to init and start docklet master. Otherwise, run  `bin/docklet-master start`, 
which will start master in recovery mode in background using 
conf/docklet.conf. It means docklet will recover workspaces existed.

This script in fact will start three daemons: the docklet master of
httprest.py, the configurable-http-proxy and the docklet web of web.py.

You can check the daemon status by running `bin/docklet-master status`

If the master failed to start, you could try `bin/docklet-master init`
to initialize the whole system.

More usages can be found by typing `bin/docklet-master`

The master logs are in **FS_PREFIX/local/log/docklet-master.log** and
**docklet-web.log**.

### worker ###

Worker needs a basefs image to boot container.

You can create such an image with `lxc-create -n test -t download`, 
and then copy the rootfs to **FS_PREFIX/local**, and renamed `rootfs` 
to `basefs`.

Note the `jupyerhub` package must be installed for this image.  And the 
start script `tools/start_jupyter.sh` should be placed at
`basefs/home/jupyter`.

You can check and run `tools/update-basefs.sh` to update basefs.

Run `bin/docklet-worker start`, will start worker in background.

You can check the daemon status by running `bin/docklet-worker status`

More usages can be found by typing `bin/docklet-worker`

The log is in **FS_PREFIX/local/log/docklet-worker.log**

Currently, the worker must be run after the master has been started.

## usage ##

Open a browser, visiting the address specified by PORTAL_URL , 
e.g., ` http://docklet.info/ `

If the system is just deployed in single host for testing purpose,
then the PORTAL_URL defaults to `http://MASTER_IP:PROXY_PORT`,
e.g., `http://localhost:8000`.

That is it.

## system admin ##