A cloud-enabled distributed resource manager
# Cloud Scheduler 1.10 README
## Introduction Cloud Scheduler: Automatically boot VMs for your HTC jobs
Cloud Scheduler manages virtual machines on clouds configured with OpenStack, Google Compute Engine, or Amazon EC2 to create an environment for HTC batch job execution. Users submit their jobs to a Condor job queue, and Cloud Scheduler boots VMs to suit those jobs.
For more documentation on Cloud Scheduler, please refer to:
[Cloud Scheduler Wiki](http://wiki.github.com/hep-gc/cloud-scheduler)
A working Condor 7.5.x or later install (details below)
[boto](http://code.google.com/p/boto/) for using EC2 API clouds (Amazon, OpenStack)
[OpenStack novaclient](https://pypi.python.org/pypi/python-novaclient/) for using the native OpenStack APIs
## Optional Prerequisites
[Guppy](http://guppy-pe.sourceforge.net/) – Used for memory usage info.
## Basic Steps to get Jobs Running via Cloud Scheduler
Install Prerequiste libraries
Install Cloud Scheduler & Condor
Configure Condor and Cloud Scheduler
Setup a VM Image with Condor installed & CS Condor Scripts
Add the Required CS Attributes to a job submission file
Start CS and Submit job(s)
### Quick Start for People Who Think They Know What They’re Doing
# pip install cloud-scheduler
This will install the latest master release, latest dev release available through github
### Special help for RHEL 5
Since Cloud Scheduler requires Python 2.6+, and we recognize that RHEL 5 comes with and requires Python 2.4, here’s a quick guide to getting Python installed on those systems:
Python 2.6 may be in the repos depending on your version(5.5+):
$ yum install python26 python26-distribute
For Python 2.7:
Install the tools we need to build Python and its modules:
- # yum install gcc gdbm-devel readline-devel ncurses-devel zlib-devel
bzip2-devel sqlite-devel db4-devel openssl-devel tk-devel bluez-libs-devel libxslt libxslt-devel libxml2-devel libxml2
Download and compile Python 2.7.1:
$ VERSION=2.7.1 $ mkdir /tmp/src $ cd /tmp/src/ $ wget http://python.org/ftp/python/$VERSION/Python-$VERSION.tar.bz2 $ tar xjf Python-$VERSION.tar.bz2 $ rm Python-$VERSION.tar.bz2 $ cd Python-$VERSION $ ./configure $ make $ sudo make altinstall
Now we need to install Python setuputils:
$ cd /tmp/src $ wget http://pypi.python.org/packages/2.7/s/setuptools/setuptools-0.6c11-py2.7.egg $ sudo sh setuptools-0.6c11-py2.7.egg
Now install pip to install the rest of our dependencies:
$ sudo easy_install-2.7 pip
And the rest of our dependencies:
$ sudo pip-2.7 install cloud-scheduler
Now clean everything up:
$ sudo rm -Rf /tmp/src/
Finally, once you’ve set up the rest of Cloud Scheduler, you’ll want to set your Python version in the Cloud Scheduler init script, or use virtualenv. Do this by changing the PYTHON variable to /opt/bin/python
### Other distros:
You can install the Python libraries listed above with pip:
lxml requires libxml2 and libxslt and their development libs to be installed.
# easy_install pip
And Cloud Scheduler and its dependencies:
# pip install cloud-scheduler
## Install without pip To install without using pip:
Download the zip from github
# wget https://github.com/hep-gc/cloud-scheduler/archive/master.zip # unzip master.zip # cd cloud_scheduler # python setup.py install
## Condor Install Cloud Scheduler works with [Condor](http://www.cs.wisc.edu/condor/), which needs to be installed and able to manage resources. You must install it on the same machine that runs Cloud Scheduler.
We recommend the following settings, especially if you’re planning on using Condor CCB:
UPDATE_COLLECTOR_WITH_TCP=True COLLECTOR_SOCKET_CACHE_SIZE=10000 COLLECTOR.MAX_FILE_DESCRIPTORS = 10000
We have also placed an example Condor config in scripts/condor/manager
Make sure you can run condor_status and condor_q, and make sure your [HOST]ALLOW_WRITE will permit the VMs you will start to add themselves to your Condor Pool.
## Preparing VM Images
The VM images you would like to run jobs with need to be prepared to join your Condor pool. Cloud Scheduler will do most of the heavy lifting for you, but at the very least, you need to install Condor, and configure it as a worker that will join your Condor pool. The easiest way to do this is use the example configuration (at least as inspiration) from scripts/condor/worker/ . You’ll want to put these in your /etc/condor directory. You will probably also want to use our custom Condor init script. This does things like set up an appropriate environment for when Condor is started with private networking only, when started on EC2, and also will automatically point your node to your Condor Pool. When using the custom init script and doing offline testing of the VM image, ensure you place the central_manager file from scripts/condor/worker into /etc/condor as the init script will read the value of the CONDOR_HOST from this file.
The Cloud Scheduler configuration file allows you to configure most of its functionality, and you’ll need to open it up to get a usable installation. All of its options are described inline in the example configuration file cloud_scheduler.conf, which is included with Cloud Scheduler.
By default, the Cloud Scheduler setup script installs its configuration files to /etc/cloudscheduler/, but you can manually select a different configuration by running cloud_scheduler with the -f option. If you’re running as a non-root user, Cloud Scheduler will also check for config files in ~/.cloud_scheduler/
Cloud Scheduler checks for config files in the following order, and will use the first one it finds:
[config specified with the -f option] ~/.cloudscheduler/cloud_scheduler.conf /etc/cloudscheduler/cloud_scheduler.conf /usr/local/share/cloud-scheduler/cloud_scheduler.conf
#### cloud init files
Cloud Scheduler has a default cloud config file included with the installation, it should be located in /usr/local/share/cloud-scheduler/default.yaml if you’ve installed from pip. The location can be set in the cloud_scheduler.conf file. Additional customization can be done by users by setting an AMIConfig list of cloud init files along with their jobs.
The cloud resource configuration file, cloud_resources.conf, is where you define which clouds Cloud Scheduler should use for starting VMs. You’ll specify how many VMs you want to boot on each cloud, and what it’s capabilities are. The best way to get familiar with this file is to open up the sample cloud_resources.conf file, where all of its configuration options, and a sample configuration are included.
Like cloud_scheduler.conf, the Cloud Scheduler setup script installs this file in /etc/cloudscheduler/, but you can manually select a different configuration by running cloud_scheduler with the -c option. You can also specify the location of this file with the cloud_resource_config option in the cloud_scheduler.conf file.
## Init Script There is a cloud scheduler init script at scripts/cloud_scheduler. To install it on systems with System V style init scripts, you can do so with:
# cp scripts/cloud_scheduler /etc/init.d/
if you’ve installed from pip
# cp /usr/local/share/cloud-scheduler/cloud_scheduler.init.d /etc/init.d/cloud_scheduler # cp /usr/local/share/cloud-scheduler/cloud_scheduler.sysconf /etc/sysconfig/cloud_scheduler
Start it with:
# /etc/init.d/cloud_scheduler start
On Red Hat-like systems you can enable it to run at boot with:
# chkconfig cloud_scheduler on
NOTE: If you’ve used a non-default Python, you may need to set the PYTHON variable in the init script. If you’ve installed in a non-default location, you may need to set your EXECUTABLEPATH variable.
To Stop Cloud Scheduler without it shutting down VMs (Current VMs will be saved to the persistence file specified in the cloud_scheduler.conf and get reloaded when Cloud Scheduler is started - Note that loading the VMs from persistence may take awhile)
# /etc/init.d/cloud_scheduler forcekill
To Reload the cloud_resources.conf without restarting Cloud Scheduler
# /etc/init.d/cloud_scheduler reconfig
## Configuring a VM for EC2
(Deprecated - use cloud-init and amiconfig files) The way Cloud Scheduler manipulates Condor to connect to the correct central manager is by writing files which are read by the Condor init script to configure itself. Nimbus supports this out of the box, but EC2 requires a helper script to accomplish this. This section explains how to install it.
Install the EC2 Context Helper script to your machine. This is a part of the Cloud Scheduler release tarball, and is in the scripts/ec2contexthelper/ directory.
# /etc/init.d/cloud_scheduler start # cd scripts/ec2contexthelper/ # python setup.py install # which contexthelper # /usr/bin/contexthelper # chkconfig context on
## Job Submission
Submitting a job for use with Cloud Scheduleris very similar to submitting a job for use with a regular Condor Scheduler. It would be helpful to read through Chapter 2 of the Condor Manual for help on submitting jobs to Condor.
Jobs meant to be run by VMs started by Cloud Scheduler need a few extra parameters to work properly. These are: (Required parameters are highlighted)
Requirements = VMType =?= “your.vm.type” : The type of VM that the job must run on. This is a custom attribute of the VM advertised to the Condor central manager. It should be specified on the VM’s condor_config or condor_config.local file.
VMLoc or VMAMI : The URL (for Nimbus) or AMI (for EC2-like clusters) of the image required for the job to run
VMCPUArch : The CPU architecture that the job requires. x86 or x86_64. Defaults to x86.
VMCPUCores : The number of CPU cores for the VM. Defaults to 1.
VMStorage : The amount of scratch storage space the job requires. (Currently ignored on EC2-like Clusters)
VMMem : The amount of RAM that the VM requires.
VMNetwork : The type of networking required for your VM. Only used with Nimbus. Corresponds to Nimbus’s network pool.
VMInstanceType : The EC2 instance type of the VM requested. Only used with EC2 clouds like Amazon.
VMMaximumPrice : The maximum price in cents per hour for a VM (EC2 Only)
VMKeepAlive : Number of minutes a VM should stay up after job finishes
VMHighPriority : 1 (Optional flag) Indicates a high priority job to Cloud Scheduler – high priority job support can be enabled in the cloud_scheduler.conf
TargetClouds : A comma separated list of names of clouds that you would like your job to use
CSMyProxyServer : The hostname of the myproxy server you’d like to use for credential renewal
CSMyProxyCredsName : The name of your myproxy credentials
VMJobPerCore : bool – Assigns multiple slots to a multi-core VM
### A Sample Job
# Regular Condor Attributes Universe = vanilla Executable = script.sh Arguments = one two three Log = script.log Output = script.out Error = script.error should_transfer_files = YES when_to_transfer_output = ON_EXIT # # Cloud Scheduler Attributes Requirements = VMType =?= “vm.for.script” +VMLoc = “http://repository.tld/your.vm.img.gz” +VMAMI = “ami-dfasfds” +VMCPUArch = “x86” +VMCPUCores = “1” +VMNetwork = “private” +VMMem = “512” +VMStorage = “20” Queue
## Using Proxy Certificates
For a more secure, but more complicated setup allowing your users to use their own proxy certificates, there is a guide on the heprc wiki:
This program is free software; you can redistribute it and/or modify it under the terms of either:
a) the GNU General Public License as published by the Free Software Foundation; either version 3, or (at your option) any later version, or
the Apache v2 License.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See either the GNU General Public License or the Apache v2 License for more details.
You should have received a copy of the Apache v2 License with this software, in the file named “LICENSE”.
You should also have received a copy of the GNU General Public License along with this program in the file named “COPYING”. If not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA or visit their web page on the internet at http://www.gnu.org/copyleft/gpl.html.
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.