Playbooks distributed with elasticluster¶
After the requested number of Virtual Machines have been started, elasticluster uses Ansible to configure them based on the configuration options defined in the configuration file.
We distribute a few playbooks together with elasticluster to configure
some of the most wanted clusters. The playbooks are available at the
share/elasticluster/providers/ansible-playbooks/
directory inside
your virtualenv if you installed using pip, or in the
elasticluster/providers/ansible-playbooks
directory of the github
source code. You can copy, customize and redistribute them freely
under the terms of the GPLv3 license.
A list of the most used playbooks distributed with elasticluster and some explanation on how to use them follows.
Slurm¶
Tested on:
- Ubuntu 12.04
- Ubuntu 13.04
- Debian 7.1 (GCE)
ansible groups | role |
---|---|
slurm_master |
Act as scheduler and submission host |
slurm_clients |
Act as compute node |
This playbook will install the SLURM queue manager using the packages distributed with Ubuntu and will create a basic, working configuration.
You are supposed to only define one slurm_master
and multiple
slurm_clients
. The first will act as login node and will run the
scheduler, while the others will only execute the jobs.
The /home
filesystem is exported from the slurm server to the compute nodes.
A snippet of a typical configuration for a slurm cluster is:
[cluster/slurm]
frontend_nodes=1
compute_nodes=5
ssh_to=frontend
setup_provider=ansible_slurm
...
[setup/ansible_slurm]
frontend_groups=slurm_master
compute_groups=slurm_clients
...
You can combine the slurm playbooks with ganglia. In this case the setup
stanza will look like:
[setup/ansible_slurm]
frontend_groups=slurm_master,ganglia_master
compute_groups=slurm_clients,ganglia_monitor
...
Gridengine¶
Tested on:
- Ubuntu 12.04
- CentOS 6.3 (except for GCE images)
- Debian 7.1 (GCE)
ansible groups | role |
---|---|
gridengine_master |
Act as scheduler and submission host |
gridengine_clients |
Act as compute node |
This playbook will install Grid Engine using the packages distributed with Ubuntu or CentOS and will create a basic, working configuration.
You are supposed to only define one gridengine_master
and multiple
gridengine_clients
. The first will act as login node and will run the
scheduler, while the others will only execute the jobs.
The /home
filesystem is exported from the gridengine server to
the compute nodes. If you are running on a CentOS, also the
/usr/share/gridengine/default/common
directory is shared from the
gridengine server to the compute nodes.
A snippet of a typical configuration for a gridengine cluster is:
[cluster/gridengine]
frontend_nodes=1
compute_nodes=5
ssh_to=frontend
setup_provider=ansible_gridengine
...
[setup/ansible_gridengine]
frontend_groups=gridengine_master
compute_groups=gridengine_clients
...
You can combine the gridengine playbooks with ganglia. In this case the setup
stanza will look like:
[setup/ansible_gridengine]
frontend_groups=gridengine_master,ganglia_master
compute_groups=gridengine_clients,ganglia_monitor
...
Please note that Google Compute Engine provides Centos 6.2 images with a non-standard kernel which is unsupported by the gridengine packages.
Ganglia¶
Tested on:
- Ubuntu 12.04
- CentOS 6.3
- Debian 7.1 (GCE)
- CentOS 6.2 (GCE)
ansible groups | role |
---|---|
ganglia_master |
Run gmetad and web interface. It also run the monitor daemon. |
ganglia_monitor |
Run ganglia monitor daemon. |
This playbook will install Ganglia monitoring tool using the packages distributed with Ubuntu or CentOS and will configure frontend and monitors.
You should run only one ganglia_master
. This will install the
gmetad
daemon to collect all the metrics from the monitored nodes
and will also run apache.
If the machine in which you installed ganglia_master
has IP
10.2.3.4
, the ganglia web interface will be available at the
address http://10.2.3.4/ganglia/
This playbook is supposed to be compatible with all the other available playbooks.
IPython cluster¶
Tested on:
- Ubuntu 12.04
- CentOS 6.3
- Debian 7.1 (GCE)
- CentOS 6.2 (GCE)
ansible groups | role |
---|---|
ipython_controller |
Run an IPython cluster controller |
ipython_engine |
Run a number of ipython engine for each core |
This playbook will install an IPython cluster to run python code in parallel on multiple machines.
One of the nodes should act as controller of the cluster
(ipython_controller
), running the both the hub and the
scheduler. Other nodes will act as engine, and will run one
“ipython engine” per core. You can use the controller node for
computation too by assigning the ipython_engine
class to it as
well.
A snippet of typical configuration for an Hadoop cluster is:
[cluster/ipython]
setup_provider=ansible_ipython
controller_nodes=1
worker_nodes=4
ssh_to=controller
...
[setup/ansible_ipython]
controller_groups=ipython_controller,ipython_engine
worker_groups=ipython_engine
...
In order to use the IPython cluster, using the default configuration, you are supposed to connect to the controller node via ssh and run your code from there.
Hadoop¶
Tested on:
- Ubuntu 12.04
- CentOS 6.3
- Debian 7.1 (GCE)
ansible groups | role |
---|---|
hadoop_namenode |
Run the Hadoop NameNode service |
hadoop_jobtracker |
Run the Hadoop JobTracker service |
hadoop_datanode |
Act as datanode for HDFS |
hadoop_tasktracker |
Act as tasktracker node accepting jobs from the JobTracker |
Hadoop playbook will install a basic hadoop cluster using the packages available on the Hadoop website. The only supported version so far is 1.1.2 x86_64 and it works both on CentOS and Ubuntu.
You must define only one hadoop_namenode
and one
hadoop_jobtracker
. Configuration in which both roles belong to the
same machines are not tested. You can mix hadoop_datanode
and
hadoop_tasktracker
without problems though.
A snippet of a typical configuration for an Hadoop cluster is:
[cluster/hadoop]
hadoop-name_nodes=1
hadoop-jobtracker_nodes=1
hadoop-task-data_nodes=10
setup_provider=ansible_hadoop
ssh_to=hadoop-name
...
[setup/ansible_hadoop]
hadoop-name_groups=hadoop_namenode
hadoop-jobtracker_groups=hadoop_jobtracker
hadoop-task-data_groups=hadoop_tasktracker,hadoop_datanode
...
GlusterFS¶
Tested on:
- Ubuntu 12.04
- CentOS 6.3
ansible groups | role |
---|---|
gluster_data |
Run a gluster brick |
gluster_client |
Install gluster client and install a gluster
filesystem on /glusterfs |
This will install a GlusterFS using all the gluster_data
nodes as
bricks, and any gluster_client
to mount this filesystem in
/glusterfs
.
Setup is very basic, and by default no replicas is set.
To manage the gluster filesystem you need to connect to a
gluster_data
node.
OrangeFS/PVFS2¶
Tested on:
- Ubuntu 12.04
ansible groups | role |
---|---|
pvfs2_meta |
Run the pvfs2 metadata service |
pvfs2_data |
Run the pvfs2 data node |
pvfs2_client |
configure as pvfs2 client and mount the filesystem |
The OrangeFS/PVFS2 playbook will configure a pvfs2 cluster. It downloads the software from the OrangeFS website, compile and install it on all the machine, and run the various server and client daemons.
In addiction, it will mount the filesystem in /pvfs2
on all the clients.
You can combine, for instance, a SLURM cluster with a PVFS2 cluster:
[cluster/slurm+pvfs2]
frontend_nodes=1
compute_nodes=10
pvfs2-nodes=10
ssh_to=frontend
setup_provider=ansible_slurm+pvfs2
...
[setup/ansible_slurm+pvfs2]
frontend_groups=slurm_master,pvfs2_client
compute_groups=slurm_clients,pvfs2_client
pvfs-nodes_groups=pvfs2_meta,pvfs2_data
...
This configuration will create a SLURM cluster with 10 compute nodes,
10 data nodes and a frontend, and will mount the /pvfs2
directory
from the data nodes to both the compute nodes and the frontend.