Deployment Models

EC3 supports a wide variety of deployment models (i.e. cluster behaviour). In this section, we provide information about all of them and a example of configuration for each deployment model. For more details, you can follow reading ec3_variables, which provides more information regarding EC3 special variables that support the specification of the deployment model in the templates.

Basic structure (homogeneous cluster)

An homogeneous cluster is composed by working nodes that have the same characteristics (hardware and software). This is the basic deployment model of EC3, where we only have one type of system for the working nodes.

Fig 1. EC3 Deployment Model for an homogeneous cluster.

In EC3, a template specifying this model would be, for instance:

system wn (
   ec3_max_instances = 6 and
   ec3_node_type = 'wn' and
   cpu.count = 4 and
   memory.size >= 2048M and
   disk.0.os.name = 'linux' and
   net_interface.0.connection = 'net'
)

This RADL defines a system with the feature cpu.count equal to four, the feature memory.size greater or equal than 2048M , a operative system based on linux and with the feature net_interface.0.connection bounded to 'net'. It also fixes the maximum number of working nodes to 6 with the EC3 special variable ec3_max_instances, and indicates that this system is of type wn though ec3_node_type.

Heterogeneous cluster

This model allows that the working nodes comprising the cluster can be of different characteristics (hardware and software). This is of special interest when you need nodes with different configuration or hardware specifications but all working together in the same cluster. It also allows you to configure several queues and specify from which queue the working node belongs to.

Fig 2. EC3 Deployment Model for an heterogeneous cluster.

In EC3, a template specifying this model would be, for instance:

system wn (
   ec3_max_instances = 6 and
   ec3_node_type = 'wn' and
   ec3_node_queues_list = 'smalljobs' and
   ec3_node_pattern = 'wn[1,2,3]' and
   cpu.count = 4 and
   memory.size >= 2048M and
   disk.0.os.name = 'linux' and
   net_interface.0.connection = 'net'
)

system largewn (
   ec3_inherit_from = system wn and
   ec3_node_queues_list = 'largejobs' and
   ec3_node_pattern = 'wn[4,5,6]' and
   cpu.count = 8 and
   memory.size >= 4096M
)

This RADL defines two different system. The first one defines the wn with the feature cpu.count equal to four, the feature memory.size greater or equal than 2048M , and with the feature net_interface.0.connection bounded to 'net'. Again, it also fixes the maximum number of working nodes to 6 with the EC3 special variable ec3_max_instances, and indicates that this system is of type wn though ec3_node_type. More systems can be defined, it is not limited to two types of working nodes, it’s only an example. The second defined system, called largewn, inherits the already defined characteristics of system wn, by using the EC3 special feature ec3_inherit_from, but it changes the values for cpu.count and memory.size. Regarding queue management, the RADL defines two queues by using ec3_node_queues_list, and determines whose nodes belong to them. It is also defined the pattern to construct the name of the nodes by the ec3_node_pattern variable.

Cloud Bursting (Hybrid clusters)

The third model supported by EC3 is Cloud Bursting. It consists on launching nodes in two or more different Cloud providers. This is done to manage user quotas or saturated resources. When a limit is reached and no more nodes can be deployed inside the first Cloud Provider, EC3 will launch new nodes in the second defined Cloud provider. This is also called a hybrid cluster. The nodes deployed in different Cloud providers can be different also, so heterogeneous clusters with cloud bursting capabilities can be deployed and automatically managed with EC3. The nodes would be automatically interconnected by using VPN or SSH tunneling techniques.

Fig 3. EC3 Deployment Model for an hybrid cluster.

In EC3, a template specifying this model would be, for instance:

system wn (
    disk.0.os.name = 'linux' and
    disk.0.image.url = 'one://mymachine.es/1' and
    disk.0.os.credentials.username = 'ubuntu' and
    ec3_max_instances = 6 and               # maximum instances of this kind
    cpu.count = 4 and
    memory.size >= 2048M and
    ec3_if_fail = 'wn_aws'
)

system wn_aws (
    ec3_inherit_from = system wn and        # Copy features from system 'wn'
    disk.0.image.url = 'aws://us-east-1/ami-30519058' and # Ubuntu 14.04
    disk.0.os.credentials.username = 'ubuntu' and
    ec3_max_instances = 8 and               # maximum instances of this kind
    ec3_if_fail = ''
)

This RADL is similar to the upper ones. It also defines two different system, but the important detail here is the EC3 variable ec3_if_fail. It defines the next system type to be used when no more instances of system wn can be launched.