On-demand Provisioning.
- Resource Provisioning means the selection, deployment, and run-time management of software (e.g., database server management systems, load balancers) and hardware resources (e.g., CPU, storage, and network) for ensuring guaranteed performance for applications.
- Resource Provisioning is an important and challenging problem in the large-scale distributed systems such as Cloud computing environments.
- There are many resource provisioning techniques, both static and dynamic each one having its own advantages and also some challenges.
- These resource provisioning techniques used must meet Quality of Service (QoS) parameters like availability, throughput, response time, security, reliability etc., and thereby avoiding Service Level Agreement (SLA) violation.
- Overprovisioning and under-provisioning of resources must be avoided.
- Another important constraint is power consumption.
- The ultimate goal of the cloud user is to minimize cost by renting the resources and from the cloud service provider’s perspective to maximize profit by efficiently allocating the resources.
- In order to achieve the goal, the cloud user has to request the cloud service provider to make a provision for the resources either statically or dynamically.
- So that the cloud service provider will know how many instances of the resources and what resources are required for a particular application.
- By provisioning the resources, the QoS parameters like availability, throughput, security, response time, reliability, performance etc must be achieved without violating SLA
There are two types Provisioning
- Static Provisioning
- Dynamic Provisioning
Static Provisioning
- For applications that have predictable and generally unchanging demands/workloads, it is
- possible to use “static provisioning" effectively.
- With advance provisioning, the customer contracts with the provider for services.
- The provider prepares the appropriate resources in advance of start of service.
- The customer is charged a flat fee or is billed on a monthly basis.
Dynamic Provisioning
- In cases where demand by applications may change or vary, “dynamic provisioning" techniques have been suggested whereby VMs may be migrated on-the-fly to new compute nodes within the cloud.
- The provider allocates more resources as they are needed and removes them when they are not.
- The customer is billed on a pay-per-use basis.
- When dynamic provisioning is used to create a hybrid cloud, it is sometimes referred to as cloud bursting.
Parameters for Resource Provisioning
- Response time
- Minimize Cost
- Revenue Maximization
- Fault-tolerant
- Reduced SLA Violation
- Reduced Power Consumption
Response time: The resource provisioning algorithm designed must take minimal time to respond when executing the task.
Minimize Cost: From the Cloud user's point of view, cost should be minimized.
Revenue Maximization: This is to be achieved from the Cloud Service Provider’s view.
Fault-tolerant: The algorithm should continue to provide service in spite of the failure of nodes.
Reduced SLA Violation: The algorithm designed must be able to reduce SLA violations.
Reduced Power Consumption: VM placement & migration techniques must lower power consumption
Reduced Power Consumption: VM placement & migration techniques must lower power consumption
Dynamic Provisioning Types
- Local On-demand Resource Provisioning
- Remote On-demand Resource Provisioning
Local On-demand Resource Provisioning
- The Engine for the Virtual Infrastructure
- OpenNEbula creates a distributed virtualization layer
- Extend the benefits of VM Monitors from one to multiple resources
- Decouple the VM (service) from the physical location
- Transform a distributed physical infrastructure into a flexible and elastic virtual infrastructure, which adapts to the changing demands of the VM (service) workloads
- New virtualization layer between the service and the infrastructure layers
- Seamless integration with the existing middleware stacks.
- Completely transparent to the computing service and so end-users
Cluster Partitioning
- Dynamic partition of the infrastructure
- Isolate workloads (several computing clusters)
- Dedicated HA partitions
