Page 280 - Cloud computing: From paradigm to operation
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1                                    Framework and requirements for cloud computing


            for securing the virtualized environment. Security and compliance monitoring needs end-to-end VI activity
            monitoring for:
            •       VM  sprawl:  Metrics  to  monitor  VM  activities  as  they  get  cloned,  copied  and,  due  to  network
                    migration, transfers to different storage media.
            •       Configuration metrics: Virtual server configuration monitoring to ensure that they are compliant
                    with standards and hardening guidelines, VM configuration monitoring for software licensing policy
                    enforcement and VI events that help enforce and detect violations of policy. This includes individual
                    security and organization security policy monitoring.
            •       Access control: Access control monitoring and reports for role-based access control enforcement.
            •       Compliance monitoring: Metrics to validate audit and certification.


            II.5    Monitoring and metering for charging and billing
            In a virtualized environment the infrastructure is centralized and it is important to measure resource usage
            by different CSCs. This information can be used to distribute, amortize and in some cases, recover the cost
            correctly across the organization through a proper chargeback mechanism. Chargeback could be based on
            dynamic parameters such as resource usage and/or fixed parameters. To compute the correct chargeback
            information in a dynamic virtualized environment, it is important to monitor virtual and physical resource
            usage and allocations, as well as to be able to normalize the measurement across the cloud infrastructure.
            The  monitoring  and  metering  data  for  service  charging  should  be  collected  and  kept  according  to  SLA
            objectives.
            Chargeback monitoring needs end-to-end VI activity monitoring and service usage metering for:
            •       Standard metrics: All chargeable resource metrics like CPU usage, memory usage, storage usage
                    and network usage metrics.
            •       Key VI events: VI events for virtual resource life-cycle events like start date and end date of VM
                    creation and allocation.
            •       Configuration monitoring: VM configuration in terms of assigned resources and reservations and
                    also applications installed to account for software licensing costs.
            •       VM usage metrics: VM uptime, number of VMs can vary depending on how the charging model is
                    employed in the organization.

            II.6    Monitoring in support of cloud services
            The need for application and service monitoring is important in the cloud computing environment, especially
            for SLA/QoS evaluation because the application or service may have problems even if the VM or the physical
            server on which it is running looks normal. Application and service needs to monitor the basic health of
            application servers with the help of application-specific response time and throughput metrics. The analytics
            on this data could be used to correlate the application-observed and service-observed metrics to all layers of
            the infrastructure to perform a root-cause analysis in the event something going wrong. Application and
            service performance monitoring using the capture of network traffic is used more and more commonly in
            this area.

            There are a few other aspects to virtual infrastructure monitoring that add to the complexity of building a
            comprehensive monitoring solution. All kinds of virtualization software allow the API to be able to collect
            metrics. However, each kind of virtualization software has its own object models. There are wide differences
            in features and even the behaviour of the common features. Therefore, the analytics that are to be built on
            the collected metrics must be developed for each kind of virtualization software.











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