Cloud Management - Deploying and Managing a Cloud Infrastructure - page 112

servers to cope with the traffic. If you are in a traditional IT infrastructure like an in-house
data center, chances are you will face a “success disaster,” meaning that you are getting a
huge amount of traffic and audience but are unable to monetize on it. To illustrate, think of
a coffee shop that sells extraordinary coffee and can serve only 30 customers an hour but
actually gets 50 customers an hour. The queue just keeps on getting longer because they
coffee shop employees can't serve fast enough. It is attracting more customers than it can
serve, which to the casual observer would look like total success, but in truth the coffee
shop is not seeing the profit that it should if it had a bigger area and more baristas.
This is the same for web applications. If you cannot serve all of your users, then you are
missing out on potential profit. To be able to serve in such situations, your cloud infrastruc-
ture must be built for fast and predictive provisioning. Setting provisioning policies based
on percentage of load will not be enough when a usage spike occurs. The traffic level would
reach the threshold and pass it quickly, and your system would not be able to provision
fast enough, leading to some users losing patience and leaving. The system should be able
to calculate the rate of increase in traffic and accurately predict how long it would take for
it to reach the threshold at that rate and then provision for additional load servers when it
sees fit, even before the threshold is hit.
Intelligent workload management (IWM) is a new paradigm that came along with
cloud computing and is made possible by dynamic infrastructure, virtualization, and
identity management. IWM securely manages and optimizes computing resources across
physical, virtual, and cloud environments in order to deliver business services for end cus-
tomers in a software- and application-compliant manner. First, a workload is a specific
request or processing request made by a user or an application that requires processing.
An example would be mathematical calculations submitted by weather prediction soft-
ware or a database process request.
IWM is a kind of systems process management where the workloads themselves know
what they are, their priority, and where they belong. For example, in a hybrid cloud envi-
ronment, a specific workload will be configured to detect its own security permissions and
level of sensitivity so it knows whether to get processed on the private side or the public
side of the cloud. In cloud computing, you can provision servers that specialize in specific
types of processes, so when a specific workload is produced, both it and the system know
at which server it should be processed.
Managing Risk
Risk is everywhere, and in a cloud computing environment, there are new types of risks
that are unique to this kind of environment. And in relation to workload management,
we must identify the possible risks that would occur. For example, in the event of a major
distributed denial of service (DDoS) attack , dynamic and intelligent provisioning, the
pay-per-use model, and virtually unlimited computing resources that are the major fea-
tures of cloud computing can be the Achilles heel of the organization but not exactly pose
any risk to the system itself. You might already have an idea what sort of risk this poses
to the organization.