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BP1024 Scaling and Best Practices for Virtual Workload Environments with the FS7500 27
4 Scalability of FS7500
A series of tests were conducted to study the scalability of the FS7500 solution with NFS exports
hosted as ESXi datastores. The network and host configuration were based on the findings described
in section 3.
4.1 Test workload
4.1.1 Workload modeling and application components
A datacenter typically consolidates several diverse workloads onto a virtualization platform—a
collection of physical servers accessing shared storage and network resources. These diverse
workloads may include OLTP databases, email servers, collaboration (SharePoint), webservers, OLAP
data warehouses, and other similar applications.
For our test purposes, we chose to model a medium scale e-commerce business running a mix of
applications in a virtualized environment. Commonly used applications and the percentage of virtual
machines (VMs) that host these applications in a medium scale e-commerce business can be
represented as a mix in table below:
Table 2 Typical medium scale e-commerce environment
Application
Approximate percentage of VMs
Windows Servers (for running Active Directory, Domain
Controllers etc.)
5%
Mail servers like Microsoft Exchange Server
5%
OLTP DB servers like Microsoft SQL Server 20%
Microsoft SharePoint Servers
5%
Web servers like Microsoft IIS 40%
Middleware servers like J2EE App servers
20%
Web 2.0/Social Media applications like Olio 5%
We used this workload mix to represent a medium scale e-commerce business in our scalability
studies for FS7500.
4.1.2 I/O profile mapping for representative applications
Iometer running on different VMs simulating that I/O pattern of applications described above
generated the required mix of I/O. A set of 20 VMs was the basic building block used for the workload.
20 VMs help to maintain the workload ratio mix described in table above. Scaling of total workload can
be achieved by scaling the number of blocks comprising the 20 VMs. The following table shows the
number of VMs running each workload, the transaction mix, and the resource allocation for the VMs in
the 20 VM building blocks. The planned or target IOPS values and data set sizes for each application
type were based on typical values representative of applications in a medium scale e-commerce
business environment.