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BP1024 Scaling and Best Practices for Virtual Workload Environments with the FS7500 1
Executive summary
Use of Network File System (NFS) based datastores for a VMware virtual environment is becoming
increasingly popular due to the ease of implementation and management capabilities available with
Network Attached Storage (NAS) solutions. Some of the challenges system administrators face while
optimizing NAS based solutions for VMware includes the lack of native multipathing options within the
hypervisor like those available for SAN based storage. This paper provides best practices and
performance optimization recommendations for the Dell EqualLogic FS7500 Unified NAS storage
solution in virtualized environments based on VMware vSphere. It also shows how EqualLogic FS7500
scales with the addition of storage resources for a specific virtual workload use-case scenario.
Based on our tests, the best practices that we suggest for the EqualLogic FS7500 in a VMware based
virtualized environment to load balance across multiple network paths and improve network utilization
are:
• Increase the number of NIC uplinks associated with the host vSwitch connected to the NAS
network to improve network and storage throughput
• Use the IP Hash-based load balancing policy for the ESXi host vSwitch uplinks along with the
source and destination IP hashing policy on the corresponding switch port LAG connected to
the NAS network
• Use the maximum number of NAS service virtual IP addresses to improve network and storage
throughput to fit with the IP Hash-based load balancing policy on the ESXi host vSwitch
• Increasing the number of ESXi hosts in a deployment improves network utilization and offers
read throughput optimization
Storage scalability studies with FS7500 using a sample virtual workload offered the following results:
• Doubling block storage resources for the NAS reserve (EqualLogic PS Series arrays) offered
more than twice the amount of scaling for our workload
• Doubling both EqualLogic PS Series arrays and the FS7500 NAS appliance yielded three times
the amount of scaling for our workload