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Monthly Archives: July 2013

Estimating Availability of SAP on ESXi Clusters – Examples

This is a follow up to the blog I posted in Jan 2013 which identified a generic formula to estimate the availability, expressed as a percentage/fraction, of SAP virtual machines in an ESXi cluster.  The details of the formula are in this whitepaper . This blog provides some example results based on some assumed input data. I used a spreadsheet to model the equation and generate the results – this is shown at the end. The formula is based on mathematical probability techniques. The availability of SAP on an ESXi cluster is dependent on: the probability of failure of multiple ESXi hosts based on the number of spares; the probability that the SPOFs (database & central services) are failing over due to a VMware HA event (depends on failover times and the frequency of ESXi host failures).

The example starts with a single 4-node ESXi cluster running multiple SAP database, application server and central services virtual machines (VMs) corresponding to different SAP applications (ERP, BW, CRM etc.).  A sizing engagement has determined that 4 ESXi hosts are required to drive the performance of all the SAP VMs (the SAP landscape). We assume the sizing is such that the memory of all the VMs will not fit into the physical memory of three or less hosts, and as we typically have memory reservations set (a best practice for mission critical SAP), VMs may not restart after a VMware HA event. So we conservatively treat any host failures that result in less than 4 ESXi hosts as downtime for the SAP landscape (not true at the individual VM/SAP system level as some of the VMs can be de-prioritized in the degraded state in favor of others but we are going with the landscape level approach to provide a worst case estimate). For this reason we design with redundancy by adding extra ESXi hosts in the cluster so I will compare three options with different degrees of redundancy: Continue reading