 infrastructure, depending on design choices and ability of VFs to utilize resiliency in the infrastructure, can be a significant contributor to single site downtime. Because cloud infrastructure generally uses commercial compute and storage, the availability tends to be lower than for purpose-built network hardware. Cloud features that improve within-site avail- ability include server sparing; multiple availability zones with anti-affinity rules to distribute VFs across hosts and racks to guard against shared hardware failures (Amazon, 2016); multiple con- trol planes; and dual storage or high availability distributed storage such as Ceph (Ceph, 2016). Assuming that VFs are designed to be able to take advantage of the infrastructure resiliency fea- tures, the compute/storage layer availability can range widely at a single site. Finally, the top two layers of the figure illustrate the impact of virtualization, which is an interac- tion between the application and virtualization layers. Many VFs cannot withstand short failures or "hiccups" in the hypervisor. So, even if the hypervisor appears to be highly available (e.g., the hiccups are of short duration), short disruptions could cause the VF to experience failures. When the failure detection and recovery time of the VF are factored in, the virtualization layer typically has 3- to 4-9s availability, though future improvements may move this higher. The application layer is similarly shown with a wide range of availability to indicate this. 5.1.2 AVAILABILITY TO COST TRADEOFF (BOTTLENECK ANALYSIS) Figure 5.3 illustrates the concept of bottleneck analysis. In this example, while the other layers achieve 4-9s (or higher) availability, the physical cloud infrastructure layer achieves only 3-9s availability. By improving this (bottleneck) layer to 4-9s, site availability can be improved from 99.87% to 99.96% (11.5-3.5 h of downtime per year)-a significant improvement. On the other hand, if the physical cloud infrastructure layer was already at 5-9s, improving this to 6