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If we treat each tier independently, which is a worst-case assumption, we can calculate an overall system uptime by multiplying each component uptime ref . Downtime per month is calculated using http://www.slatools.com/sla-uptime-calculator. This yields an estimated overall uptime as follows:
TM | IIS LB | WEB | POR | GIS | DS | Overall Uptime | Overall downtime/month |
|---|---|---|---|---|---|---|---|
99.99% | 99.90% | 99.95% | 99.95% | 99.95% | *99.99%90% | 99.78%64% | 95min155.5min |
TM | Azure LB | WEB | POR | GIS | DS | Overall Uptime | Overall downtime/month |
|---|---|---|---|---|---|---|---|
99.99% | 99.99% | 99.95% | 99.95% | 99.99%95% | *99.90% | 99.87%56min73% | 117min |
* Since our DS0 machine currently hosts the file share used by paired portal and gis machines, we can’t consider it a load balanced resource
Case study
We've recently deployed a production-style instance in Bill's sandbox, TC-Sandbox-BXUeGIS-RG. This instance has a virtual machine load balancer in front of the two web machines, and also has a traffic manager and load balancer configured.
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