There was an interesting talk on running MapServer on Amazon Lambda - 
https://www.youtube.com/watch?v=g_WMDxsuCfk&t=2s
The CGI approach of MapServer scales well as each request can be run separately 
(at a slight overhead for database connections, PROJ startup etc). 

Seth

--
web:http://geographika.co.uk
twitter: @geographika


On Fri, Apr 23, 2021, at 5:20 PM, Andreas Neumann wrote:
> Hi,
> 
> For a small project as part of the Swiss National Geodata Infrastructure 
> (grant project) several people worked on a study document called 
> "Cloud-optimized OGC WMS Server" where we analyzed problems that can arise 
> when you install an OGC web server in the cloud (e.g. docker image deployed 
> via Kubernetes, OpenShift or the likes). This work had a focus on QGIS Server 
> with it's own set of problems - but some of the issues studied in this 
> document also matter for other OGC WMS servers, such as UMN Mapserver or 
> Geoserver, such as the load balancing problem, how to share resources, etc.
> 
> Here is the link to the document (not in final form yet, but close to being 
> final): 
> https://docs.google.com/document/d/1cOUWgzalRx7CHWTFgHz6-uyScsCcoaEmYC0VBHdZShQ/edit#heading=h.c7gq4lie7ys2
> 
> I wonder if any similar work has been done specifically around problems, 
> challenges and solutions when you deploy UMN Mapserver in cloud environments? 
> Do you know of any work?
> 
> One major problem that probably all installations of an OGC WMS server have 
> is how to deploy a more intelligent load balancing system? Often, the default 
> load balancer is some kind of round robin load balancer system, but often 
> this leads to inferior results where "cheap and short" requests (such as a 
> simple GetFeatureInfo or GetLegendGraphics request) can be queued behind a 
> long-running GetMap request (potentially with many layers, many features and 
> a high-dpi, such as 600dpi, where the request can take several seconds to 
> process.
> 
> In our production system we are currently separating the requests to 
> dedicated instances for short requests and potentially long requests, to 
> avoid the above mentioned scenario, but we are not so satisfied with the 
> solution, as it is  a bit inflexible and also a bit harder to maintain. 
> Ideally, we would like to have a more intelligent load balancer with incoming 
> queue that holds back requests as long as all WMS server instances are busy. 
> This would avoid the situation where a "less intelligent" load balancer would 
> simply forward the requests to instances based on Round-Robin principle.
> 
> Do you know of any work in the UMN Mapserver community regarding cloud 
> deployment, cloud optimization, load balancing and resource sharing?
> 
> In our study document I'd like to also include the perspective of other WMS 
> servers besides QGIS server, so any input would be welcome.
> 
> Thanks,
> Andreas
> 
> --
> Andreas Neumann
> QGIS.ORG <http://qgis.org/> board member (treasurer)
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