[mapserver-users] Mapserver installation in cloud environments (kubernetes)

[Andreas Neumann]

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 board member (treasurer)
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