Hi Andreas,
This is very interesting. I have my own MapServer + MapCache based
application called GeoSphere: https://geosphere.ssec.wisc.edu/
We did the bare minimum of what we had to to get it running on an
on-premise kubernetes cluster. So while I don't have any solutions for
you, I'm very interested in what you're doing and what you might be able
to find. We currently don't have a lot of users so we're still only
using a single MapCache server talking to a single MapServer server, but
want to look into more flexibility as we offer additional layers and
features in the future. Thanks for the document, I'll be sure to read it.
Dave
On 4/23/21 10:20 AM, 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
<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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