GSS In Kubernetes

The GIS and Asset Management worlds have taken notice of the huge architectural improvements that GE has made in its GeoSpatial Server (GSS) product for Smallworld. From the legacy jBoss solution, it has now become completely cloud compatible with Kubernetes.

Of course, Kubernetes is all the buzz these days, but it is worth noting that GE’s investment here makes it a truly scalable solution for your web/cloud application backend, using state-of-the-art technology without reinventing the wheel over and over again. It is not simply dumping the application into a container or cluster, like we’ve seen with ESRI presentations.

The thought put into creating a Kubernetes-based architecture, the way GE has done, has resulted in a well-designed, all-inclusive solution, from authentication and authorisation to well-designed load balancing solutions.


The design team’s use of the name ‘Bifröst’ for the general access of the GSS cluster was very clever, as it means that the god, Heimdallr,  will guard the bridge to the backend functionality.

When studying the solution, it is clear that there are a lot of standard components tightly configured together to form a well-functioning solution.


Many open-source standard solutions are used together: Docker for containerisation, Kubernetes to orchestrate the cluster, and UAA for guarding access as well as Open source logging solutions.

New technology

If you are not familiar with the technology of containerisation, starting with the new version of GSS can be quite a challenge. You have to familiarise yourself with how Docker containers and Kubernetes pods work.  You then need to learn how to orchestrate all these containers with Kubernetes and finally how to create your customisations in the back-end containers.


A steep learning curve…

At Realworld Software Products B.V., we wanted to know more about this solution and with our international Realworld sister companies, we set out to acquire this knowledge together.

Development environment

In order to familiarise ourselves with this technology, we started by extending our current knowledge base and got ourselves acquainted with Docker and its capabilities. The next step was to dive into the Kubernetes solutions. Past experience helped us to recognise that the best way to get into cluster technology is to have a “real” cluster, meaning to have multiple computers do the job. In Cluster terms: have multiple nodes.

If you want to know more, please contact one of our Realworld specialists. 


One of the new elements in the GSS solution is logging, which has been set up using the ELK logging framework, presenting great logging possibilities. GE provides an example dashboard for this with two graphs. Unfortunately for customers, it is a framework…while there is some work to do for consultants.


For those of you who are familiar with Smallworld, you are probably aware of Diagnostics. Diagnostics is a tool that assists customers in improving the performance of their system when it comes to big data. This big data allows customers to monitor their systems proactively and reactively. This is what ELK facilitates and, as such, interpreting that big data can sometimes be a challenge. With Diagnostics integrated, you can be proactive with clear and transparent insights on that big data – in advance. This is the big difference when compared to logging. Logging alerts you after an issue has already happened. Proactivity means that you see your nodes in the GSS cluster are not equally sharing the load. Proactive means that you see upfront when certain services are misbehaving on particular data.


We created an easy way to ingest the GE GSS logging into Diagnostics and configured it to enrich the extensive insights already provided, including data load and database access from GSS’s Magik service provider pods!


Should you need assistance with your GSS architecture: you know how to find us!

But be proactive: monitor your applications and be ahead of the curve. Behind the curve always means sliding off of it.

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