2018 and 2019 was mostly spent obsessing over containers, trucks, trailers and hand written paper invoices for me. I was helping build out the technology stack and engineering team for Lori Systems. Early in 2019 we made our first DevOps hire, getting Clive from Safaricom and getting started on migrating our handrolled Django monolith from EC2 to EKS. We would make jokes around shipping containers using containers. Clive even had a container shaped stressball with the EKS logo on it. This set me thinking on the parallels between shipping code and shipping goods, perhaps also led to the foundations of this post.
Intermodal Shipping in the real-world and in software
Over the almost 2-years of work in Logistics I learnt a lot about how the global logistics system works. Almost like the life-blood of the planet. Large container ships abstract away contents and ship things from Taiwan to Timbukutu. The seminal book on this topic is perhaps, The BOX. Watching global shipping lanes in Marine Traffic and scraping ships arriving in Mombasa from the KPA Sharepoint became a daily ritual. I digress, back to the original point on the importance for containerization in shipping code or machinery.
Docker uses the ubiquitous whale/ship logo, most containers arrive at ports this way from the oceans of developers. I don't quite have an analogy here for the massive ships that land the containers at ports, some 500 or 1000 TEU's at a time. The analogy here covers land transport aspects, somewhat related to how code runs in production and is typically served via datacenters / public clouds to users.
Containers themselves make transfer of goods/code from development (ships) to production (trains/trucks) easy. However even containerized applications can demonstrate tight coupling similar to what a train has, in effect being a distributed monolith, instead of a true suite of microservices. In my opinion, any system that requires a release train approach for new features is most likely to be a distributed monolith masquarding as microservices. The real flexibility comes from the low coupling between containers and the freedom to release each clearly delineated service at its own cadence on the roads.
Trains are awesome
My 5yo is currently obsessed with steam engines, even though they are from an era long gone. There is something magical about a powerful engine pulling everything along smoothly on a set of constraints (rails). It works nicely as long as no quick changes are needed in the carriages and everyone wants to get to the same destination. Trouble arises when something in the closely coupled chain of components goes awry and requires a quick change. I still don't understand the scene in snow piercer where a few wagons were dumped in a siding at speed. If we can do that one neat trick perhaps monoliths would become much more maintainable. In early stages of a product monoliths are a nice simple entry point, especially if the features are narrowly scoped and well coupled. On the reverse the monolith may be a very good idea for a mature product which is not changing rapidly and perhaps needs to be optimised for performance instead by reducing communication overhead between components by introducing tight coupling. In both cases a modular approach and service-oriented designs are still feasible, as long as the implementation and maintenance team is aware of the implications. People are still driving around in classic cars from the 1900's, where as steam locomotives from that era are languishing in museums.
Trucks are flexible
One of the killer advantages of trucks in the logistics business is their ability to deliver right to the factory or warehouse loading bay. It is simply not feasible to build train tracks to serve every address. Even in areas with great railway infrastructure, buffers (known as Inland container depots) have to be placed to cover the last few miles of transport from the rail to the industrial areas. This sort of mode can sometimes be seen in Microservices being layered on older monoliths to provide user facing services, especially in banking systems. The other great advantage trucks have is the ability overtake each other gradually along the road, this manifests itself in software systems as rolling deployment of new features. Such an approach requires careful management of the stateful parts of the system such as storage and database schemas. Otherwise it turns into a Fast and Furious game of stealing a container from a moving platform, aka the Romanian Rollover.
This analogy is not new
The logistics analogies are rife in software engineering, we ship code, we package things, we have release trains. The largest real world container orchestration organization Maersk uses a 7-point logo surprisingly similar to the most popular software container orchestration platform Kubernetes. I will continue updating this post as more ideas and links come together.
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Random Roadtrip Rumination : Microservices vs Monotliths is Trucks vs Trains for shipping features.
— Tisham Dhar (@whatnick) December 26, 2020
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