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Scaling a growing organization by reorganizing the teams (The Continuous Improver)

On July 25, 2016, in Syndicated, by Association for Software Testing
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During this year’s QCon conference held in New York, I attended a full-day workshop on the scalability challenges a growing organization faces, hosted by Randy Shoup. In my previous two posts I discussed a model to understand the needs of an organization in its different life phases, as well as a migration strategy for getting from a monolith to a set of well-defined microservices.

The Universal Scalability Law…again

However, Randy also talked about people, or more specifically, how to reorganize the teams for scalability without ignoring the Universal Scalability Law. What this means is that you should be looking for a way to have lots of developers in your organization working on things in isolation (thereby reducing contention) without the need for a lot of communication (a.k.a. coherence). So any form of team structuring that involves a lot of coordination between teams is obviously out of the question, particularly skill-based teams, project-based teams or large teams.

For the same reason, Randy advises against geographically split teams or outsourcing to so-called job shops. Those do not only involve a lot of coordination, but local conversations will become disruptive in melding a team. Just like Randy, I find face-to-face discussions crucial for effective teams. But if your team is not co-located, those local conversations will never reach the rest of the team. Yes, you may persist on posting a summary of that discussion on some kind of team wiki, Flowdock/Slack or other team collaboration tool, but they will still miss the discussions that let to that summary. Even using a permanent video conferencing set-up doesn’t always solve that, particularly if the people in the team don’t share the same native language (which is already a problem for co-located teams).

The ideal team

He also said something about the effect of getting more people in the organization. In his view, 5 people is the ideal. That number of people can sit around a table, will benefit from high bandwidth communication and roles can be fluid. When you reach about 20 people, you require structure, which on turn, can be a potential trough of productivity and motivation. When you reach 100 people, you must shift your attention from coordinating individuals to coordinating teams. A clear team structure and well-defined responsibilities becomes critical. Knowing this, it’s kind of expected that Randy likes to size his teams using the “2 pizza rule”, the number of people you can feed from 2 pizza’s. So a team consisting of 4-6 people in a mix of junior and senior and (obviously) co-located has his preference.

Ideally he wants to have that team take ownership of a component or service, including maintenance and support as well as the roadmap for that component or service. This implies that all teams are full-stack from a technological perspective and are capable of supporting their component or service all the way into production. But Randy emphasizes that managers shouldn’t see teams like this as software factories. Teams should have an identity and be able to build up proud-of- ownership. This also implies taking responsibility over the quality of those services. He purposely mentioned the problem of not having the time to do their work right and taking shortcuts because of (perceived) pressure from management or other stakeholders. In his opinion, this is the wrong thing to do, since it means you’ll need to do the work twice. The more constrained the team is in time, the more important it is to do it the right way first.

The effect of team structure on architecture

Another argument for his ideas is provided by Conway’s Law. Melvin Conway observed that in a lot of organizations the structure of the software system closely followed the structure of the organization. This isn’t a big surprise, since quite often, cross-team collaboration requires some kind of agreed way of working, both on the communication level as well as on the technical level. Quite often, architectural seams like API contracts or modules emerge from this. So based on that observation, he advices organizations to structure the teams along the boundaries you want to accomplish in your software architecture. And this is how Conway’s Law is usually used. But in this workshop, Randy has already steered us towards the notion of using microservices for scaling the organization. So does Conway’s Law apply here? Each team owns one or more microservices, or, the API contracts I just discussed. They work in isolation, but negotiate about the features provided by their services. I would say that is a resounding yes!

All things considered, it should not come as a surprise that he believes microservices are the perfect architecture for scaling an organization on both the people and the technical level. So what do you think? Are microservices the right technology to scale teams? Or is this the world up-side down? Let me know by commenting below. Oh, and follow me at @ddoomen to get regular updates on my everlasting quest for better solutions

 

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