Legislature and Off the Shelf Thinking

I’m always pleasantly surprised when I find an aspect of software delivery which I hadn’t previously considered, or seen as fully as I might have.

Today I was chatting with a colleague who it turns out has a long history in the business of superannuation (pensions, for those in the UK). I was expressing my very heart felt belief that building a business’ core domain using an off the peg system is a risky undertaking. I talked about how I could understand a company purchasing a CRM system, as customer management is a well understood space, and why spend money developing an in-house CRM system when you really only want it to do what every other CRM system does? I talked about how leveraging an off the peg system leaves the core domain at the mercy of the business which owns the system. I expressed dissatisfaction at the architecture of off the peg solutions; that they are generally monolithic and impossible to marry with today’s continuous delivery practices.

It was about at this point when she explained that the business of superannuation is predominantly legislated by the Australian government, and the main difference between funds is in choice of investment opportunity. The services made available are mandated by legislation. The way the fund is managed is by and large mandated by legislation. So much is legislated that there are off the shelf systems available which cover pretty much every aspect of managing a superannuation fund, from managing fund investments to giving members access to manage their accounts online. These systems are also kept up to date with legislative changes as and when they happen. So funds stay within the bounds of the law simply by using that software.

Ok, so the off the shelf story always sounds rosier than it is in real life, but there’s an interesting point to see here. Because the core domain of the business is not proprietary business logic, because the core domain is in fact not just well known but it’s enforced by an external third party, then an off the peg solution could perhaps model it perfectly well. Updates to the system from the vendor are driven by the same legislation as drives the business. The main differentiators between systems becomes UX and architecture.

The conversation has left me wondering whether there are any other businesses which are so highly legislated that the same logic would apply. It has also left me wondering how a business which embraces an off the shelf solution for their core domain might also find it difficult to embrace modern software delivery techniques. In fact, I wonder if they would ever reach the tipping point where it becomes necessary to raise the dev teams above simply hacking solutions together.

Scale or Fail

I’ve heard a lot of people say something like “but we don’t need huge scalability” when pushed for reason why their architecture is straight out of the 90’s. “We’re not big enough for devops” is another regular excuse. But while it’s certainly true that many enterprises don’t need to worry so much about high loads and high availability, there are some other, very real benefits to embracing early 21st century architecture principals.

Scalable architecture is simple architecture

Keep it simple, stupid! It’s harder to do than it might seem. What initially appears to be the easy solution can quickly turn into a big ball of unmanageable, tightly coupled string of dependencies where one bad line of code can affect a dozen different applications.

In order to scale easily, a system should be simple. When scaling, you could end up with dozens or even hundreds of instances, so any complexity is multiplied. Complexity is also a recipe for waste. If you scale a complex application, the chances are you’re scaling bits which simply don’t need to scale. Systems should be designed so hot functions can be scaled independently of those which are under utilised.

Simple architecture takes thought and consideration. It’s decoupled for good reason – small things are easier to keep ‘easy’ than big things. An array of small things all built with the same basic rules and standards, can be easily managed if a little effort is put in to working out an approach which works for you. Once you have a few small things all being managed in the same way, growing to lots of small things is easy, if it’s needed.

Simple architecture is also resilient, because simple things tend not to break. And even if you aren’t bothered about a few outages, it’s better to only have the outages you plan for.

Scalable architecture is decoupled

If you need to make changes in anything more than a reverse proxy in order to scale one service, then your architecture is coupled, and shows signs of in-elasticity. Other than being scalable, decoupled architecture is much easier to maintain, and keeps a much higher level of quality because it’s easier to test.

Decoupled architecture is scoped to a specific few modules which can be deployed together repeatedly as a single stack with relative ease, once automated. Outages are easy to fix, as it’s just a case of hitting the redeploy button.

Your end users will find that your decoupled architecture is much nicer to use as well. Without having to make dozens of calls to load and save data in a myriad of different applications and databases, a decoupled application would just make only one or two calls to load or save the data to a dedicated store, then raise events for other systems to handle. It’s called eventual consistency and it isn’t difficult to make work. In fact it’s almost impossible to avoid in an enterprise system, so embracing the principal wholeheartedly makes the required thought processes easier to adopt.

Scalable architecture is easier to test

If you are deploying a small, well understood, stack with very well known behaviours and endpoints, then it’s going to be no-brainer to get some decent automated tests deployed. These can be triggered from a deployment platform with every deploy. As the data store is part of the stack and you’re following micro-architecture rules, the only records in the stack come from something in the stack. So setting up test data is simply a case of calling the API’s you’re testing, which in turn tests those API’s. You don’t have to test beyond the interface, as it shouldn’t matter (functionally) how the data is stored, only that the stack functions correctly.

Scalable architecture moves quicker to market

Given small, easily managed, scalable stacks of software, adding a new feature is a doddle. Automated tests reduce the manual test overhead. Some features can get into production in a single day, even when they require changes across several systems.

Scalable architecture leads to higher quality software

Given that in a scaling situation you would want to know your new instances are going to function, you need attain a high standard of quality in what’s built. Fortunately, as it’s easier to test, quicker to deploy, and easier to understand, higher quality is something you get. Writing test first code becomes second nature, even writing integration tests up front.

Scalable architecture reduces staff turnover

It really does! If you’re building software with the same practices which have been causing headaches and failures for the last several decades, then people aren’t going to want to work for you for very long. Your best people will eventually get frustrated and go elsewhere. You could find yourself in a position where you finally realise you have to change things, but everyone with the knowledge and skills to make the change has left.

Fringe benefits

I guess what I’m trying to point out is that I haven’t ever heard a good reason for not building something which can easily scale. Building for scale helps focus solutions on good architectural practices; decoupled, simple, easily testable, micro-architectures. Are there any enterprises where these benefits are seen as undesirable? Yet, when faced with the decision of either continuing to build the same, tightly coupled, monoliths which require full weekends (or more!) just to deploy, or building something small, light weight, easily deployed, easily maintained, and ultimately scalable, there are plenty of people claiming “Only in an ideal world!” or “We aren’t that big!”.

Bonkers!

Avoiding Delivery Hell

Some enterprises have grown their technical infrastructure to the point where dev ops and continuous deployment are second nature. The vast majority of enterprises are still on their journey, or don’t even realise there is a journey for them to take. Businesses aren’t generally built around great software development practices – many businesses are set up without much thought to how technical work even gets done, as this work is seen as only a supporting function, not able to directly increase profitability. This view of technical functions works fine for some time, but eventually stresses begin to form.

Failing at software delivery.

Each area of a young business can be easily supported by one or two primary pieces of software. They’re probably off the shelf solutions which get customised by the teams who use them. They probably aren’t highly integrated; information flows from department to department in spreadsheets. You can think of the integration points between systems as being manual processes.

While the flow of work is funnelled through a manual process such as sales staff on phones or shop staff, this structure is sufficient. The moment the bottleneck of sales staff is removed (in other words, once an online presence is built where customers can be serviced automatically) things need to run a bit quicker. Customers online expect to get instant feedback and delivery estimates. They expect to be able to complete their business in one visit and only expect to receive a follow up communication when there is a problem. Person to person interaction can be very flexible; a sales person can explain why someone has to wait in a way which sounds perfectly fine to a customer. The self-service interaction on a website is less flexible – a customer either gets what they want there and then, or they go somewhere else.

And so businesses start to prioritise new features by how many sales they will bring in, either by reducing the number of customers jumping out of the sales flow or by drawing additional customers into the sales flow.

Problems arise as these features require more and more integration with each of the off the shelf solutions in place throughout the various areas of the business. Tight coupling starts to cause unexpected (often unexplained) outages. Building and deploying new features becomes harder. Testing takes longer – running a full regression becomes so difficult and covers so many different systems that if there isn’t a full day dedicated to it, it won’t happen. The online presence gets new features, slowly, but different instabilities make it difficult for customers to use. The improvements added are off-set by bugs.

Developers find it increasingly difficult to build quality software. The business puts pressure on delivery teams to build new features in less time. The few movements among the more senior developers to try to improve the business’ ability to deliver are short lived because championing purely technical changes to the business is a much more complicated undertaking than getting approval from technical piers. It’s not long before enough attempts to make things better have either been shot down or simply ignored, that developers realise there are other companies who are more willing to listen. The business loses a number of very talented technologists over a few months. They take with them the critical knowledge of how things hang together which was propping up the development team. So the rate of new features to market plummets, as the number of unknown bugs deployed goes through the roof.

It’s usually around this point that the management team starts talking about off-shoring the development effort. The same individuals also become prime targets for sales people peddling their own off the shelf, monolithic, honey trap of a system – promising stability, fast feature development, low prices, and high scalability. The business invests in some such platform without properly understanding why they got into the mess they are in. Not even able to define the issues they need to overcome, never mind able to determine if the platform delivers on them.

By the time the new system is plumbed in and feature parity has been achieved with existing infrastructure, the online presence is a long way behind the competition. Customers are leaving faster than ever, and a decision is made to patch things up for the short term so the business can be sold.

Not an inevitability.

Ok, so yes this is a highly pessimistic, cynical, and gloomy prognosis. But it’s one that I’ve seen more than a few times, and I’m guessing that if you’re still reading then it had a familiar ring for you too. I’m troubled by how easy it is for a business to fall into this downwards spiral. Preventing this is not just about being aware that it’s happening, it’s about knowing what to do about it.

Successfully scaling development effort requires expertise in different areas: architecture, development, operations, whatever it is the business does to make money, people management, leadership, change management, and others I’m sure. It’s a mix of technical skills and soft skills which can be hard to come by. To make things even harder, ‘good’ doesn’t look the same everywhere. Different teams need different stimuli in order to mature, and there are so many different tools and approaches which are largely approved of that one shoe likely won’t fit all. What’s needed is strong, experienced, and inspirational leadership, with buy in from the highest level. That and a development team of individuals who want to improve.

Such leaders will have experience of growing other development teams. They will probably have an online presence where they make their opinions known. They will be early adopters of technologies which they know make sense. They will understand how dev ops works. They will understand about CI and CD, and they will be excited by the idea that things can get better. They’ll want to grow the team that’s there, and be willing to listen to opinion.

Such leaders will make waves. Initially, an amount of effort will be directed away from directly delivering new functionality. Development effort will no longer be solely about code going out the door. They will engage with technology teams at all levels, as comfy discussing the use of BDD as they are talking Enterprise Architecture. Strong opinions will emerge. Different technologies will be trialled. To an outsider (or senior management) it might appear like a revolt – a switch in power where the people who have been failing to deliver are now being allowed to make decisions, and they’re not getting them all right. This appearance is not completely deceptive; ownership and empowerment are huge drivers for team growth. Quality will come with this, as the team learn how to build it into their work from architecture to implementation, and learn how to justify what they’re doing to the business.

Software delivery becomes as much a part of the enterprise as, for example, Human Resources, or Accounts. The CEO may not understand all aspects of HR, but it is understood that the HR department will do what needs to be done. The same level of respect and trust has to be given to software delivery, as it is very unlikely the CEO or any other non-technical senior managers will understand fully the implications of the directions taken. But that’s fine – that’s the way it’s meant to be.

In time to make a difference.

Perhaps the idea of strong technical leadership being critical to technical success is no surprise, it seems sensible enough. So why doesn’t this happen?

There are probably multiple reasons, but I think it’s very common for senior managers to fear strong technical leadership. There seems to be a belief that devolving responsibility for driving change among senior technicians can bring about similar results as a single strong leader while avoiding the re-balancing of power. I see this scenario as jumping out of the same plane with a slightly larger parachute – it’ll be a gentler ride down, but you can only pretend you’re flying. By the time the business makes it’s mind up to try to hire someone, there’s often too much of a car crash happening to make an enticing offering.

If we accept that lifting the manual sales bottleneck and moving to web based sales is the catalyst for the explosion of scale and complexity (which I’m not saying is always the case) then this would be the sweet spot in time to start looking for strong technology leadership. Expect to pay a lot more for someone capable of digging you out of a hole than for someone who has the experience to avoid falling in it to begin with. And other benefits include keeping your customers, naturally.

What’s Slowing Your Business?

There are lots of problems that prevent businesses from responding to market trends as quickly as they’d like. Many are not IT related, some are. I’d like to discuss a few problems that I see over and over again, and maybe present some useful solutions. As you read this, please remember that there are always exceptions. But deciding that you have one of these exceptional circumstances is always easier when starting from a sensible basic idea.

Business focused targeting.

For many kinds of work, quicker is better. For software development, quicker is better. But working faster isn’t the same thing as delivering faster.

I remember working as technical lead for a price comparison site in the UK, where once a week each department would read out a list of the things they achieved in the last week and how that had benefited the business. For many parts of the business there was a nice and easy line that could be drawn from what they did each week and a statistic of growth (even if some seemed quite contrived). But the development team was still quite inexperienced, and struggling to do CI never mind CD. For the less experienced devs, being told to “produce things quicker” had the opposite effect. Traditional stick and carrot doesn’t have the same impact on software development as on other functions, because a lot of the time what speeds up delivery seems counter intuitive.

Have two people working on each task (pair programming)
Focus on only one feature at a time
Write as much (or more) test code as functional code
Spend time discussing terminology and agreeing a ubiquitous language
Decouple from other systems
Build automated delivery pipelines

These are just a few examples of things which can be pushed out because someone wants the dev team to work faster. But in reality, having these things present is what enables a dev team to work faster.

Development teams feel a lot of pressure to deliver, because they know how good they can be. They know how quickly software can be written, but it takes mature development practices to deliver quickly and maintain quality. Without the required automation, delivering quick will almost always mean a reduction in quality and more time taken fixing bugs. Then there are the bugs created while fixing other bugs, and so on. Never mind the huge architectural spirals because not enough thought went into things at the start. In the world of software, slow and steady may lose the first round, but it sets the rest of the race up for a sure win.

Tightly coupling systems.

I can’t count how often I’ve heard someone say “We made a tactical decision to tightly couple with <insert some system>, because it will save us money in the long run.”

No.

Just no.

Please stop thinking this.

Is it impossible for highly coupled systems to be beneficial? No. Is yours one of these cases? Probably not.

There are so many hidden expenses incurred due to tightly coupled designs that it almost never makes any sense. The target system is quite often the one thing everything ends up being coupled with, because it’s probably the least flexible ‘off the shelf’ dinosaur which was sold to the business without any technical review. There are probably not many choices for how to work with it. Well the bottom line is: find a way, or get rid. Ending up with dozens of applications all tightly bound to one central monster app. Changes become a nightmare of breaking everyone else’s code. Deployments take entire weekends. License fees for the dinosaur go through the roof. Vendor lock in turns into shackles and chains. Reality breaks down. Time reverses, and mullets become cool.

Maybe I exaggerated with the mullets.

Once you start down this path, you will gradually lose whatever technical individuals you have who really ‘get’ software delivery. The people who could make a real difference to your business will gradually go somewhere their skills can make a difference. New features will not only cost you more to implement but they’ll come with added risk to other systems.

If you are building two services which have highly related functionality, ie. they’re in the same sub-domain (from a DDD perspective), then you might decide that they should be aware of each other on a conceptual level, and have some logic which spans both services and depends on both being ‘up’, and which get versioned together. This might be acceptable and might not lead to war or famine, but I’m making no promises.

It’s too hard to implement Dev Ops.

No, it isn’t.

Yes, you need at least someone who understands how to do it, but moving to a Dev Ops approach doesn’t mean implementing it across the board right away. That would be an obscene way forwards. Start with the next thing you need to build. Make it deployable, make it testable with integration tests written by the developer. Work out how to transform the configuration for different environments. Get it into production. Look at how you did it, decide what you can do better. Do it better with the next thing. Update the first thing. Learn why people use each different type of technology, and whether it’s relevant for you.

Also, it’s never too early to do Dev Ops. If you are building one ‘thing’ then it will be easier to work with if you are doing Dev Ops. If you have the full stack defined in a CI/CD pipeline and you can get all your changes tested in pre-production environments (even infra changes) then you’re winning from the start. Changes become easy.

If you have a development team who don’t want to do Dev Ops then you have a bigger problem. It’s likely that they aren’t the people who are going to make your business succeed.

Ops do routing, DBA’s do databases.

Your developers should be building the entire stack. They should be building the deployment pipeline for the entire stack. During deployment, the pipeline should configure DNS, update routing tables, configure firewalls, apply WAF rules, deploy EC2 instances, install the built application, run database migration scripts, and run tests end to end to make sure the whole lot is done correctly. Anything other than this is just throwing a problem over the fence to someone else.

The joke of the matter is that the people doing the developer’s ‘dirty work’ think this is how they support the business. When in reality, this is how they allow developers to build software that can never work in a deployed state. This is why software breaks when it gets moved to a different environment.

Ops, DBA’s, and other technology specialists should be responsible for defining the overall patterns which get implemented, and the standards which must be met. The actual work should be done by the developer. If for no other reason than the fact that when the developer needs a SQL script writing, there will never be a DBA available. The same goes for any out-of-team dependencies – they’re never available. This is one of the biggest blockers to progress in software development: waiting for other people to do their bit. It’s another form of tight coupling, building inter-dependent teams. It’s a people anti-pattern.

If you developers need help to get their heads around routing principals or database indexing, then get them in a room with your experts. Don’t get those people to do the dirty work for everyone else, that won’t scale.

BAU handle defects.

A defect found by a customer should go straight back to the team which built the software. If that team is no longer there, then whichever team was ‘given’ responsibility for that piece of software gets to fix the bug.

Development teams will go a long way to give themselves an easy life. That includes adding enough error handling, logging, and resilient design practices to make bug fixing a cinch, but only if they’re the ones who have to deal with the bugs.

Fundamental design flaws won’t get fixed unless they’re blocking the development team.

Everything else.

This isn’t an exhaustive list. Even now there are more and more things springing to mind, but if I tried to shout every one out then I’d have a book, not a blog post. The really unfortunate truth is that 90% of the time I see incredibly intelligent people at the development level being ignored by the business, by architects, even by each other, because even though a person hears someone saying ‘this is a good/bad idea’ being able to see past their own preconceptions to understand that point of view is often incredibly difficult. Technologists all too often lack the soft skills required to make themselves heard and understood. It’s up to those who have made a career from their ‘soft skills’ to recognise that and pay extra attention. A drowning person won’t usually thrash about and make a noise.

When Things Just Work

A particularly tricky epic hits the development team’s radar. The Product Manager has been mulling it over for a while, has a few use cases from end users and has scoped things pretty well. He’s had a session with the Product Owner who has since fleshed things out into an initial set of high priority stories from a functional point of view. The Product Owner spends an hour with the Technical Lead and another Developer going over the epic. It quickly becomes apparent that they’re going to have to build some new infrastructure and a new deployment pipeline so they grab one of the Architects to make sure their plans are in line with the technical roadmap. Some technical stories are generated and some new possibilities crop up. The Product Owner takes these to the Product Manager. Between them they agree what is expected functionally and re-prioritise now they have a clearer picture of what’s being built. In the next grooming session the wider team hit the epic hard. There’s a lot of discussion and the Architect gets called back in when there are some disagreements. The QA has already spent some time considering how testing will work and she’s added acceptance criteria to all the stories which are reviewed by the devs during the meeting. Each story is scored and only when everyone is happy that there is a test approach, a deployment plan and no unresolved dependencies, does a story get queued for planning. It takes three sprints to get the epic completed, during which the team focus primarily on that epic. They pair program and work closely with the QA and Product Owner who often seem like walking, talking specifications. There are a few surprises along the way and some work takes longer than expected but everyone’s ok with that. Some work gets completed quicker than expected. The Product Manager has been promoting the new feature so when it finally goes fully live the team get some immediate feedback on what users like and dislike. This triggers a few new stories to make some changes that go out in the next release.

Well, that all sounded really simple. Everyone involved did their bit, no-one expected anything unreasonable, the only real pressure came from the team’s own pride in their work and everyone went home on an evening happy. So why is it that so often this isn’t the case? Why do some teams or even entire companies expend huge amounts of effort but only succeed in increasing everyone’s stress levels, depriving people of a decent night’s sleep and releasing product with more bugs than MI5?

What Worked?

If you’re reading this then hopefully team management is something you’re interested in and you’re probably well aware that there is never just one thing that makes it work. In fact, Roy Osherove described three distinctly different states that a team can find itself in which require very different management styles and expose very different team dynamics.

If you haven’t already done so, take a look at Roy’s blog here: http://5whys.com/ and download his book here: https://leanpub.com/teamleader

Often team members are affected by influences external to the team – for example, the Product Manager is almost certain to be dealing with multiple teams and end users. Their day could have started pretty badly and that will always colour interactions with others – we’re only human. So at any one given moment of interaction, the team could be in one of many states that could either be conducive to a good outcome or that could be leading to a problem.

Let’s try pulling apart this idealistic scenario and see how many opportunities there were for derailment.

Early Attention

In our scenario, the epic isn’t straight forward so the Product Manager has been thinking about what it means to his end users and where it fits into his overall plan. A lesser Product Manager might not have given it any attention yet and instead of having some stories outlined there might not be much more than a one line description of the functionality. Lack of care when defining work speaks to the rest of the team about how little the epic matters. If the Product Manager doesn’t care enough about the work to put effort into defining it properly, then others will often care just as little.

Early Architectural Input

Right at the beginning the Architect is questioned about how they see the work fitting in with the rest of the enterprise. Without talking tech early the team could waste time pursuing an approach which is at best not preferred and possibly just won’t work.

Product Owner and Technical Lead

The Product Owner and the Technical Lead take on the initial task of trying to get to grips with the story together. These two are a perfect balance of product and development. Moving up the seniority tree, the Product Manager and the Architect can often disagree vehemently, but the less senior pair need the relationship of mutual trust they’ve built. Nowhere is there a better meeting of the two disciplines. Lose either of these roles and the team will suffer.

Changing Things

After looking at things from a technical point of view, the Product Owner goes back to the Product Manager to discuss some changes. If the Product Owner isn’t open to this then many opportunities for quick wins will be missed and it becomes much more likely that the team will be opening at least one can of worms that they’d prefer not to.

Grooming Wide

Although strictly speaking all the work that goes into defining a story is ‘grooming’ and doesn’t have to include the whole team, there should be a point (probably in a grooming session) where the majority of the team gets the chance to review things and give their own opinions. If this doesn’t happen then much of the team’s expertise is being wasted. Also, some team members will be specialists in certain areas and may see things that haven’t yet been considered. Lastly (and maybe most importantly) if the team are simply spoon fed a spec and expected to build it, they aren’t being engaged in the work – they are far more likely to care less about what is being built.

Ready for Planning

The team make sure that the stories have test approaches, reams of acceptance criteria, no unresolved dependencies and that everyone believes the stories are clear enough to work on them. This is a prerequisite to allowing the work to be planned into a sprint. Without this gate to progression, work can be started that just can’t be finished. Working on something that can’t yet be delivered is a waste of time.

Questions with Answers

During the sprints, the Product Owner and QA are on hand all the time for direct face to face discussions about the work. “Does this look right?” “Can we reduce the number of columns on the screen?” “Is this loading quick enough?” – developers are at the sharp end and need to have answers right there and then so they can build. Without Product and QA representation available, a simple question like these can stall a story for an hour, a day or maybe too long to complete in the sprint.

And More

This is one small, quite contrived scenario. In real life things are rarely as straightforward but with every interaction and every piece of work within the team and beyond there is the risk for some kind of derailment. To list every scenario would take forever, so how can problems be avoided?

Knowing Their Jobs

Each individual in this team knew where they fitted into the puzzle. Everyone worked together as a team. In fact things need to go a little further than that for the best outcome – team members should know what each other’s jobs entail. Take the Technical Lead role; they should be protecting their team from ill conceived ideas (even when there seems to have been a lot of effort gone into those ideas). It’s part of their job to question whether proceeding with a given piece of work is the best thing to do. When they do raise concerns, these should be listened to and discussed with a level of maturity and mutual respect that befits someone who fulfilling one of the requirements of their job. Equally, when a QA suggests that a feature seems flawed even though it passes acceptance criteria, their issue should be addressed, even if nothing is ultimately changed. This is part of the QA’s job – raising issues of quality.

I’d like to outline what I see as an excellent balance of team members and responsibilities. I don’t mean to insinuate that this is the only way a team can work – in fact I encourage every team to find their own way. Regular retrospectives where the team look at how they’re performing, what works and what doesn’t, allow the team to form their own processes. This is nearly always preferable to mandating how things should be done as people are more likely to stick to their own ideas.

That having been said, I believe the lines are there to blur and if I were to define roles around those lines, it would be like this:

Product Manager

The Product Manager is responsible for the product road map. They are focussed on what the end users are missing in the product as it stands and they are working to define feature sets that will better meet the end user’s requirements and better any competition. It’s a trade off between effort, risk, how badly the feature is wanted, when it is technically feasible to implement it.

It is vitally important that their roadmap is fully understood initially by the Product Owner and then by the senior members of the team. Decisions are constantly being made during delivery which benefit from a knowledge of product focus.

The Product Manager is not responsible for writing stories or working with the development team beyond receiving demo’s of completed or near completed work. They’re not responsible for the velocity of the team or for managing the team in any way, although they do have a vested interest in when things are going to get delivered and will almost certainly require an explanation if things can’t or don’t happen as quickly as they’d like.

Product Owner

The Product Owner can best be thought of as an agile Business Analyst. They are responsible for communicating the vision of the Product Manager to the team. They sit within the team and are answerable to the Team Lead rather than the Product Manager. This might seem odd but the team needs them to put their need to understand the product ahead of anything else. Without good understanding of what is being built, the team cannot hope to build the right thing.

The Product Owner wants their stories to be understood, so they will want the team to be involved in deciding what information is recorded in a story and how it is formatted. Story design will usually evolve over a few sprints from discussions during retrospectives. It is the Product Owner’s sole responsibility to make sure that all functional details are described once and only once and that none are left out. They will often work closely with the team’s QA to make sure all functional aspects have acceptance criteria before the story is presented in a grooming session. At a minimum, before a story is allowed to be planned into a sprint, all functional details must have an acceptance criteria to go with them. It is quite acceptable for these acceptance criteria to be considered the specification, rather than there being two different descriptions of the same thing. This reduces duplication, which is desirable because duplication leaves a story open to misunderstanding.

The QA should be focussing on automation as much as possible. The last thing a QA wants to do is spend their time testing – it isn’t a good use of their time. Yes, there are a few things that are still best done by opening the app and having a look and I’m not saying that automation should be solely relied on, but it should be the default approach. Recognising that something can’t be automated should be the exception rather than noticing that something could. Something automated never needs to be tested again until that thing changes. Something manual adds to the existing manual set of tests. Only so much of the latter can go on before the QA has no time to really think about the quality of the product.

The QA should be happy that they understand how they are going to ensure the quality of every single story picked up by the team. They should have recorded acceptance criteria which act as a gateway to ‘done’ for the developers and a reminder for the QA about different aspects of the story.

Sometimes there will be several different levels of criticality to functionality. For example, imagine a piece of work on a back office system which includes modifications to an integration to a customer facing system. It’s not the end of the world if the back office system needs a further tweak to make things absolutely perfect, but if the integration breaks, then end users may be affected and data may be lost. The integration should definitely be tested with automation – for every field and every defined piece of logic involved. The internal system’s ui, could probably be tested manually, depending on the circumstances.

The QA should make sure they spend time with the Product Owner looking at new stories and working quite abstractly to define acceptance criteria around the functionality. During grooming, technical considerations will kick up other acceptance criteria and a decision around what needs to be automated and what doesn’t can be made by the team. A decision which the QA should make sure is made actively and not just left to a default recipe.

Architect

The Architect is not really a part of a specific team. They will have their own relationship with the Product Manager and will be familiar with the product road map. They will have three main considerations on their mind:

They will be looking at the direction that technology in general is going and will be fighting the rot that long lived systems suffer from. This isn’t because code breaks, quite the opposite – the problem is that working code could stay in place for years after anyone who had anything to do with writing it has left the company, even if that code is not particularly good. Replacing working systems is a difficult thing for businesses to see a need for but if the technology stack that is relied on isn’t continuously refreshed then it becomes ‘technical debt’. Something that no-one wants to touch and that is expensive to fix.
They will be making sure the the development teams have enough information about the desired approach to system building. If following a DDD approach, the teams need to know what the chosen strategy is for getting data from one subdomain to another. They want to know what format they should be raising their domain events in, how they should be versioned. Given new ideas and technologies, they need to know when it’s ok to start using them and more importantly, when it’s too premature to start using them.
In conjunction with the Product Roadmap, they will be defining the Technical Roadmap. This document takes into consideration what Product are wanting to do and what the technical teams are wanting to do. It’s almost a given that the Technical Roadmap will have to feedback into the Product Roadmap as it shows what needs to be done to deliver. For this reason, it’s generally a good idea not to consider a Product Roadmap complete until it has been adjusted to accommodate the technical plan.

In the scenario at the start of this post, the Architect was consulted because additional infrastructure was going to be needed. This is something that could happen several times a week and something that the Architect should be prepared for. They need to give definite answers for what should be done right now, not what that decision would be if the question was asked in a month’s time – this leads to premature adoption of new concepts and technologies that aren’t always fully understood or fully agreed on.

Developers

The Developers are at the sharp end. They should have two main focusses, and make no mistake, both are as important as each other:

They need to build the Product.
They need to work out how they can become better developers.

Notice how I haven’t mentioned anything about requirements gathering. This is something that has classically been considered what most developers overlook, but in a development team this is done by the Product Owner, Product Manager and to a lesser extent the QA. It’s this support net of walking talking specifications combined with well defined stories that allow a developer to focus on doing what they do best, writing code.

Something that can be ignored by less experienced developers is that the Product is not just the code that makes it up; it has to be delivered. If building a web application then this will ultimately have to deployed, most likely into at least one test environment and into production. Maybe this process is automated or is handed on to a ‘Dev Ops’ team, but it’s still down to the developers to build something that can actually be deployed. For example, if a piece of code that would normally talk to a database is changed so that it now only works with a new version of the database, how do we deploy? If we deploy the database first, then the old code won’t work when it calls it. If we deploy the code first then the call to the old database won’t work. There could be dozens of instances of the code, which could take hours to deploy to one by one – it isn’t usually possible to deploy data changes at exactly the same time as deploying code. Basically, the Developers have to keep bringing their heads out of the code to think about how their changes impact other systems.

Technical Lead

Technical Lead is a role that is very close to my heart as it’s a role I tend to find myself in. I believe that if a development team delivers a product, then a Technical Lead delivers the team. They are technically excellent but are split focussed – they are as much about growing the team as they are about making sure the team are delivering what is expected.

There is a lot of noise about a good Technical Lead being a ‘servant leader’ and for the most I think this is true. Still, there are times when it’s necessary to be direct, make a decision and tell people to do it. When to use each tactic is something only experience teaches but get it wrong and the team will lose focus and cohesion.

It’s quite common to find that a Technical Lead has one or more developers in their team that are better coders than themselves. It’s important for someone in the lead role to realise that this is not a slur on their abilities; the better coder is a resource to be used and a person to grow. They aren’t competition. This often happens when developers don’t want to split their focus away from the technology and onto the people. They become incredible developers and eventually often move into a more architectural role. Because of their seniority, they can also stand in for the Technical Lead when it’s needed. Which can allow a lead to occasionally focus on building something specific (it’s what we all enjoy doing, after all).

Ultimately it’s down to the Technical Lead to recognise what is missing or lacking and make sure that it is made available. They see what the team needs and makes sure the team gets it (even if sometimes that’s a kick up the arse).

Blurring the Lines

Not every team has enough people to fill all these roles. Not every company is mature enough to have the staff for each of these roles. So this is where the lines begin to blur.

It isn’t always critical to have each of these roles fulfilled as a full time resource. Each company and team’s specific situation needs to be considered on it’s own merits. What is critical is understanding why these roles exist. This knowledge allows the same individual to have different hats at different times. But beware of giving too much power to one person or to removing the lines of discussion which is what generates great ideas.

So What Actually Makes it Work?

In a highly technical environment I find my own opinion on this very surprising. I don’t think it’s any individual’s technical ability or how many different programming languages they can bring to bear. I don’t think it’s having every detail of every epic prepared completely before development work starts. Primarily, consideration must be given to the structure and dynamics of a team. the above is an excellent starting point although as I’ve already mentioned, it may be that multiple roles are taken by any one individual. Other than this, the I believe a successful team will have these qualities:

Patience, mutual respect and a healthy dose of pragmatism.

If there is one constant in every team I’ve ever worked with or in, it’s that some things will go wrong. Mistakes will happen – no-one is immune (and if they claim otherwise don’t believe them). Making progress forwards doesn’t mean always building the most incredibly perfect solution, it means getting product out the door which end users will be happy with. So if there are mistakes, have the patience to realise that it was inevitable. If you make the mistake, have the respect for the rest of your team to realise that they can help fix things – believe that they aren’t judging you by your mistake. Finally, remember that the perfect solution is not the perfect system – there’s more to delivering software than trying to find all the bugs.

A team with these values will ultimately always outperform a collection of technically excellent individuals.