Monthly Archives: February 2015

On Thursday I once again had the pleasure of presenting at the London Java Community (LJC) meetup. This time I presented a new talk “The Craft Consultant’s Guide to… DevOps”. This builds on a DevOps parody talk I gave at last year’s LJC Unconference, and also combines some of my thoughts from my earlier “Chuck Norris doesn’t do DevOps, but Java developers might benefit” talk.

The goals of this talk was to provide a high-level overview of some of the key themes of DevOps, specifically from a tooling perspective. It’s worth stating at this point that in my opinion DevOps is more about methodology, process and culture more than it is tooling. However, for the intended audience of this presentation the focus on tooling provides a framework on which to build understanding for the non-technical issues. The slides can be found below:

The original abstract for the talk can be found in the next paragraph, and as usual, if you have any comments, thoughts or (constructive) criticism then please do get in touch!

“Come along and learn how the Crafty Consultant makes his money by consulting craftily in DevOps. We’ll see how silos can be broken down by introducing more independent and isolated team, how only idiots automate everything, and why monitoring only provides actionable insight that simply confuses your clients…

…and then we’ll look at the real world implementation of DevOps 🙂 The primary aims of this talk are to introduce the concepts behind the DevOps movement, and we’ll do this by debunking all of the Crafty Consultant’s advice. We’ll cover the drivers of breaking down silos (in business and in tech), the benefits of automation (especially with provisioning and configuring infrastructure), and the power that monitoring provides (particularly when deploying to the cloud, or implementing a microservice architecture).”

Details of the event can be found on

Building Microservices – by Sam Newman


TLDR: If you are looking for an introduction to and overview of the current ‘microservice’ landscape and the concepts and thinking behind it, then look no further. I would recommend this book for architect, developer, QA and operations (DevOps)

Microservices are obviously a very hot topic at the moment, and everyone and their dog appears to have an opinion about this concept. Accordingly, writing a book about microservices and keeping everyone happy is going to be a challenge (and probably impossible).

In my opinion Sam has done a great job here and manages to provide key information on a range of relevant microservice issues, such as the motivations for microservices, how to model services, integration with other systems, deployment, testing, monitoring, security and architecting/implementing microservices at scale.

I’ve seen negative comments towards this book on other sites stating that more code examples should be provided, and although I appreciate their motivations, I don’t believe this will be the book to address these issues. In my experience, code contained within a book can quickly become stale, and the diversity of language (and the associated rate of change) that is currently being used to create microservice implementations would make pleasing everyone an impossible challenge. Instead I recommend people interested in code samples have a Google, or visit InfoQ, DZone or Voxxed where there is plenty of microservice implementation code.

In my opinion I will use this book much like I did the original ‘Continuous Delivery’ book by Jez Humble and Dave Farley – the book will provide an excellent high-level overview of the issues (and potential solutions), help me to understand core concepts and how key components and methodologies relate to each other, and also provide inspiration and pointers to further reading.

Much like I didn’t expect to create a full build pipeline implementation simply from reading the ‘Continuous Delivery’ book, I wouldn’t expect to build a complete microservice ecosystem from Sam’s book. However, after reading both books I began the respective tasks with a lot more insight then I originally had, and I made much smarter decisions (and knew what to look for when searching for more knowledge) once I understood the big picture.

As stated above, I would recommend this book for any software delivery role. I’ve personally seen the benefits of a microservice architecture when deployed for the correct use case, but the nature of this architecture creates new challenges whether you are a developer, QA or operations specialist.

(In the interest of full disclosure I did provide feedback on this book as it was being published via the O’Reilly Early Access program. However, I have endevoured to write a review that takes into account only the final published book.)

I’ve received some great feedback after posting my proposal for a microservice maturity/classification model last week, some positive, and some negative.

Some private communications suggested that I may be getting caught up in the marketing hype, and several emails suggested that the microservice architecture really is just classical SOA re-invented. Other emails balanced out these comments by suggesting that microservices present an opportunity to learn and iterate on the mistakes made in the original implementation of SOA, especially now that we are embracing concepts such as domain-driven design, and are applying more consideration to well-defined software architectures.

The only public response I’ve seen so far is by my fellow London-based microservice and Spring framework expert Russ Miles – you can read it on the Simplicity Itself blog. In the interest of full disclosure I do know Russ personally (and have sank a few beers in his company), but that’s not going to influence what I think could be a great discussion about my proposal.

Maturity – not all it’s cracked up to be…

The first comment made by Russ is that the approach of creating a maturity model could be dangerous. I think this is totally fair, and it crossed my mind several times when writing the initial post. So much so, that I added the word ‘classification’ to the title as an alternative to maturity.

If you look at other maturity models, such as the Richardson model for APIs or the Continuous Delivery model, then there is a clear sense of scale, from negative to positive. As Russ quite rightly points out, there is room for interpretation in my model that smaller is better, and I probably should have taken more care to make it clear that I don’t think this is necessarily the case.

In some cases a monolithic, but well-structured, architecture may be the best solution. Russ has also conjectured in a recent talk a Skillsmatter that starting out with building a monolith and then moving to a microservice architecture may be the fastest way to build software. It’s definitely difficult to prove this beyond anecdotal evidence, but my instincts (and experience) tell me this is probably true in certain cases, especially at the current point in time where we have little in the way of modelling or tooling support for building microservices.

In my opinion Russ is quite right to think about how this model could be used negatively, and although my initial intention was to give people a model that they could look at and point to where they think their software is, it could easily be abused. I would be keen to get more feedback on how the model could be shaped or evolved to make my intentions clearer.

Size – it’s what you do with it that counts (but size still matters)

Russ also mentioned that size is a dangerous metric, and I agree. Although lines of code (KLOC) is potentially an arbitrary metric, especially with the variety of languages and frameworks currently available, I still do believe that size is important. Not in the “if you’re application is over a 100 lines, then it’s not a microservice” kind of way (which, in fairness, could have been read from my model), but in the perspective of encapsulation, responsibility and comprehension.

After a bit more thought, a measure of architectural/code cohesion is probably a better metric for this concept. I definitely believe the microservice architecture is rooted in the principle of high cohesion (and loose coupling), but it has been argued by the likes of Simon Brown and Bob Martin that this can be achieved in a monolithic codebase without the need for the creation of separate ‘services’. The key here is modularisation or componentisation.

Accordingly, I do believe that microservices should be ‘small’ in size. For me, this was one of the failings in the original approach with SOA. The lack of skilled modelling and architectural guidance allowed services to morph into ‘all singing and dancing’ applications that offered low cohesion. Hard system boundaries (and potentially expensive coordination and communication) provided by microservices in combination with the notions of ‘bounded contexts’ from domain-driven design (DDD) should make it more obvious to developers when we are straying outside the remit of a component.

Bloated vendor tools that emerged from traditional SOA also allowed developers to ‘cheat’ by circumventing the loose coupling that patterns such as the service bus initially proposed, and monstrosities such as the heavyweight ESB were born. These days we are seeing tooling emerge that encourage reactive systems and event-driven architectures based on small components (such as the very interesting AWS Lambda). With services such as AWS Lambda a codebase size limit is enforced due to the nature of execution. It will be interesting to see what applications emerge from these frameworks.

Putting a size limit on a codebase may not be an exact science, but I believe an upper bound can at least be used as a trigger to discuss if a service is growing beyond it’s original remit (or if the architectural quality is degrading). A lot of agile and architectural techniques I teach clients are not hard-and-fast rules to determine which decisions should be made, but often act as a cue for the team (or organisation) to engage in conversation or a whiteboard session to check that we are still designing high-quality software that models the business correctly.

Dogma or dogfooding – you decide…

The final section of Russ’ post contains the strongest argument, in that dogma over thinking will only lead us down the wrong path “A maturity model can be used in place of thinking; I’d like to avoid that if we can”. Yeah, this sucks, but I agree.

The problem is that my academic background drives me towards the sharing of ideas and proposals among my peers, and I enjoy the ensuing discussion. We should always take care to make sure we are being pragmatic in these discussions (and not “solving the world’s problems at the dinner table”), but I’m still a supporter of pushing stuff out to the public for comment.

Russ also makes a great reference to Greg Young’s talk at muCon last year, which should be essential watching for anyone building microservices. Paraphrasing Greg massively, he suggested that a lot of the concepts behind microservices have already been done before, and that if we aren’t careful then we will re-invent the wheel (albeit more ‘micro’ than before 🙂 ).

Greg’s observations about the negative impact of dogmatic standardisation and overly-opinionated vendor tooling were also especially damning, and I couldn’t help but nod in agreement through a lot of his talk (on a side note, the whole muCon conference was awesome, and I would highly recommend attending the next iteration later this year! Massive kudos to Russ for kickstarting this conference).

I’m definitely going to take care to avoid being dogmatic (or inspiring dogma), but I’m still keen to share my thoughts on things like the maturity/classification model. It might turn out that this approach isn’t useful, but I’ve already been using a slightly less polished version of this model with tech friends over the last few months to help them understand where their software stack currently sits in relation to the ‘unicorn’ organisations such as Netflix and Amazon (what else are techies going to discuss over a few beers! :- ).

Something that I believe could emerge from this type of proposal (which may be more valuable) is some kind of model that shows organisations where their software sits on the big picture scale of innovation, architecture and delivery. Each level of the model should also clearly show the benefits and drawbacks, and provide guidance on why (if at all) organisations should move some of their software to the next level. We would also need to show how organisations should go about doing this, both from a pragmatic organisational and cultural perspective (Conway’s law in action), and also from a technical tooling and process perspective.

I’m currently reading Jez Humble’s new book ‘Lean Enterprise’, and this is providing some superb inspiration for approaching these tasks. I’m also dogfooding some of my new models and processes, and as soon as I have some useful insights I’ll make sure I share them.

In summary…

I really appreciate Russ taking the time to reply to my original post, and I’m definitely going to think more of several of the great points he’s made (and I’m sure I’ll also catch up with him for a beer after an upcoming London Microservices User Group meetup).

I will also take more care to make my intentions clearer, but I’m still keen to share my thoughts and inspire debate. I’m also keen to avoid dogma, and focus more on dogfooding the model, and here I’ll use some of Russ’ comments to attempt to refine the model.

As usual, if anyone has any comments or feedback then please do get in touch!

I’ve been chatting to various people for quite some time about how there isn’t an agreed maturity model for the current trend to implement microservice architectures, and so I though I would have a go at creating one (quick link to PDF: Microservice Maturity Model Proposal).

I’m in no way suggesting this first draft is complete or definitive, but I hope it may stimulate the conversation around this topic. I’m sure some people will argue that a maturity or classification model isn’t necessary, but I believe it is a fun exercise, and it does enable us to explore (and discuss) what we think are requirements for a microservice implementation.

I’ve proposed six classifications of application architectural styles:

  • Megalith Platform
    • Humongous single codebase resulting in a single application
  • Monolith Platform
    • Large single codebase resulting in a single application
  • Macro SOA Platform
    • Classical SOA applications, and platforms consisting of loosely-coupled large services (potentially a series of interconnected monoliths)
  • Meso Application Platform
    • ‘Meso’ or middle-sized services interconnected to form a single application or platform. Essentially a monolith and microservice hybrid
  • Microservice Platform
    • ‘Cloud native’ loosely-coupled small services focused around DDD-inspired ‘bounded contexts’
  • Nanoservice Platform
    • Extremely small single-purpose (primarily reactive) services

I’ve then attempted for each classification to write about things such as, motivations, challenges, architecture, code modularisation, state data stores, deployment, associated infrastructure, tooling and delivery models.

The full proposal can be found in the following PDF ‘Microservice Maturity Model Proposal – Daniel Bryant (@danielbryantuk)

Please do let me know what you think – I’m keen to see whether this model could be useful, and also explore how it could be developed.

I’ve just got back from my first Jfokus conference in Stockholm, Sweden, where I presented the latest version of my “Thinking Fast and Slow with Software Development”. The core concept of the presentation is based on Daniel Kahneman’s bestselling book, “Thinking Fast and Slow“, and I wanted to relate the discussion of decision making heuristics and bias contained in the book to software development.

I’ve included the slide deck below, and I believe the video of the presentation will eventually be available from Parleys

Here is the original abstract:

In the international bestseller ‘Thinking, Fast and Slow’, Daniel Kahneman explains how we as human beings think and reason, and perhaps surprisingly how our thought processes are often fundamentally flawed and biased. This talk explores the ideas presented in the book in the context of professional software development. As software developers we all like to think that we are highly logical, and make only rational choices, but after reading the book I’m not so sure. Here I’ll share my thinking on thinking. Topics that will be discussed include; the ‘Availability Heuristic’, which can lead developers to choose the ‘latest and greatest’ technology without proper evaluation; ‘Optimistic Bias’ which can blind architects from the ‘unknown unknowns’ within a project; and more!

If you have any comments or questions then please do get in touch!