Udi Dahan   Udi Dahan – The Software Simplist
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Archive for the ‘Architecture’ Category



Microservices presentation [London 2014]

Tuesday, July 21st, 2015

… in which I realize I shouldn’t put off blogging about the presentations I’ve given.

This one is from µCon 2014: The Microservices Conference at Skills Matter in London.

microservices

The title of this talk was: An Integrated Services Approach

and the description:

After many years of the largely enterprise-scale SOA philosophy being applied across multiple systems, we’re now seeing some of that philosophy being applied to the design of the systems themselves with Microservices. Unfortunately, unless we integrate these enterprise and system level philosophies appropriately, we’ll end up with a mess of data duplication and coupling that may even result in businesses running on inconsistent data. Join Udi for a discussion of a unified approach that leverages the best of both worlds.

Hope you find it interesting.



Service-Oriented Composition (with video)

Wednesday, July 30th, 2014

When telling people about my approach to SOA, in which a given service would have client/browser-side components running side-by-side in the same process and even in the same page as components from other services, I often get asked this question:

“Doesn’t all of this loosely-coupled composition come with a high cost, in terms of client to server chit-chat?”

So, I’ve finally buckled down and put together a slide to illustrate how the technocratic IT/Ops service I’ve talked about in the past can provide components to resolve these sorts of problems.

After putting the slide together, and realizing some animation would do it good, I went and made a short (5 min) video including some verbal explanation as to how it all works – just for clarity. Check it out or watch it here:

And here’s the image showing everything in one picture:

Service-oriented composition



People, Politics, and the Single Responsibility Principle

Monday, May 26th, 2014

PeopleIn one of Uncle Bob’s recent blog posts on the Single Responsibility Principle he uses the example of using people and organization boundaries as an indication of possible good software boundaries:

When you write a software module, you want to make sure that when changes are requested, those changes can only originate from a single person, or rather, a single tightly coupled group of people representing a single narrowly defined business function. You want to isolate your modules from the complexities of the organization as a whole, and design your systems such that each module is responsible (responds to) the needs of just that one business function.

This is something that often comes up when I teach people about service boundaries when it comes to SOA – organization boundaries are the most intuitive choice.

And, once up on a time, that intuition might have indeed held up.

Stepping back in time

In the age before computers, organizations had a very specific way of structuring themselves.

People who had to work closely together sat in close physical proximity to each other. Data that was required on an ongoing basis would be in file cabinets also physically co-located with the people using that data, and it would be structured in a way that was optimal for their specific purposes. All of this was due to the high cost of communicating with people farther away.

If you needed data from a different department, you had requisition it by filling out a special form, put it in your outbox, and then some guy from the mail room would pick it up, and physically schlep it to the right department, putting it in their inbox, and then someone there would get your data for you – putting it together with your original request, and then the mail guy would schlep it back. This inbox/outbox style of communication should ring a bell from the messaging patterns I talk about with NServiceBus.

As a result, different departments had to have very clearly delineated responsibilities with minimal overlap with each other. The organization just couldn’t function any other way.

And then a bunch of us geeks came along.

Enter the age of computers and networks

By introducing this technology, the cost of communication across large distances started falling – slowly at first, and then quite dramatically.

When anyone in an organization was able access data from anywhere in the blink of an eye, an interesting dynamic started to unfold. All of a sudden, the division of responsibility between departments wasn’t as critical as it was before. When an employee needed to do something, there wasn’t this “that isn’t our job, you need to go to so-and-so” reaction. Because things could be done instantly, that’s exactly what happened.

And then came the politics

By removing the cost of communication, it became possible for more power-hungry people in the organization to start making (or trying to make) decisions that they couldn’t have made before. The introduction of computers into an organization was heralded as a new way of doing business – that the old organizational boundaries were a relic that we should leave behind us.

And thus can the re-org (the first of many).

Responsibilities and people were shuffled around, managers vied for more power, and politics took its’ place as one of the driving forces in the company structure.

Nowadays, if you want a decision made in a company, there isn’t just one person who has the authority to sign off on it anymore. No, you need to have meetings – and more meetings, with people you never knew existed in the company, or why on earth they should have a say on how something is supposed to get done. But that is now our reality: endlessly partially overlapping responsibilities across the organization.

So, what of the Single Responsibility Principle

This just makes it that much harder to decide how to structure our software – there is no map with nice clean borders. We need to be able to see past the organizational dysfunction around us, possibly looking for how the company might have worked 100 years ago if everything was done by paper. While this might be possible in domains that have been around that long (like banking, shipping, etc) but even there, given the networked world we now live in, things that used to be done entirely within a single company are now spread across many different entities taking part in transnational value networks.

In short – it’s freakin’ hard.

But it’s still important.

Just don’t buy too deeply into the idea that by getting the responsibilities of your software right, that you will somehow reduce the impact that all of that business dysfunction has on you as a software developer. Part of the maturation process for a company is cleaning up its’ business processes in parallel to cleaning up its’ software processes.

The good news is that you’ll always have a job 🙂



On that Microservices thing

Monday, March 31st, 2014

antsSeems that I’m a bit late to the Microservices party – original article here.

But since I’ve been getting repeated requests to weigh in on the topic, I guess I’ll have to risk fanning the flames up again.

Also, since quite a few reactions have already been written on the topic (and I don’t want to repeat them here), I’ll just point to this post by Arnon which sums them all up pretty well.

Now, I don’t entirely agree with all the commentary Arnon pointed to, or all of his thoughts on the topic, but I’ll try to take those up some other time.

And before jumping into it, let me say that there is a lot of good stuff in the article and that, regardless of naming, spreading the word more broadly on these approaches has value.

So, where do I stand on the topic

First of all, for those of you who have been following my blog for a while I’d say this:

Microservices almost equals Autonomous Components.

Why “almost”?

Because an Autonomous Component (AC) isn’t necessarily a physical unit of deployment – very often we’ll see multiple ACs deployed in the same physical process. One of the most common occurrences is in a web front end built as a composite UI. In the same web server process we’ll see components from multiple Services.

This is something that was hardly mentioned in the original article.

On Services and Systems

In my world, Services are a larger organizing principle that are meant to align solution domain boundaries with problem domain boundaries.

Now, that might sound very similar to this passage from the original article:

“The microservice approach to division is different, splitting up into services organized around business capability. Such services take a broad-stack implementation of software for that business area, including user-interface, persistant storage, and any external collaborations. Consequently the teams are cross-functional, including the full range of skills required for the development: user-experience, database, and project management.”

Now, this isn’t entirely surprising because I did have several conversations with both James and Martin on the topic over the past couple of years.

Still, there is something important missing here that I believe is very important to achieve loose-coupling, and that is that Services necessarily have to span system boundaries.

Let me repeat that: a Service will need to have components that are deployed to more than one system.

Here’s why:

Let’s say you have a piece of data like the price of a product. Not only will that data be visible in one system, often it will need to be shown (as well as updated) in other systems too. In order to have appropriate encapsulation of that concept, the owning service will need to be the one that owns the components that operate on that concept in the other systems.

This means that if we need to show the product price on an invoice in a back-end system, then that invoice would have to be a composite UI as well, and the service which owns the price will have a component deployed there which would be responsible for showing the price on the invoice.

In this manner, no code outside the service boundary would know about the concept of the product price and thus could not end up coupled to it.

Although the original article does get into this to some degree (when talking about Decentralized Data Management), I don’t really see how a microservice/AC could end up having this level of ownership of data.

Still, the point made about different persistence technologies is valid at the level of services (though not ACs).

How big is a service

Now, if the price is not shared outside the boundary of the service, then how would order totals be calculated?

The answer is that the totals must (MUST) be calculated in the same service.

This shouldn’t be surprising as it’s just good old OO – encapsulating data with the logic that operates on it. Or, if you’d like, call it the Single Responsibility Principle: there should only be a single service impacted by a change to the definition of this data.

As a result, you’ll tend to see services that aren’t all that small, and probably not so many of them. In my experience, I’ve seen between 7 and 15 services the majority of the time.

Cross-service collaboration

Although I am glad to see the recommendation for event-based interactions between microservices, the focus on cross-process communication ignores some extremely important collaboration scenarios – the most important of which is in the client tier.

In a web application, it is quite common to have components written in javascript from multiple services interacting among themselves in the browser – one publishing events, others subscribing to those JS events. It is also quite common to see those JS components request some data from back-end components in the same service in response to those JS events.

This type of synchronous RPC communication within a service boundary is perfectly acceptable, although it stands in contrast to the recommendations of the microservices approach.

Caveat on sharing data

I’ve been going on and on about the importance of not sharing data, but there is one exception to that rule.

There is a special service that I call IT/Ops which (among other things) is responsible for integration with 3rd party systems. As a part of this integration, it encapsulates data transformation logic and, as a result, needs to be able to receive data from the other more business-centric services.

As you can imagine, this puts IT/Ops in the risky position of coupling itself to a lot of things and thus needs to be done carefully. As a result, I recommend that many of the most skilled technical people work within the IT/Ops team, also serving in a consultative capacity to the other service teams.

In closing

I am extremely thankful to Martin and James for writing the Microservices article.

I think that the conversations it has sparked are timely, and hopefully more people will ponder these questions of how to structure their code-bases in order to avoid them becoming monolithic.

And while I think that it’s great to consider aligning team boundaries with service boundaries, people need to understand that it will need to be an evolutionary process – it will take time to transition an existing code base and an existing team structure to this new model, especially since these teams will have to continue to deliver features and bug fixes through the transition period. Jumping to the new model directly may cause more harm than good.

This is actually one of the most salient topics of my course (next one in NYC in May) – how do you get there from here. In my experience there are 4 phases that companies go through, often taking at least a couple of years, with larger environments taking potentially longer.

In any case, let’s keep the conversation going.

What are your thoughts? Have you been applying the Microservices approach, or possibly the one I talk about (I really should give it a name). What’s been working well for you? What hasn’t?

Leave me a comment or write your own blog post.



Thoughts on a career in software development

Friday, December 27th, 2013

helping_handFor much of the history of computers, programmers really only had one path to take – upward into management.

While you could go from Junior Programmer to Senior Programmer, sooner or later you were faced with the choice of becoming a Team Lead or having your career stagnate.

The primary difficult with becoming a team lead is that the skills that made you an excellent Senior Programmer didn’t really carry over to leading a team.

On leading teams

Much ink has been spilled (and keyboards been pounded) on this topic, so I’ll just give the common solution that is proposed to this issue – having a parallel technical career track to the traditional management track.

After being a senior programmer, developers can grow into architects and upwards. IBM, for example, has the title “Fellow” reserved for this ultimate level.

An IBM Fellow is an appointed position at IBM made by IBM’s CEO. Typically only 4 to 9 IBM Fellows are appointed each year in May or June. It is the highest honor a scientist, engineer, or programmer at IBM can achieve. —Wikipedia

All that’s well and good, but I have a feeling that something is still missing.

Why does it have to be either/or?

What if we allowed, nay – encouraged, developers to try both types of roles as they advance in their career?

After your first year as a senior programmer, you are then assigned to be a mentor to a junior programmer. You don’t assign them work, but take responsibility for some of their professional development. During this time, you also start learning what it takes to be a good team lead and developing your soft skills – yourself being mentored by a more senior team lead (probably not a good idea for it to be the team lead on the project you’re working on). From there, you take on a team lead role on a small-ish project leading 2-3 other developers.

During your time as a team lead, architects in the company work with you to deepen your technical knowledge of larger system concerns – grooming you for your next role: an architect. Your experience as a team lead gives you new found appreciation for managing technical risk.

Later, as an architect with developed soft-skills, you are now much more capable of getting teams to adopt your ideas and to want to do “the right thing”, rather than just deliver the project any way they know how. Even as you develop your expertise in various technological areas, the organization has an eye on bringing you back to being a team lead, this time on a larger project.

In praise of the zigzag

I think this has actually been happening more than just a little in our industry, although I believe it usually happens as people move from one company to another.

Is it possible that the limitations of the structures in their previous companies contributed to their choice to move to another company? Well, I wouldn’t discount it.

I don’t think companies should pigeonhole developers – either you’re an X or a Y.

Human beings thrive on variety and occasionally stretching out of their comfort zone.

I believe this model optimizes for people’s personal growth and can be tuned quite easily.

I think this is also very much in alignment with the Software Craftsmanship movement and can make it easier for companies to develop and hold on to the talent they’ve been lucky enough to hire in the first place.

In closing

While I believe this model is workable for a lot of the software industry, both for consulting companies and internal development organization, it’s clearly not going to be applicable for small startups. That being said, if the startup is successful and starts growing, it might not be such a bad idea to lay the groundwork for the team early on.

I don’t claim that this is the “best model” out there, and I haven’t tried it myself (yet), but I do believe that it has potential and would love to (re)spark the conversation about processes and structure that has seemed to die down under the Agile maxim of “Individuals and interactions over processes and tools” (though I believe that Agile as a whole *has* gotten us pointed in a better direction than where the industry was before).

What are your thoughts?

Write a comment or, even better, write something on your blog and spread the word!



Ask Udi 1: Alternative Architectures & Preaching to the Unconverted

Friday, June 28th, 2013

As promised, the podcast is back.

Download episode 1 here      and then      Subscribe to the feed.

There were 16 questions submitted and a couple hundred votes for the various topics. I was able to cover the top two questions.

Do you have a question you want to ask?
Want to vote on which questions will be answered next week?
Click here

This week’s questions

Rob Eisenberg asked:

It seems that every project I walk into has the exact same architecture, regardless of what the company is building. It’s that standard 3-tier pattern: data-business-presentation. But, there are other large-scale architectural patterns available. I’d love to hear some case studies that pair business problems with the rationale for choosing an “alternative architecture.”

And since it’s not just about knowing the right approach but also being able to convince others, I included Rvonwink’s question too:

Some of us see the genuine benefits of pub/sub, EDA and SOA design. However, how do you go about persuading the cynics, time pressed and uninformed:

Our developers hate debugging pub/sub models; Others love the ‘simplicity’ of monolithic domains; Our DBA questions why messaging is required (since “the bus simply persists messages elsewhere”); Our sys admins hate deploying new applications or changing the deployment topology; Our boss is scared to tell the business there is a little extra work to start splitting apart services.

Next week

Currently the top questions for next week are:

  • Composite UI, Business Components and Deployment
  • How to handle predetermined technology choices
  • How do you manage NULL pointer exception in general?

What would you like to hear? Let me know.

Until next week…



Queries, Patterns, and Search – food for thought

Sunday, April 28th, 2013

fishWith all the talk of CQRS, the area that doesn’t get enough treatment (in my opinion) is that of queries. Many are already beginning to understand the importance of task-based UIs and how that aligns to the underlying commands being sent, validated, and processed in the system as well as the benefits of messaging-centric infrastructure (like NServiceBus) for handling those commands reliably. When it comes to queries, though, it isn’t nearly as well understood what it means for a query to be “task based”.

Starting with CRUD

Let’s start with a traditional CRUD application and work our way out from there.

In these environments, we often see users asking us to build “excel-like” screens that allow them to view a set of data as well as sort, filter, and group that data along various axes. While we might not get this requirement right away, after some time users begin to ask us to allow them to “save” a certain “query” that they have set up, providing it some kind of name.

That, right there, is a task-based query and it is the beginning of deeper domain insight.

Pattern matching

Any time a user is repeatedly running the same query (this can be once a day or some other unit of time) there is some scenario that the business is trying to identify and is using that user as a pattern-matching engine to see if the data indicates that that scenario has occurred.

It’s quite common for us to get a requirement to add some field (often a boolean or enum) to an entity which defaults to some value and then see that same field used in filtering other queries. These measures are sometimes instituted as a temporary stop-gap while a larger feature is being implemented, though (as the saying goes) there is nothing more permanent than a temporary solution.

Where we developers go wrong

The thing is, many developers don’t notice these sorts of things happening because we don’t actually look at the kinds of queries users are running.

One excellent technique to better understand a domain is to sit down with your users while they’re working and ask them, “what made you run that query just now?”, “why that specific set of filters?”.

What I’ve noticed over the years is that our users find very creative ways to achieve their business objectives despite the limitations of the system that they’re working with. We developers ultimately see these as requirements, but they are better interpreted as workarounds.

I’ll talk some more about how a software development organization should deal with these workarounds in a future post, but I want to focus back in on the queries for now.

Oh, and don’t get me started on caching or NoSQL, not that I think that those tools don’t provide value – they do, but they’re only relevant once you know which business problem you’re solving and why.

Not all queries are created equal

Even before bringing up the questions I described in the previous section, any time you get query-centric requirements the first question to ask is “how often will the user be running this specific query?”.

If the answer is that the specific query will be run periodically (every day, week, etc), then drill deeper to see what pattern the user will be looking for in the data. If the person you’re talking to doesn’t know to answer that question, then go find someone who does. Every periodic query I’ve seen has some pattern behind it – and in my conversations with thousands of other developers over the years, I’ve seen that this is not just my personal experience.

But there is a case where a query does get run repeatedly without there being a pattern behind it.

I know this sounds like I’m contradicting myself, but the distinction is the word “specific” that I emphasized above.

There are certain users who behave very differently from other users – these users are often doing what I call research, i.e. the “I don’t know what I’m looking for but I’ll know it when I see it” people.

These researchers tend to repeatedly query the data in the system however they tend to run different queries all the time. This is the reason why traditional data warehouse type solutions don’t tend to work well for them. Data warehouses are optimized for running specific queries repeatedly.

Keeping the Single-Responsibility Principle in mind – we should not try to create a single query mechanism that will address these two very different and independently evolving needs.

And now on to Search

Search is a feature that is needed in many systems and whose complexity is greatly underestimated.

While the developer community has taken some decent strides in understanding that search needs to be treated differently from other queries, the common Lucene/Solr solutions that are applied are often overwhelmed by the size of the data set on which the business operates.

The problem is compounded by our user population being spoiled by Google – that simple little text box and voila, exactly what you’re looking for magically appears instantaneously. They don’t understand (or care) how much engineering effort went into making that “just work”.

Lucene and Solr work well when your data set isn’t too large, and then they become pretty useless as the quality of their results degrades. The thing is that many of us in IT tend to work on projects where we have an unrealistically small data set that we use to test the system and, at these volumes, it looks like our solutions work great. But if you have 20 million customers, do you think a full text search on “Smith” is going to find just the right one?

Larger data sets require a relevance engine – something that feeds off of what users do AFTER the query to influence the results of future queries. Did the user page to the next screen? That needs to be fed back in. Did they click on one of the results? That needs to be fed back in too. Did they go back to the search and do another similar search right after looking at a result – that should possibly undo the previous feedback.

And that’s just relevance for beginners.

You know what makes Google, you know, Google? It’s that they have this absolutely massive data set of what users do after the query that informs which results they return when. You probably don’t have that. That and search is/was their main business for many years – I’m betting that it’s not your main business.

You should discuss this with your stakeholders the next time they ask for search functionality in your system.

In closing

I know that the common CQRS talking points tell you to keep your queries simple, but that doesn’t mean that simple is easy.

It takes a fair bit of domain understanding to figure out what the queries in the system are supposed to be – what tasks users are trying to achieve through these queries. And even when you do reach this understanding, convincing various business stakeholders to change the design of the UI to reflect these insights is far from easy.

It often seems like the reasonable solution to give our users everything, to not limit them in any way, and then they’ll be able to do anything. What ends up happening is that our users end up drowning in a sea of data, unable to see the forest for the trees, ultimately resulting in the company not noticing important trends quickly enough (or at all) and therefore making poor business decisions.

Even if your company doesn’t believe itself to be in “Big Data” territory, I’d suggest talking with the people on the “front lines” just in case. Many of them will report feeling overwhelmed by the quantity of stuff (to use the correct scientific term) they need to deal with.

It’s not about Lucene, Solr, OData, SSRS, or any other technology.

It’s on you. Go get ’em.



Life without distributed transactions

Monday, December 31st, 2012

transactionsOccasionally I get questions about the issue of transactional messaging – why is it so important, why does NServiceBus default to this behavior, and if we didn’t use it, what bad things could happen. I’m talking specifically about the ability to enlist a queue in a distributed transaction here.

I think the reason for this interest is the rise in popularity of cloud platforms and queuing systems like RabbitMQ (which don’t support distributed transactions) and the difficulty of setting up distributed transactions even in on-premise.

Of course, there’s also the regular scalability hand-wringing going on even though most people wouldn’t bump up against those limits anyway.

In this post, I’ll talk about the nature of the problem, explain the pitfalls in some of the common solutions, but I’ll put off the description of how to provide consistency without distributed transactions to a future post as this one is already going to be quite long.

I’ll start with the basic fault-tolerance issues and then explain how things spiral out from there.

Starting with the basics

OK, so we have a queuing system in place that dispatches messages to our business logic which does some transactional work against a database.

Let’s say that we completed the transaction against our database but before we could acknowledge to the queue that the message was processed successfully, our machine crashed. What our machine comes up again, the queue will once again dispatch us the same message. Unless we have some logic to detect that we’ve already processed it (called “idempotence” in the REST community), we will end up processing it again.

In short, the problem is duplicates.

Attempted solutions to the duplicate problem

Most queuing systems don’t do anything about duplicates, actually giving it a proper architectural name: At-least-once message delivery, as opposed to the Once-and-only-once model that a queue that supports distributed transaction provides.

The solution often suggested is to have your logic check to see if it has already processed a message with that ID before – in essence storing the ID of each message processed for some period of time. Of course, there is some performance overhead with that, but it might be a small price to pay compared to dealing with it in the logic of every use case.

On the other hand, you’ll often have some messages (like Update commands) for which it looks like you can safely process them multiple times, in which case you might want not to pay the performance overhead there. The thing is, if your logic publishes an event in addition to the regular database work (something that is quite common) and you process the same message twice, you will probably end up publishing the event twice as well.

These duplicates are different in that here we have two distinct messages with different IDs that contain the same business data. This means that recipients of these messages will not be able to filter them out at an infrastructure level anymore.

NOTE: Deduplication abilities in queues

Although the Azure Service Bus doesn’t support distributed transactions meaning you still have the issue mentioned above, Microsoft added the ability to detect and filter out duplicates based on message contents rather than just the ID. This helps quite a bit but it’s important to understand that that doesn’t cover everything for you. Let me explain:

More complex logic

In some of your most important use cases, you may have both entity updates as well as entity creation happening together in your domain model. You might be using some kind of event model (like I wrote about here) to percolate out the information that an entity was created in order to keep your service layer decoupled from the internals of the domain model.

In the callback code from these domain events, you will likely publish out an event on the queuing system containing information like the ID of the entities created as well as other business data. And there’s the rub.

You see, without distributed transactions, you can run into some problematic scenarios:

For example, if you don’t make sure that your event publishing calls to the queuing system include the same transaction object as the one you used when retrieving the original message from the queue, then those calls could “escape” before you know if the database transaction is going to succeed. Deadlocks always happen at the lousiest times. Anyway, if you’re using database generated IDs for your entities, then those IDs will get published out in events despite the database rolling back and your subscribers will now be making decisions on wrong data – not just eventually consistent data.

In this case, processing the message again doesn’t really solve the problem – it just means that you’ll be publishing events with different IDs, so an infrastructure like Azure Service Bus couldn’t really de-duplicate them.

On the other hand, if you do use the same transaction and combine in the infrastructural message ID based de-duplication described above (as identifying duplicate calls for complex business logic is damn hard), you’ll run into another problem.

Consider what would happen if your server crashes right after finishing its database work but before it completes the transaction against the queuing system. When going to retry the message, the infrastructure filtering thing would know not to call your business logic again and that message would be quietly swallowed. Unfortunately, the event publishing calls to the queuing system from the first time the message was processed were rolled back and since your business logic isn’t called again, the event publishing won’t happen again.

Oops.

In closing

I hope I’ve been able to clarify what kind of scenarios distributed transactions solve for you and some of the difficulties in solving them yourself.

Now, to be clear, you could solve these problems by going in-depth on each of your use cases, analyzing the consistency needs and structuring the code differently to address those needs. But give this another thought, if our consistency is dependent on calling otherwise independent APIs in exactly the right order, and that a change in this order would not cause any visible functional effects, what would happen when developers with less expertise maintain this code?

The folks in the event sourcing community have their solution to this which is based on writing their business logic differently. As the adoption of this pattern is still pretty limited (probably still in the Innovator section of the Technology Adoption Curve), it’ll be interesting to see how it holds up with larger teams in the mainstream.

Oh, and in case it wasn’t clear from before, the guys in the REST community haven’t even begun addressing this problem when it comes to server-to-server integration.

We’re working on a solution for this with NServiceBus that won’t require you to change how you write business logic. We’ve got one big release to do before we can roll this in, and that’s coming soon (with all sorts of cool things like support for ActiveMQ and queues in the database). The solution we’ve found is architecturally sound but you’ll have to wait for my next post to hear about it.

Stay tuned.



Service-Oriented API implementations

Monday, December 10th, 2012

gearsIt’s quite common for our systems to need to expose an API for external parties to call that isn’t exactly aligned with our service boundaries – at least, when you follow the “vertical services” model rather than the “layered services” approach. I’ve blogged many times about the problems with layering, so I won’t go into that now beyond to say that you really, REALLY, should avoid it.

A short intro to SOA, done right

In the “vertical services” approach I espouse, you often see components from multiple services deployed to any given endpoint. While these services usually don’t need to communicate with each other at all, occasionally you’ll see them leaving “breadcrumbs” behind for each other – things like UserId or OrderId in the session. What’s especially important is that these IDs are accessible even before the entity is finalized – this enables each service to collect its own data without needing any other service to know about that data.

In an ecommerce environment, we would see one service owning money, another the product catalog (excluding prices, those would be owned by the previous service), another service owning the customers’ payment info (credit cards, etc), and yet another owning shipping addresses – all of these separate from the one that owns the shopping cart. Let’s call these Finance, Catalog, Payment, Shipping, and finally Shopping – just so that we have something to reference later.

The API

While we can do all sorts of cool browser composition with the UI in our own system, enabling each service to collect and display its own information, if we want to expose an API for clients to call, we wouldn’t want to force those clients to have to make a separate call to each service in order to make a purchase. Instead, we’d want something that looks like:

MakePurchase(Guid orderId, Dictionary cart, CreditCardInfo cc, Address shippingAddress)

In case you were wondering, the service which owns the definition of this API is different from all of the above services – it is a service that is primarily technical in nature and is responsible for things like integration and data transformations. I call this service IT/Ops.

Getting the data from the API to the services

So, we don’t want any of our business-centric services to know about anybody else’s data structures, so that leaves it to IT/Ops to pass the data to them. The thing is that we still want to do that in the most loosely-coupled way possible – with messaging being a good candidate for that.

So, what we’ll do is have IT/Ops send a message containing the data to the other services, but with a slight twist.

Here’s what the code would look like with NServiceBus:

Bus.SendLocal(new Order { Id = orderId, Cart = cart, 
                          CreditCard = cc, ShippingAddress = shippingAddress });

Why the SendLocal?

So that the components from the other services can all run together with IT/Ops in the same process giving a nice tight deployment model.

UPDATE:

If you’re using a transport like RabbitMQ that is set up as a remote broker, the overhead of going back through the broker might not be worth the improved reliability you’d get by going through messaging. In that case, you might want to consider the Domain Events approach. This would give you a similar level of decoupling but then IT/Ops would need to set up an surrounding transaction, well, that is if you want all the services processing to succeed/fail as one unit. If you don’t, you’d probably be better off just sending messages from IT/Ops to endpoints that host each of the components of the other services.

End Update

Before we get to the services, let me show you the Order class – specifically, the interfaces it implements:

public class Order : ShoppingOrder, PaymentsOrder, ShippingOrder
{
    public Guid OrderId { get; set; }
    public Dictionary<Guid, int> Cart { get; set; }
    public CreditCardInfo CreditCard { get; set; }
    public Address ShippingAddress { get; set; }
}

public interface ShoppingOrder
{
    Guid OrderId { get; set; }
    Dictionary<Guid, int> Cart { get; set; }
}

public interface PaymentsOrder
{
    Guid OrderId { get; set; }
    CreditCardInfo CreditCard { get; set; }
}

public interface ShippingOrder
{
    Guid OrderId { get; set; }
    Address ShippingAddress { get; set; }
}

Each of the above interfaces represents the data that each service cares about. Therefore, each service will provide an assembly that handles that message/data and persists it to its database, like this:


public class ShoppingAPIHandler : IHandleMessages<ShoppingOrder>
{
    public void Handle(ShoppingOrder message)
    {
        //persist to shopping service db
    }
}

public class PaymentsAPIHandler : IHandleMessages<PaymentsOrder>
{
    public void Handle(PaymentsOrder message)
    {
        //persist to payment service db
    }
}

public class ShippingAPIHandler : IHandleMessages<ShippingOrder>
{
    public void Handle(ShippingOrder message)
    {
        //persist to shipping service db
    }
}

Since the Order object being sent is a polymorphic match for all of these interfaces, NServiceBus knows to invoke all of these handlers. By the way, if you care about the order of invocation, then you can control that as well (but I won’t get into that here).

Also, since all of these handler assemblies are deployed to the same endpoint, and the Order object is sent just once, this means that all the handlers will be invoked in a single transaction on a single thread – either all of them succeeding, or all failing. Since they’re all connected on the same Order Id, referential integrity can be preserved as well.

Wrapping up

When you are building a system on SOA principles, you’ll often find that you need a service like IT/Ops to handle data transformation and other broker-centric tasks. While much of SOA is based on the Bus Architectural Style – meaning primarily publish/subscribe interaction between services – that doesn’t mean that your business-centric services cannot have their components deployed in the same process.

I’d go so far as to say that if you aren’t deploying components from multiple services in process with each other at least some of the time then it’s quite likely that your service boundaries are probably incorrect.

Anyway, I hope you found this post interesting. Shout out to Slawek who gave me the idea for this post.

By the way, if you’d like to learn more about these kinds of patterns, the next batch of courses is open for registration – but the early bird prices are almost over, so you’d better hurry.

Register for   Denver CO, USA,     Bad Ems, Germany,     Perth, Australia.



JPA with REST, OData, and SQL

Sunday, November 4th, 2012

Feeling a little bit rant-y today, as I just saw some more abuse of remote calls, this time on the Java side of things.

JPA is the Java Persistence API – a kind of ORM, as you’d expect. Luckily, a lot of the web services stuff was already on the way out by the time that EclipseLink DBWS came out. DBWS allowed you to expose database artifacts as web services.

I mean, it’s not like we have any other interoperable ways of accessing data, right?

Anyway, like I said, that didn’t take off, but now they’re reinventing it – this time with REST!

In case you had any doubts, REST is pure awesomeness and adding it to anything else makes it awesome too. Lest anybody take this out of context (it’s happened before), I’m being sarcastic.

Here it is.

God knows they couldn’t let Microsoft totally dominate this area with OData coming out quite some time ago. In case you were wondering, OData was designed to provide standard CRUD access of a data source over HTTP.

Of course, none of these support any transactions so if you actually wanted to do some meaningful business logic on top of this CRUD, you wouldn’t have any consistency. And, let’s face it, if you’re not doing any meaningful business logic, just basic persistence, you just do it. That problem’s been solved a long time ago.

Can we please stop reinventing SQL already?



   


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It was a pleasure to finally meet Udi in Seattle Alt.Net OpenSpaces 2008, where I was pleasantly surprised at how down-to-earth and approachable he was. His depth and breadth of software knowledge also became apparent when discussion with his peers quickly dove deep in to the problems we current face. If given the opportunity to work with or recommend Udi I would quickly take that chance. When I think .Net Architecture, I think Udi.”

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He started out with sketching a naive traditional n-tier application (big ball of mud), and based on suggestions from the audience we explored different solutions which might improve the solution. Whatever suggestions we threw at him, he always had a thoroughly considered answer describing pros and cons with the suggested solution. He obviously has a lot of experience with real world enterprise SOA applications.”

Raphaël Wouters Raphaël Wouters, Owner/Managing Partner at Medinternals
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Pasi Taive Pasi Taive, Chief Architect at Tieto
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Eran Sagi, Software Architect at HP
“So far, I heard about Service Oriented architecture all over. Everyone mentions it – the big buzz word. But, when I actually asked someone for what does it really mean, no one managed to give me a complete satisfied answer. Finally in his excellent course “Advanced Distributed Systems”, I got the answers I was looking for. Udi went over the different motivations (principles) of Services Oriented, explained them well one by one, and showed how each one could be technically addressed using NService bus. In his course, Udi also explain the way of thinking when coming to design a Service Oriented system. What are the questions you need to ask yourself in order to shape your system, place the logic in the right places for best Service Oriented system.

I would recommend this course for any architect or developer who deals with distributed system, but not only. In my work we do not have a real distributed system, but one PC which host both the UI application and the different services inside, all communicating via WCF. I found that many of the architecture principles and motivations of SOA apply for our system as well. Enough that you have SW partitioned into components and most of the principles becomes relevant to you as well. Bottom line – an excellent course recommended to any SW Architect, or any developer dealing with distributed system.”

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