Celestial Bodies and Micro-Front End Reuse

Source: Wikimedia Commons

If you are writing a modern production system of any complexity, chances are you are using microservice architecture for it. If that system serves the Web browser, sooner or later you will discover that you must break up the UI into parts served by multiple micro-services (or micro front-ends).

The promise of microservices is that they can be built by separate teams, allowing teams relative independence and ability to move at their own speed, without the need to for intergalactic coordination. However, sooner or later executives (God bless them) will notice that some of the user interfaces contain elements that look similar across the system, and the dreaded word “Reuse” will raise its head.

It can sound downright heretical to say anything against reuse in software industry. That code reuse saves time and improves quality feels so innately right that it takes gumption to raise against it. What would be more logical than to create a reusable component for things that look similar and make all micro front-ends reuse them?

And yet.

Movement on a planetary scale

To try to illustrate the problem we can hit with indiscriminate reuse, let’s look at the movement of planets in a solar system. As planets rotate around the star, they follow their own orbits that place them at various distances to each other. If we simplify the geometry and make all orbits perfect circles and in the same plane, the planets will still have different rotational speed, dictated by various factors (yes, ‘Gravity’ violated many of them). This rotation will place them at various positions to each other, with two extremes:

  1. Conjunction – when two planets are lined up on the same side relative to the star and closest to each other
  2. Opposition – when two planets are lined up on opposite sides relative to the star

As planets are in constant motion, they will at any moment be between these two points.

Back to the topic

OK, so let’s bring it back to the microservice system. The reason UI component reuse is being discussed in your meetings is because a design pass was made, and the first iteration of the whole system’s user experience has been put together, and some repetition is observed. This page in micro front-end A looks very similar to the page in micro front-end B. That picker is the same in three pages. Let’s solve it once and for all for everybody. Reuse, people! Sensible leadership all around.

It is easy to fall into this trap because reuse works great for, say, libraries. Of course you will not write that set of mathematical transformations over and over everywhere. In our Node.js microservice system, the list of modules each app depends on is getting longer and longer.

I just typed npm list > deps in one of our largest microservices (I am tempted to call it Gustav for its girth). The flattened list of all dependencies is 3689 lines long. We should call it “miniservice” or just “service” by now. I am not writing 3000 modules by hand any time soon. Reuse is fine and dandy here.

Similarly, all our micro front-ends are using the same platform API layer. The APIs are ensuring the state of the microservice system is consistent. Again, I am not saving the same state in two APIs and keeping it in sync somehow – that would be crazy.

All our micro front-ends are using the same style guide and the same set of React components written to follow that guide with a set of basic visual building blocks (no, we are not using Bootstrap; yes, we know 15% of all web sites use it – good for them). Without it, our UI will look like a ransom note:


Say NO to casual UI reuse

This brings us to reusing actual parts of pages between micro front-ends. If you follow the reasoning above, it is the logical next step. This is where our astrophysics comes into play.

The pages that look similar today are like planets in conjunction. They are at their closest position in the microservice planetary system. The danger is that we are forgetting the constant movement. It may be hard to believe right now, but these pages will move apart. Why? Complex systems rarely evolve in perfect coordination. You cut your hair and a month later the cut starts losing shape, because the hair refuses to grow exactly the same everywhere. Diverging priorities, architectural changes, business pressures, reorgs all conspire against your microservices keeping their relative distance to each other.

The whole point of a microservice system is to insulate against this corporate chaos by allowing self-sufficient teams to cut through the haze and continue to make progress. Wonton UI reuse will tie the microservices together and restrict their freedom of movement. This is an elaborate way to write a distributed monolith, the worst kind. In our planetary analogy, you are applying super-natural gravitational forces between planets that completely mess up their trajectories and may result in the fiery collapse of the entire system. Or ‘Gravity 2’.

Doing it right

The heretical thought presented in this article is that some duplication and bespoke UI code is good if the outcome is preserved agility and independence of the microservice teams. Of course, thousands of lines of duplicated code is its own kind of a waste, agility or not. This is where good practices are essential, such as using back end for front end to push most of business logic to the server, leaving mostly presentation logic on the client. The business logic can then reuse libraries and modules across microservices (within reason, you need avoid the danger of increased coupling so don’t go overboard).

If you do it right, you will already use common style, common APIs, shared libraries and common widgets. The rest is just composition, where you can create a bespoke UI that perfectly fits your page and nobody will break you by pushing a change without enough testing at 2am.

Any exceptions?

Yes, there are exceptions. Some UI components are just too tricky to implement even once, let alone multiple times. You will know those when you see them – the microservice teams will come together and agree that one of them will build it for all of the teams because life is too short to fix that horrible bug 5 times.

The threshold to clear will be:

  1. Is this truly a single component, or multiple components merged together, selected with a maze of flow control and configuration parameters? If latter, don’t.
  2. Is the component simple enough and with a single purpose, more likely to survive inevitable zigs and zags of business requirements and design changes?
  3. Is the team writing the shared component up to the task and ready to write exhaustive functional and UI tests to guard against regressions and breakages?
  4. Is the problem complex enough to overcome the overhead of reuse?

Once you are true to these conditions, reusable components will be few and far between. If a once useful reused component becomes a sore point in a year, fork and take the control back.

You will reap the consequences

In complex microservice systems, some of the truisms of software development need to be put to the test and re-examined. The true test is not if applying them works at the current moment (at the planetary conjunction), but if the system will survive the opposing forces of changing business requirements, architecture evolution, aging code and organizational changes.

As engineers, we must remember that business defines requirements, design defines the UX, but we are responsible for turning the requirements and the design into clickable reality. It is our responsibility to choose that reality not only based on what our system looks like today, but what it may look like in 6, 12 or 18 months. Resist the urge to reach for quick shortcuts through casual reuse, and plan for what situation that reuse will likely put you after a few architectural and organization changes.

Like planets, your microservices will never stand still.

© Dejan Glozic, 2017






Microservice Grid and Micro Frontends

Adam naming the animals, Wellcome Library, London. Source: Wikimedia Commons.

This post is not here to bring you anything new as it is for me to run a victory lap. If there is anything I blogged about with any consistency, it was about microservices. There are many articles in this blog addressing various problems you may face when attempting a microservice system of a non-trivial scale. One area I was particularly keen on was decomposition of the front end in a way similar to what we did in the back.

You would think that it goes without saying, but a lot of microservice noise was focused on the backend. I understand that: breaking the big server into a number of smaller ones behind a routing proxy is easier to understand. REST API is REST API is REST API. A number of endpoints per microservice neatly collate into a complete system with use of session-less API services.

But what’s good for the goose ought to be good for the gender. Slapping a massive, unruly front end server in front of a nice microservice API system does not help us much, other than to highlight the irony of the half-hearted approach. That’s why I focused a lot of this blog on composing the UI microservices as well. From your favorite article on microservice authentication, to UI composition, to isomorphic microservices using Node.js and React.

Far from being armchair generals, we put our money where our mouth is, applying these ideas in production, learning more in each successive generation. The last name for this approach I used was microservice grid:

microservice-gridThe picture above represents the essence of our current approach. It is uniform in that horizontally it represents tiers (front end, back end, optional hosted legacy apps in containers). Three buses provide glue – UI domain for bringing all paths under the same URL, API domain for collating all API endpoints, and an event bus to glue the microservices using a message broker of some kind.

Vertically, each column of the grid represents a feature. What I like about this approach is that unlike with big monolith apps, adding features does not make everything bigger and slower. Adding a new feature vertical does not affect the performance of the existing verticals.

So that’s what you call it

One of my favorite hobbies now is going to Technology Radar published by ThoughtWorks and looking for how they are naming a technique we are already using in production. For example, the pattern of providing a single API gateway for your client side code is now called Back End for Front end. But what gave me no end of pleassure was that now the whole approach of this blog that I spent so much time writing about has an official name: micro frontends.

We’ve seen significant benefit from introducing microservice architectures, which have allowed teams to scale delivery of independently deployed and maintained services. However, teams have often struggled to avoid the creation of front-end monoliths—large and sprawling browser applications that are as difficult to maintain and evolve as the monolithic server-side applications we’ve abandoned. We’re seeing an approach emerge that our teams call micro frontends. In this approach, a web application is broken up by its pages and features, with each feature being owned end-to-end by a single team. Multiple techniques exist to bring the application features—some old and some new—together as a cohesive user experience, but the goal remains to allow each feature to be developed, tested and deployed independently from others. The BFF – backend for frontends approach works well here, with each team developing a BFF to support its set of application features.

Technology Radar, Nov 2016, ThoughtWorks

Like with Adam in the engraving above, things exist before they are named, but Nomen est Omen – naming our approach in a way that offers a nice symmetry with micro services gives it a renewed meaning and is a success in my book.

Therefore, go forth and build your microservice grids, your micro frontends, your Backends for Frontends, you princes of Maine, you kings of New England.

© Dejan Glozic, 2017

The Web of Hooks


It’s a new year, which means it is time to update the copyright at the bottom. I have been busy lately and I didn’t want to write fluffy blogs just to fill the space. But this time I actually have real content, so here it goes.

If you followed my blog in the past, you know I was very bullish on message brokers in the context of microservice architecture. I claimed that REST APIs alone are not sufficient to sustain a successful microservice system. Event collaboration pattern is necessary to ensure a scalable and robust system where microservices that own resource lifecycle don’t need to be burdened with executing all the code driven by that lifecycle. You can read more about it in my article about REST/MQ mirroring.

Not so fast

There is a fly in this particular ointment, however. While HTTP REST is well understood, messaging protocols are numerous. You may know from my writing that I liked MQTT for a while due to its simplicity and wide support. However, MQTT is actually not a great protocol for gluing your microservice system. It is designed to be lightweight and run on the smallest of IoT devices, and lacks some critical features such as anycast support and manual acknowledgement of messages.

Another popular protocol (AMQP) suffered a schism of sorts. The version supported in a popular RabbitMQ broker (0.91) is a very different protocol from an actual open standard AMQP 1.0 that is not as widely supported. This is a pity because I really like AMQP 1.0. It is like MQTT but with anycast and manual acknowledgment – perfect as a microservice system glue, yet still very simple to work from within clients.

And of course, there is Apache Kafka, a very powerful but odd choice given its origins in high-throughput distributed log aggregation. Kafka is unapologetically Java-centric, has a proprietary protocol and bolt-on REST APIs to connect client languages are still fairly low level. For example, where AMQP 1.0 guarantees quality of service and requires implementations to provide a buffer of messages that are re-delivered to a client that crashed, Kafka simply allows you to maintain a pointer in the queue but it is your job to work up the queue and catch up after restarting. You pay for performance by working at a level fairly low for general purpose application messaging.

Authentication pains

Choosing the messaging solution and protocol is only one part of the problem. If you want your system to be extensible and allow third-party integrations, you need to make it fairly easy for new clients to connect. On the other hand, you need to secure the clients because you don’t want a rogue app to eavesdrop on the events in the system without authorization (otherwise you have this egg on the bot face). Maintaining a large list of clients connected to the same topics can also be an scalability issue for some brokers.

For all these reasons, it has been widely acknowledged that message brokers are not a good match for external integrations. A cursory scan of popular cloud applications with large ecosystems all point at a more client-friendly alternative – WebHooks.

WebHooks to the rescue

You would think that if something is so popular and has a catchy name, there is an actual well written protocol for it. Wrong! WebHooks is the least common denominator you could imagine. In a nutshell, this is all there is:

  • You publish a list of valid events for which you will notify clients
  • You provide an API (and/or UI) for clients to register URLs for one or more of those events
  • When an event happens, you execute HTTP POST on the URLs registered for that event type.

That’s all. Granted, message brokers have topics you can publish and subscribe, and the actual messages they pass around are free-form, so this is not very different. But absent from WebHooks are things such as anycast, Quality of Service, manual acknowledgement etc.

I don’t intend to go into the details of what various implementations of WebHooks in apps such as GitHub, Slack etc. provide because thankfully Giuliano Iacobelli already wrote such an article. My interest here is to apply this knowledge to a microservice system we are building and try to anticipate pros and cons of going with WebHooks.

What it would take

First thing that comes to mind is that in order to support WebHooks, we would need to write a new WebHook service. Its role would be to accept registrations, and store URL and event type mappings for subsequent invocation. Right there, my first thought is about the difference between external and internal clients. External clients would most likely use the UI to register a URL of their integration. This is how you register your script in GitHub so that it runs on every commit, for example.

However, with internal clients we would have a funny problem: every time I restart a microservice instance, I would need to register somewhere in startup. That would make a POST endpoint a nonstarter, because I don’t want to keep creating new registrations. Instead, a PUT with a client ID would work better, where an existing registration for the same ID would just be updated if already there.

Other than that, the service would offer a POST for a new message into the provided event type that would be delivered to all registered URLs for that type. Obviously it would need to guard against 404s, 502s and URLs that take too long to return response, giving up on them after a set timeout.

The best of both worlds

The set timeout brings back the topic of the quality of service, implying that WebHooks are great for external integration but not that great for reliable glue of a microservice system. Why don’t we marry the two then? We could continue to use message broker for reliable delivery of internal messages, and hook it up to a WebHook service that would notify external integrations without the need to support our particular protocol, or get too much access into the sensitive innards. Hooking up a WebHook service to a message broker would have the added benefit of buffering the service itself so that it can be restarted and updated without interruption and missed events.


In the diagram above, our microservice system has the normal architecture with a common routing proxy providing a single domain entry into the microservices. The microservices use normal message broker clients to publish to topics. A subset of these topics deemed suitable for external integrations is also listened to by the WebHook service, and for each of those messages it reaches into the stored list of registrations and calls HTTP POST on the registered URLs. If the WebHook service crashes, a reputable message broker will maintain a buffer of messages to re-deliver them upon restart. For performance reasons, WebHook service can choose to keep a subset of registrations in the in-memory cache depending on how frequently they are used.


Obviously registering a URL with an HTTP PUT is much easier to implement, and providing a single POST endpoint to handle the event lowers the barrier of entry for external integrations. In fact, hooking up code to react to a single POST could very well be done using serverless architecture.

Are we losing something in the process? Inserting another service into the flow will add a bit of a delay but external notifications are normally for events that are not happening many times a second, so the tiny delay is more than acceptable tradeoff. In addition, if the client providing WebHook URL is itself load-balanced, this delivery will be hardcoded to anycast (the event notification will only hit one of the instances in the cluster).

Finally, this creates two classes of clients – ‘inner circle’ and external, segregated clients. Inner circle is hooked up directly to the message broker, while the external clients go through the service. In addition to this being an acceptable price to pay for easier integration, it is useful to be able to only expose a subset of events externally – some highly sensitive internal events may only be available to ‘trusted’ clients subscribing to message broker topics and having internal credentials.

Since the WebHook service will normally not keep retrying to deliver an event to an unresponsive URL, it is possible to miss an event. If this is a problem, external system would need to fashion a ‘belt and suspenders’ fortification, where event driven approach is augmented with a periodic REST API call to ‘compare notes’ and ensure the baseline it is working against is up to date.

© Dejan Glozic, 2017

Self-Contained Systems – Microservices for Dummies

Harran beehive houses, Wikimedia Commons
Harran beehive houses, Wikimedia Commons

I love the smell of the new year in the morning. As in the tweet above, there is something hopeful in starting a new blog by first updating the copyright notice at the bottom.

Nevertheless, what is currently occupying my mind is not as much how 2016 started, but how 2015 ended. As luck would have it, within weeks I had a chance to present about our production experience with micro services to two enterprises –  a mutual fund and a bank. Both were curious about them and simultanously unsure as to how they would apply in their unique situation.

In such discussions, the topic of Netflix inevitably comes up, and I am not sure this is a good thing. Sure, I enjoyed watching The Social Network like the most of us, but I am not sure it taught me much about how to become Mark Zuckerberg. Certain experiences, approaches and stories are so intensely singular that their utility as a ‘how to’ manual is quite poor.

In the case of Netflix, I have noticed two characteristics that are not very useful in most scenarios where micro services are considered:

  1. Very few outfits need to scale up to a third of all Internet traffic
  2. Being the micro service pioneers, Netflix engineers wrote a lot of custom code that is impractical in most situations

Maybe we don’t need 1000 microservices?

The consequence of the fact that you don’t need to prepare to handle a third of all Internet is that the overhead equation skews towards having fewer large micro services, rather than many small ones. In fact, it is surprising what transpires when discussions go a bit deeper into the ‘why’ direction.

As you probably know, I am on the record claiming that micro services are more about future-proofing, solving organizational problems of large teams and DevOps than any particular technology. It has become apparent to us as we talk to companies that the problem of two speed IT is more acute and pressing than replicating Netflix’s improbable feat. In the two-speed systems, companies can preserve investment and control through exposing the current system of record through APIs, while building up a cloud-based micro service system that consumes those APIs and serves Web and mobile experiences at the required speed and agility. You don’t need thousands of micro services for this.

In fact, more proof that the pragmatic pendulum has swung towards more reasonable architectures  can be found in the coining of a new phrase – Self Contained Systems (SCS). It is a neat workaround for the cognitive issues that may come from the term ‘micro service’. The term ‘system’ implies something larger, so even the illustrations of SCSs imply no more than a dozen or so. All the good properties of micro services are preserved (polyglot persistence, ability of teams to develop and deploy them independently, stack independence), but there is no expectation to deploy them in the hundreds and thousands. Sure, a self-contained system can in turn consist of several micro services, but at that point it becomes implementation detail.

It is probably best for companies dipping their toes into the micro service world to think about self-contained systems instead, lest they are taken down the Netflix path which will most likely be wrong for them.

I make my own underwear

The point of custom code from above reminded me of a story from the days when I was still climbing the audiophile ladder and cared about hi fi companies and stories about them. In this particular story from 2011, a parent company IAG that owns illustrious British names such as Quad, Mission and Wharfedale, describes its process like so:

One of the immediately notable things about IAG’s operation is the extent of what they make themselves: from new parts, to the tools to make those parts, through to all their own speaker drivers: the vast bulk of what goes into IAG products is made right there in the Shenzhen factory. They even manufacture their own wire.

What Hi Fi: Behind the scenes at IAG

The advice ‘start by making your own wire’ would make sense for very few companies, and the same applies to most enterprises trying to replicate Netflix’s approach. This comes into sharp focus when you start discussing concepts such as service discovery. Consider the following diagram:


The URL of the micro service system is composed based on spaces (dev, QA, prod) and regions. It can be easily constructed or scripted. The routing proxy partitions the path namespace, and each path acts as API and is driving a load balancer which in turn handles any number of micro service instances.

I am showing you this because we are running this successfully in production right now. If you want to, say, hit the development version of the micro service system running in US1 data centre, you would have something like https://foo-dev.us1.acme.com. A script with a couple of substituted variables is all you need to hit the system you want. As for the load balancer, it comes for free in the IBM’s Cloud Foundry-based PaaS (Bluemix).

If you have a Netflix-type system, you need service discovery just so that you can connect all your micro services, all flailing around at the unguessable IPs and port numbers. And since you need to build everything yourself, a simple thing such as load balancing that comes out of the box in all PaaSes and a number of IaaSes is something you need to provide.

Netflix story is unique for many reasons, and having to build everything yourself is one of those characteristics not necessary in 2016. Cloud today is all about what you can outsource to a PaaS or IaaS vs what is uniquely your value add. Building load balancers is doable but a rarely justified practice today.

For Dummies?

Yes, I know, forgive me for the click bait – SEO and all that. But by now you are well versed with the tongue-in-cheekness of the ‘For Dummies’ franchise. As people finding value in them are hardly dummies, so are people wisely choosing Self-Contained Systems instead of going down the path of the thousand micro services. Running a half a dozen to a dozen independently deployed, agile self-contained systems hooked up to your legacy systems may be the best choice for you right now. You can always add more, but don’t feel pressured to do so.

© Dejan Glozic, 2016

Dust.js as a React Delivery Vehicle


Even people in love with Single Page Apps and pooh-poohing server side rendering know that SPAs cannot just materialize in the browser. Something has to deliver them there. Until recently, AngularJS was the most popular client side JS framework, and I have seen all kinds of ADVs (Angular Delivery Vehicles) – from Node.js (N is for Node.js in the MEAN stack), to wonderfully ironic JSP files serving Angular. Particularly exuberant developers go all the way to using static HTML to launch their apps into orbit, extolling the virtues of CDNs.

Of course, I would like to see their faces the first time they realize the need to compute something dynamically in those static files. But that is beside the point. The important takeaway is that AngularJS has a very nice property of being embeddable. You don’t need to surrender your entire page to Angular – you can sequester it to a DIV (in fact, you can have multiple Angular apps running in the same page). This is a very nice feature, but also a necessary one – again, AngularJS is a pure client side framework.

With great power…

React changes this equation because it can be rendered on the server. Similarly to AngularJS, React root component can be mounted to any node inside your page, but unlike Angular, this page can also be rendered on the server by React.

This opens the door for a whole new class of isomorphic or universal apps, and I have written about it already. What you need to decide is whether you want to render the entire page, or a subset of it. If you choose the latter, then the subsequent question becomes – how do you start the rendering process until React takes over?

My first inclination was to go full React. Using the awesome react-engine module, it is easy to configure React as the view engine in the Express framework, and render the entire page. However, we soon hit some snags:

  1. As we render our UIs using micro services that use UI composition to glue the pages together, we hit a problem of React being grumpy about having to render HTML snippet arriving from outside of its control – something much easier with a templating library such as Dust.js.
  2. JSX turned out to be fairly quirky and finicky when rendering HTML HEAD element, as well as trying to inline JavaScript in tags. In fact, the latter became so error prone that we completely gave up on it, electing to put all our script in files. I didn’t like this particular restriction, and this remains an area where I am sour on JSX and the fact it most decidedly isn’t HTML.

Of course the problems I listed above did not show up in the small example I published in the initial article. They reared their ugly head once we started getting serious. In my original example, the header was a React component. This works great if you control the entire app, but the whole deal of UI composition is to integrate with apps not necessarily written using React, and you can only do that using the least common denominator (HTML, CSS and vanilla JS).

Remind me again about UI composition

In a nutshell, UI composition is the approach where common areas on the page are served as HTML snippets from a REST API. The API service can also serve CSS and JavaScript files that accompany the snippet (if you don’t serve them from a CDN). The idea is that a dedicated microservice can be providing these common areas this way, allowing other microservices to pull the content and inline it in their pages regardless of their stack.

UI composition inverts the flow you would normally use with iframes. Instead of rendering the common areas, then placing an iframe for the content and loading the content from an external URL, we load the common area as HTML and inline it into our page. In the olden days this approach was often accomplished using ‘edge side includes’ or ESIs. This approach has many benefits, including no need for the dreaded iframes, full control over the entire page, and the ability to integrate microservices implemented using different stacks. For example, the teams in my current project use:

  1. Node.js microservices using React for isomorphic rendering
  2. Node.js microservices using Dust.js and jQuery
  3. Java microservices using AngularJS

All of these microservices render the exact same header even though they use different stacks and libraries. Powerful stuff.

OK, so React?

The problem here with React is that when we use it to render the entire page server-side, it starts to squirm in discomfort. Inlining HTML is a problem for React because, while it can be used on the server, it was designed to shine on the client. Inlining raw HTML presumably obtained as a user input into DOM is a major security exposure without sanitization, and React will tell you so in no uncertain terms. Here is the line that inlines the shared header taken straight out of our production code:

<div dangerouslySetInnerHTML={{__html: decodeURIComponent(this.props.header)}} />

This is React telling us very clearly: “I really, really, really don’t like what you are asking me to do”. And this is even before we bring in react-engine. React engine is a PayPal module that enables isomorphism when combined with Node.js/express and react-router. We can render on the server, then pack the properties as part of the HTML response, hydrate the React components on the client and continue where we left off.

Only we have a little problem: notice that in the snippet above we have inlined the header by passing it down to the React component as a prop. What this means is that this prop (‘header’) will be sent to the client alongside other properties. The only problem is that this property contains HTML snippet for the entire header, and because it can really mess up react-engine, it is also URLencoded, making it even bulkier.

This is an unhappy situation: first we inline the header HTML (which is fine), then we send that same inlined HTML, this time encoded, as a React prop to the client. This unnecessarily bloats the generated HTML.


This is what we are going to do to solve this problem: we are going to call back our trusty Dust.js sitting sad on the sidelines ever since we got smitten with React. We can press it into service to do what it does best – outline the page, prep it up to the point where React can take over.

It’s a good thing that Express framework will happily handle more than one view engine. Of course, only one of them can be registered as default, but this just means that we will need to spell out the extension of dust files (because React is the default). Big deal.

var path = require('path')
, express = require('express')
, renderer = require('react-engine')
, dust = require('dustjs-linkedin')
, helpers = require('dustjs-helpers')
, cons = require('consolidate');


// create the view engine with `react-engine`
var engine = renderer.server.create({
  routes: require(path.normalize(__dirname + '/public/routes.jsx')), 
  docType: ""

// set the engines
app.engine('.jsx', engine);
app.engine('.dust', cons.dust);

// set the view directory
app.set('views', __dirname + '/public/views');

// set jsx as the view engine
app.set('view engine', 'jsx');

// finally, set the custom view
app.set('view', renderer.expressView);

Once we have both engines set up, we can arrange our delivery vehicle like this. We will first set up a reusable layout template using Dust.js that will deliver the outline of each page:

<!DOCTYPE html>
   <meta charset='utf-8'>
   <meta http-equiv="X-UA-Compatible" content="IE=edge">
   <meta name="viewport" content="width=device-width, initial-scale=1" >
   <link rel="stylesheet" href="/css/styles.css">
   <div class="main-content">

Notice how inlining of the header now happens in Dust.js, relieving React from doing it. We can now use this template to render our page like this:

<div id="react-mount-node">{spa|s}</div>
<script src="/bundle.js"></script>

We have created a DIV in the template above where we are mounting React, and we will inline the React server-side content using the ‘spa’ variable.

Our Express controller that will handle both Dust.js and React can look something like this:

var request = require("request");

module.exports.get = function(req, res) {
  var settings = {
    title: 'SPA - Demo',
    name: 'React SPA',
    selection: 'header-spa'

  var headerUrl = "http://"+req.headers.host+"/header?selection=header-spa";

  request.get(headerUrl, function (err, response, body) {
    if (err)
      settings.header = body;
    res.render(req.url, { name: settings.name }, function(err, html) {
      if (err) {
        settings.spa = err.message;
        settings.spa = html;
      res.render("spa.dust", settings); 

The code above is what I call ‘React Delivery Vehicle’. It has three steps:

  1. First we fetch the header from the URL that is providing us with the header HTML snippet. We capture it into a variable ‘header’. In production, we will heavily cache this step.
  2. Then we render the React root component as usual. This will employ react-engine and react-router to render all the views necessary for the provided request URL. However, we don’t send the rendering to the response. Instead, we capture it in the variable ‘spa’.
  3. Finally, we invoke Dust.js view engine to render the full page, passing in the ‘settings’ object. This object will contain both the header and the content rendered by React. Dust will simply inline both while rendering the page outline. The result will be sent directly to the Express response.


The solution described above plays to the strengths of both Dust.js as a server side template engine and React as a component library. Dust.js is great at rendering HTML outline the way you would expect, with no need to worry about JSX quirks around HEAD meta tags, or JavaScript inlining. React takes over to render isomorphic components into the mount node. This means we don’t need to send any data that is not needed on the client. This fixes the HTML bloat problem I mentioned before.

As for the negatives, setting up two rendering engines on the server has a slight overhead, and switching mentally from Dust.js to JSX adds context switching tax. Luckily, you can set up reusable Dust.js templates and not really worry about them too much – most of the action will be in JSX anyway.

We like this approach and are currently switching to it across the board. If you have alternative ideas or comments, drop me a line. Meanwhile, the source code for the entire example is available on GitHub as usual, and the sample app employing this mechanism runs on Bluemix.

© Dejan Glozic, 2015

Don’t Take Micro-Services Off-Road

Fred Bauder, 2009, Wikimedia Commons
Fred Bauder, 2009, Wikimedia Commons

I own an Acura TL 2006. It’s a great car. Every day I derive great pleasure driving it to work. It has a tight sporty suspension, precise steering, comfortable leather seats and an awesome audio system.

At the same time, I know better than to take it off-road. Its high performance tires are optimized for asphalt traction and low rolling resistance, not gravel or soil. It does not have enough clearance for rocks, or 4×4 drive required for rough terrain. If I did take it off-road, I could erroneously conclude that it is an awful car, which I know not to be true. I would have simply used it for something it was never designed to do.

I used this example to explain the concern I have seeing the evolution of the industry’s relationship with the micro-service architecture. It was just a matter of time people until people started taking their micro-service Acuras off-road and then writing how they are awful cars.

Original success stories

Architectures and approaches normally turn into trends because enough use cases exist to corroborate their genuine usefulness when solving a particular problem or a class of problems. Otherwise, only architecture astronauts would care. In the case of micro-services before they were trendy, enough companies built monoliths beyond their manageability. They had a real problem on their hands – a large application that fundamentally clashed with the modern ways of scaling, managing and evolving large systems in the cloud. Through some trial and error, they reinvented their properties as a loose collections of micro-services with independent scalability, life cycle and data concerns. Netfix, Groupon, Paypal, SoundCloud are just a small sample of companies running micro-services in production with success.

It is important to remember this because the trendiness of micro-services threatens to compel developers to try them out in contexts where they are not meant to be used, resulting in the projects overturned in the mud. This is bad news for all of us who derive genuine benefits from such an architecture.

Things to avoid

It is therefore good to try to arrive at a useful list of use cases where micro-services are not a good choice. It will keep us more honest, keep the micro-service hype at bay and prevent some failures that would sour people to an otherwise sound technical approach:

  1. Don’t start with micro-services – this one is a no-brainer. Micro-services attempt to solve problems of scale. When you start, your app is tiny. Even if it is not, it is just you or maybe you and couple more developers. You know it intimately and can rewrite it over a weekend. The app is small enough that you can easily reason about it. There is a reason why we use the word ‘monolith’ – it implies a rock big enough that it can kill you if it falls on you. When you start, your app is more like a pebble. It takes certain amount of time and effort by a growing number of developers to even approach monolith (and therefore micro-service) territory.
  2. Don’t even think about micro-services without DevOps – micro-services cause an explosion of moving parts. It is insane to attempt it without serious deployment and monitoring automation. You should be able to push a button and get your app deployed. In fact, you should not even do anything – committing code should get your app deployed through the commit hooks that trigger the delivery pipelines (at least in development – you still need some manual checks and balances for deploying into production).
  3. Try not to manage your own infrastructure – micro-services often introduce multiple databases, message brokers, data caches and similar services that all need to be maintained, clustered and kept in top shape. It really helps if your first attempt at micro-services is free from such concerns. A PaaS such as Cloud Foundry or Heroku will allow you to be functional faster and with less headache than with an IaaS, providing that your micro-services are PaaS-friendly.
  4. Don’t create too many micro-services – each new micro-service adds overhead. Cumulative overhead may outstrip the benefits of the architecture if you go crazy. It is better to err on the side of larger services and only split when they end up containing parts with conflicting demands for scaling, life cycle and/or data. Making them too small will simply transfer complexity away from the micro-services and into the service integration task.
  5. Don’t share micro-services between systems – I listed this final point here for completeness, but it is so important that it requires to be broken into its own section.

On micro-service sharing

I have seen many a fiery debate about the difference between micro-services and SOA. There are many similarities (it is hard to argue that micro-service architecture, or MSA is revisiting SOA principles). More recently I have formed a fairly strong opinion that a key differentiation between MSA and SOA is that of ambition.

When you go back and read about the lofty goals of SOA proponents, it is easy to notice that the aim was much higher. MSA success stories didn’t attempt to reinvent the world around catalogs of reusable services, systems that are discovering those services through registries, etc. At the beginning of every MSA success story is a team that grew their simple application too fast without refactoring along the way and hit the maintainability wall.

If you carefully read ‘monolith to micro-services’ blog posts, you will notice that the end result is the same thing. Groupon team has not created a ‘catalog of social coupon services to be assembled into coupon applications’ – they rebuilt Groupon Web site. They broke the monolith into small pieces and rebuilt it again. As far as their end users are concerned, the monolith is still there – the site was rebuilt in mid-air.

Since I think that micro-services are pragmatic and sane revisiting of SOA, it is apt to assume that creating reusable micro-services is low on the list of priorities. Yes, a micro-service needs to be individually deployable and be flexible enough that it can be bound to other services dynamically (minimally through some kind of a configuration on startup). You need to be able to deploy each service to multiple logical ‘spaces’ (DEV, QA, STAGING, PROD). But each logical micro-service instance is part of a single distributed monolith, re-imagined in a cloud-friendly way.

From a monolith to a – distributed monolith?

Where am I going with all this? I am a bit concerned that the industry noise will ruin micro-services by taking them outside their comfort zone. Too many people are taking them to the areas where they shouldn’t, and I don’t want the inevitable backlash to overshoot. Micro-services are a solution for the Big Ball of Mud architecture, but the alternative micro-service system is still a big ball. This ball made up of many small balls, is cleaner and easier to manage, deploy, scale and evolve, and can be inflated bigger than the old ball without exploding, but it is fundamentally the same thing.

Any attempts at nano-services, trying to deploy micro-services manually, using them because they are trendy without real need, or re-using them between multiple systems will result in a disappointment we don’t really need at the moment.

Are micro-services SOA? No, and please let’s keep it that way.

© Dejan Glozic, 2015

Micro-Services for Dysfunctional Teams

Jan Steen, Argument over a Card Game, Wikimedia Commons.
Jan Steen, Argument over a Card Game, Wikimedia Commons.

Update: I have received a ton of feedback on this post, and some of the well meaning criticism is concerned with the term ‘dysfunctional’, considering it a bit ‘judgy’ from somebody that is supposed to help these same teams. Apart from yielding a catchy title, Hacker News reader was spot on when he declared my use of the word as ‘term of endearment’ more than anything else. Not unlike a smart person calling herself ‘stupid’ or a workaholic calling himself ‘lazy’ for sleeping in one morning. In the proceeding article, ‘dysfunctional’ are most teams made from real people, and the opposite is the ideal we are all striving towards, always just beyond our reach.

I am back from Las Vegas and IBM Interconnnect 2015, and fully recovered from the onslaught on the senses. Man, does that city ever shut up. Time to return to regular programming. Today topic is my surprising realization of the main backers of micro-services in large enterprises. As they say in click baits, it’s not who you think.

For the last year or so I was a vocal evangelist for both Node.js and micro-services in IBM and elsewhere (using former as the platform of choice for the latter). Or as a dear former colleague of mine kindly put ‘evangelist, coach, and referee’. That role put me in contact with a number of teams finding themselves on the verge of the now familiar ‘from monolith to micro-services’ journey.

What I find over and over again is that micro-services appeal to leadership more than the developers. This is a somewhat confusing revelation considering micro-services are considered an architectural approach, and project managers are not supposed to fall in love with an architecture (at best, they are weary of it because ‘architecture’ is typically a code word for more boxes and increased cost and time to delivery). And yet.

Micro-services are not (only) about technology

When I am asked to do an elevator pitch about advantages of micro-services, this list typically comes to mind:

  1. Individually deployable pieces of running software each responsible for a small number of tasks
  2. Each micro-service can be implemented using a different stack
  3. Horizontal scalability decisions can be made at a micro-service level

When you analyze this list, neither point is really making your system better from a purely technical point of view. In fact, a monolithic system is definitely easier to work with when you are alone or have a small, ‘war room’ kind of a team. When a monolith is relatively small, deploying it is not a big deal, and cookie cutter scaling does not seem too wasteful (assuming the monolith does not depend on in-memory state that is hard to distribute).

Each of the points actually promises to fix long-standing systemic problems of very large teams responsible for equally large monoliths that are at the bursting point.

Breaking the logjam

The promise of individually deployable pieces seems to always light a fire in project managers’ eyes. I don’t blame them – most large monolithic systems are a bitch to deploy. If they use compiled languages such as Java, the build times are nontrivial. With every new line of code, deploy times keep growing, and it increasingly feels that there must be a better way to do this.

Monoliths are the first thing we build in the cloud because that’s what we used to do for on-premise deployment. Turns out, the price we pay to get the monolith built and deployed is too steep given the high bar set by ‘born in the cloud’ unicorns. Therefore, breaking up the monolith into smaller, more manageable parts seems as natural as mitosis is for single-cell organisms.

Beyond solving the sheer size problem, micro-services promise to solve the ‘different rate of change’ problem. As I have blogged recently, a typical system today have elements of Web sites, as well as Web apps rolled into one. Elements acting as a site have a tendency of wanting to change more often than the app part. Site sections tend to have a lot of marketing material that is time sensitive, while app sections are trickier and need to be changed more carefully (and may require data migration every once in a while). I often joke that these types of systems feel like a donkey and a horse strapped to the same harness – they just cannot find the right rhythm. One of them is either too fast or too slow. In fact, a lot of systems feel like we have a donkey, a horse, a cow and a goat all trying to pull the carriage together – not a pretty picture (funny though).

In these kinds of situations, micro-services offer an organizational, or governance solution, not a technical one. They often result in more moving parts and more complexity, but the relief of letting the metaphorical donkey and the horse run at their own pace is too hard to resist, overhead be damned. The alternative is having a complex process executed with utmost precision, and so far I know only one team (Facebook) that can pull it off with any regularity. Micro-services offer a more realistic alternative for the rest of us (the ‘dysfunctional teams’ from the title, which is really most of the teams).

No more intergalactic technology consensus

Anybody who tried to get a number of teams in a large organization to agree on a common technology can sympathize with this. We are all human, and tend to have passionate and strong opinions on technologies we like and hate. Put enough of these strong opinions together, and they tend to cancel each other out, leaving no common ground. This is bad news for the poor architect that needs to pick an approach for a large project. I once heard a saying learned through the hard won experience: “Even if we agree on a common technology or approach on Monday, we will slide back into disagreement by Thursday”.

In this context, micro-services offer not as much of a solution as “let’s just agree to disagree”. The focus is moved from common technology to common interfaces, integration techniques, protocols for passing data around. There is enough understanding about the advantages of stable protocols and APIs, so this part is much easier to close with a solid and lasting agreement.

A word of caution: I personally don’t think that, just because we could write each micro-service in a different technology, we should. There is much to be said about code reuse, and micro-services quickly minted by Yeomen generators tend to yield more productive teams than ‘let’s write the same authentication library in 6 different languages’. We found that by limiting our choices to Node.js and Java, we can move faster.

Nevertheless, it is just a matter of time until a new platform is touted as revolutionary or trending. When the time comes, we can risk one micro-service without betting the farm on it. Just in case Go does not turn out to be the giant killer it is touted to be, for example.

Cookie cutter is no fun with giant cookies

Finally, making clustering decisions at a micro-service level is more of a bean counter than architectural issue. Just clustering a small monolith is very simple – put a load-balancer in front of the monolith copies and you are done (again, assuming the monolith nodes do not critically depend on in-memory data that need to be kept in sync).

As the monolith grows, it needs more CPU and RAM to operate properly, times number of nodes. As it normally happens, ‘heat points’ are not distributed evenly across the monolith – there are sections that are working very hard, and sections that are barely moving. Cookie-cutter clustering becomes more and more expensive, with an increased percentage of unused and therefore wasted capacity.

Micro-services promise to be more efficient at using resources because we can make individual clustering decisions. We can beef up busy nodes and run a relatively small number of instances of rarely used micro-services. This is a purely economic (and ecological) issue – if we didn’t care about waste, we could just continue to run multiple monolith instances.

Of course, this is all assuming our monolith is clusterable to begin with. If it is not, micro-services become a way out for a system that has hit a limit of its ability to scale.

Keep the excitement to yourself

Next time you are in position to pitch micro-services to a worried project manager or product owner, don’t forget that technology is really not what you are selling – you are selling a solution for process, governance, cost of operation and scalability issues, not a technology. You are selling the ability to fix a typo on a prominent page of your large system within minutes without touching the rest of the system. You are promising the ability to maneuver an oil tanker as if it was a canoe, in a world full of oil tankers.

You can still be in love with the technology, just make it our little secret. I’ll never tell.

© Dejan Glozic, 2015