This will be my final post in this blog for a while.
All posts were moved to blog.caelumobjects.com and I will keep posting over there.
REST was a research result that left us with an open question, as its researcher suggested: it beautifully solves a lot of problems, but how to apply it on contemporary concerns that enterprise have?
The following video shows an example on how to start from a typical non restful architecture to adopting REST constraints and creating a buying process in any REST server.
So what is the power behing applied REST?
“Rest Applied” as I have exemplified, solves our contemporary concerns, filling the gap between Roy’s description and application’s usage, opening up a new world of possibilities.
The same way that REST ideas, although they were not called REST at that time, allowed web crawling to be an amazing client, “REST applied”, as described, can change the way our applications communicate with servers.
Why did we miss it? Because Roy’s description goes for with crawling examples, which benefit directly from content type negotiation. i.e. different languages, same resource and google post ranking it:
“In fact, the application details are hidden from the server by the generic connector interface, and thus a user agent could equally be an automated robot performing information retrieval for an indexing service, a personal agent looking for data that matches certain criteria, or a maintenance spider busy patrolling the information for broken references or modified content .”
But, “Not surprisingly, this exactly matches the user interface of a hypermedia browser. “… the client adapts itself to its current representation – limited to the client’s cleverness.
Restfulie gives better HTTP support to http libraries and provides a REST frameworks while Mikyung allows you to create your REST clients. With both of them you are ready to apply REST to enterprise problems.
Mikyung stands for “beauty capital” in Korean, in a attempt to reproduce what a beautiful rest client could look like when following REST constraints.
Not yet REST
How do we achieve REST? Leonard Richardson’s model was widely commented and Martin Fowler posted on “Rest in Practice” (a book I recommend reading). But what is left out from REST in Richardson’s model and why?
According to his model, level 3 adds hypermedia support, leveraging a system through the use of linked data – a requirement for a REST architecture. But HATEOAS alone does not imply in REST, as Roy stated back in 2008.
Remember how method invocation on distributed objects allowed you to navigate through objects and their states? The following sample exemplifies such situation:
orders = RemoteSystem.locate().orders();
receipt = order.payment(payment_information);
But what if the above code was an EJB invocation? If navigating through relations is REST, implementing EJB’s protocol through HTTP would also be REST because linked data is also present in EJB’s code – although lacking an uniform interface.
While Richardson’s model get close to REST on the server side, Rest in Practice goes all way to a REST example, describing the importance of semantics and media type importance. The rest of the post will explain what was left out of this “Rest services” model and why, proposing a model that encompasses REST, not REST under http; while the next post, with a video, describes how to create a REST system.
What is missing?
Did the previous code inspect the relations and state transitions and adapted accordingly?
It did not choose a state transition, it contains a fixed set of instructions to be followed, no matter which responses are given by your server. If the API in use is http and the server returns with a “Server too busy” response, a REST client would try again 10 minutes later, but what does the above code do? It fails.
We are missing the step where REST clients adapt themselves to the resource state. Interaction results are not expected as we used to in other architectures. REST client behavior was not modelled on Richardson model because the model only thought about server side behavior.
This is the reason why there should be no such a thing as “rest web services” or “rest services”. In order to benefit from a REST architecture, both client and server should stick to REST constraints.
Richardson’s server + http model
Semantic meaningful relations are understood by the client, and because of that we need a model which describes how to create a REST system, not a REST server.
An important point to note is that this model is pretty good to show a REST server maturity over HTTP, but limiting REST analysis both to server and http.
A REST architecture maturity model
For all those reasons, I propose a REST maturity model which is protocol independent and covers both consumer and provider aspects of a REST system:
Trying to achieve REST, the first step is to determine and use an uniform interface: a default set of actions that can be taken for each well defined resource. For instance, Richardson’s assumes HTTP and its verbs to define a uniform interface for a REST over HTTP architecture.
The second step is the use of linked data to allow a client navigate through a resource’s state and relations in a uniform way. In Richardson’s model, this is the usage of hypermedia as connectedness.
The third step is to add semantic value to those links. Relations defined as “related” might have a significant value for some protocols, but less value for others, “payment” might make sense for some resources, but not for others. The creation and adoption of meaningful media types allows but do not imply in client code being written in a adaptable way.
The fourth step is to create clients in a way that decisions are based only in a resource representation relations, plus its media type understanding.
All of the above steps allow servers to evolve independently of a client’s behavior.
The last step is implied client evolution. Code on demand teach clients how to behave in specific situations that were not foreseen, i.e. a new media type definition.
Note that no level mentions an specific protocol as HTTP because REST is protocol independent.
The following post will describe one example on how to create a REST system using the above maturity model as a guide.
For those who are going to RailsConf this year and want to create consumer and servicing systems with lesser coupling, do not miss Fabio’s talk.
Everything started when we decided to stop pretending…
The most frequently asked question about REST in any presentation: why hypermedia is so important to our machine to machine software?
Is not early binding through fixed URI’s and using http verbs, headers and response codes better than what we have been doing earlier?
An approach that makes real use of all http verbs, http headers and response codes already presents a set of benefits. But there is not only the Accept header, not only 404, 400, 200 and 201 response codes: real use means not forgetting important verbs as PATCH and OPTIONS and supporting conditional requests. Not implementing features as automatic 304 (as a conditional requests) parsing means not using http headers and response codes as they can be used, but just providing this information to your system.
But if such approach already provides so many benefits, why would someone require a machine-to-machine software to use hypermedia? Is not it good enough to write code without it?
The power of hypermedia is related to software evolution, and if you think about how your system works right now (its expected set of resources and allowed verbs), hypermedia content might not help. But as soon as it evolves and creates a new set of resources, building unforeseen relations between them and their states (thus allowed verbs), that early binding becomes a burden to be felt when requiring all your clients to update their code.
Google and web search engines are a powerful system that makes use of the web. They deal with URIs, http headers and result codes.
If google’s bot was a statically coded bot that was uncapable of handling hypermedia content, it would require a initial – coding time or hand-uploaded – set of URIs coded that tells where are the pages on the web so it retrieves and parses it. If any of those resources creates a new relationship to other ones (and so on), Google’s early binding, static URIs bot would never find out.
This bot that only works with one system, one specific domain application protocol, one static site. Google would
not be able to spider any other website but that original one, making it reasonably useless. Hypermedia is vital to any crawling or discovery related systems.
Creating consumer clients (such as google’s bot) with early binding to relations and transitions do not allow system evolution to occur in the same way that late binding does, and some of the most amazing machine-to-machine systems on the web up to date are based in its dynamic nature, parsing content through hyperlinks and its semantic meaning.
Although we have chosen to show Google and web search engines as examples, any other web systems that communicate with a set of unknown systems (“servers”) can benefit from hypermedia in the same way.
Your servers can only evolve their resources, relations and states without requiring client-rewrite if your code allows service-crawling.
REST systems are based in this premise, crawling your resources and being able to access its well understood transitions through links.
While important systems have noticed the semantic value and power of links to their businesses, most frameworks have not yet helped users accomplishing late binding following the above mentioned principles.
It’s common to find developers struggling with their clients browser’s cache and proxies in order to get their application running as expected: some of them actually view cache options as a bad thing.
Actually http caches presents a few advantages, being the two most important amongst them all the ability to serve more clients at the same time without buying more expensive hardware (or horizontally scattering your system) and avoiding excessive bandwidth consumption where it can be saved or it is expensive.
A well known tutorial on how web caches work
was written by Mark Nottingham. Mark has also been involved with the Link header specification and developed Redbot, a clever machine that inspects your pages to avoid cache related issues you might be facing or improve your application scalability: and its everything connected to rest architectures.
Linked data is the basis for HATEOAS systems while http cache supports higher scalability using such architecture.
Imagine a theoretical scenario where a huge content provider application contains hundreds of thousands of articles that are frequently accessed in your country. Such application might have a few pages that change often, while others do not.
By adding a simple “Cache-control” header to your page, all existing cache layers between you and your client monitor will hold the resource representation in memory for one hour:
In Restfulie (Rails) it can be achieved by providing some cache information to your resource:
class OrdersController < ApplicationController
Now there can be three cache systems leveraging from such header example.
The browser’s cache will use the previously retrieved representation while it does not expires, and might use it even if its expired and you did not provide the must-revalidate option. This will save you bandwidth and server cpu consumption.
A cache proxy situated within the users network, or anywhere between the server and the client machine, will serve the previously retrieved representation, saving you bandwidth outside your network and server cpu consumption.
A reverse proxy can cache the representation within the server’s network and save cpu consumption. This approach has been widely adopted in order to share cached representations amongst different consuming applications/users.
All these three savings are actually reverted in a easier to scale application, you did not need any paid middleware, any fancy stack or load balancers, although they might help: it saves you complexity, time and money.
There is much more you can do with cache headers (Last-Modified, ETag and so on) and REST libraries should make it easy to use them, appart from supporting local caches.
Finally, in syndication based systems, or in any other heavy machine-to-machine communication based one, a local cache might not be able to handle the large volume of caching hits. In such systems, it is a common approach to use distributable cache systems, and Restfulie allows you to use your own cache provider.
For example, a distributed cache like Memcached could be used by simply implementing three methods:
def put(url, request, response)
# save it into memcached
def get(url, request)
# retrieves from cache, if available
# optional implementation
# clears the cache
Restfulie.cache_provider = MemcachedCache.new
Most used http clients implement low level features such as handling response and requests on your own, processing only the basic request headers.
The difference between http client libraries and rest client libraries is that the second should implement further http api processing, while the first allow access to the previously mentioned low level api.
And both because cache is part of the HTTP api and one of the key issues that made the web scale as we know it, Restfulie required such support out of the box (along with etag, last-modified and 304).
Not only one write less code to process the responses, but one leverages his client and server applications.
Note: I am moving my posts to our company’s blog, the next post will be just an announcement. Comments can be made either here or there.