With advancements in cloud technology, managed services are not only an option, they are becoming the standard. A managed services means little or no maintenance for you. Most of these services scale dynamically as demand increases and there are few fixed fees. Instead, you pay for usage.
This is a three part article which will walk you through how to create a server-less RESTful service starting with the architecture and methodology, then walking through how to create the business layer to apply rules and get data from the database, and finally, the connection through the web to tie it all together.
For this article, I will be referencing the Amazon AWS platform but the architecture and methodology is applicable to any cloud network including Azure. For a cross reference between the names between the two technologies, you can reference this page: https://azure.microsoft.com/en-us/campaigns/azure-vs-aws/mapping/
Note: Since this document is meant to be agnostic to the cloud technology, it will not go into the details on how to setup or configure your Amazon AWS applications. There are quite a few blogs describing this process. For information about setting up Lamdba, go to the AWS Lambda site located here: https://aws.amazon.com/lambda. For information about setting up Java to work with Amazon, look at the Java Development Center. The Java Development Center is located here: https://aws.amazon.com/java/
The key principles of REST involve separating your API into logical resources. These resources are manipulated using HTTP requests where the method (GET, POST, PUT, PATCH, DELETE) has specific meaning.
When generating your resource, it is important to remember the method is your verb so the resource should be a noun that makes sense from the perspective of the API consumer. Although your internal models may map neatly to resources, it isn’t necessarily a one-to-one mapping. The key here is to not leak irrelevant implementation details out to your API.
Once you have your resources defined, you need to identify what actions apply to them and how those would map to your API. RESTful principles provide strategies to handle CRUD actions using HTTP methods mapped as follows:
With the recent release of Amazon API Gateway, developers can now create custom RESTful APIs that trigger AWS Lambda functions, allowing for truly server-less back ends that include built-in authorization, traffic management, monitoring, and analytics.
GET /cats – Retrieves a list of cats
GET /cats/5 – Retrieves a specific cat
POST /cats – Creates a new cat
PUT /cats/5 – Updates cat #5 (including references)
PATCH /cats/5 – Partially updates cat #5 (only the cat record)
DELETE /cats/5 – Deletes cat #5
You will notice that I used plural endpoint names here to keep it simple and not having to deal with odd pluralization (person/people, goose/geese) makes the life of the API consumer better and is easier for the API provider to implement (as most modern frameworks will natively handle /cats and /cats/5 under a common controller).
If a relation can only exist within another resource, RESTful principles provide useful guidance. A cat consists of a number of paws. These paws can be logically mapped to the /cats endpoint as follows:
GET /cats/5/paws – Retrieves list of paws for cat #5
GET /cats/5/paws/2 – Retrieves paw #2 for cat #5
POST /cats/5/paws – Creates a new paw in cat #5
PUT /cats/5/paws/2 – Updates paw #2 for cat #5
PATCH /cats/5/paws/2 – Partially updates paw #2 for cat #5
DELETE /cats/5/paws/2 – Deletes paw #2 for cat #5
If a relation can exist independently of the resource, it makes sense to just include an identifier for it within the output representation of the resource. The API consumer would then have to hit the relation’s endpoint. However, if the relation is commonly requested alongside the resource, the API offers functionality (via an attribute to include child records) to automatically embed the relation’s representation and avoid multiple hits to the API.
Simply put, always use SSL with no exceptions. Today, your web APIs can get accessed from anywhere there is internet (like libraries, coffee shops, airports among others). Not all of these are secure. Many don’t encrypt communications at all, allowing for easy eavesdropping or impersonation if authentication credentials are hijacked.
Another advantage of always using SSL is that guaranteed encrypted communications simplifies authentication efforts – you can get away with simple access tokens instead of having to sign each API request.
Always version your API. Versioning helps you iterate faster and prevents invalid requests from hitting updated endpoints. It also helps smooth over any major API version transitions as you can continue to offer old API versions for a period of time.
There are mixed opinions around whether an API version should be included in the URL or in a header. Academically speaking, it should probably be in a header. However, the version needs to be in the URL to ensure browser explorability of the resources across versions.
An API is never going to be completely stable. Change is inevitable. What’s important is how that change is managed. Well documented and announced multi-month depreciation schedules can be an acceptable practice for many APIs. It comes down to what is reasonable given the industry and possible consumers of the API.
Result filtering, sorting & searching
It’s best to keep the base resource URLs as lean as possible. Complex result filters, sorting requirements and advanced searching (when restricted to a single type of resource) can all be easily implemented as query parameters on top of the base URL. Let’s look at these in more detail:
Use a unique query parameter for each field that implements filtering. For example, when requesting a list of cats from the /cats endpoint, you may want to limit these to only those in the open state. This could be accomplished with a request like GET /cats?state=open. Here, state is a query parameter that implements a filter.
Similar to filtering, a generic parameter sort can be used to describe sorting rules. Accommodate complex sorting requirements by letting the sort parameter take in list of comma separated fields, each with a possible unary negative to imply descending sort order. Let’s look at some examples:
GET /cats?sort=-birthdate – Retrieves a list of cats in descending order of birth date
GET /cats?sort=-birthdate,birthplace – Retrieves a list of cats in descending order of birth date and within a specific birth date, the birth place in order
Sometimes basic filters aren’t enough and you need the power of full text search. Perhaps you’re already using ElasticSearch or another Lucene based search technology. When full text search is used as a mechanism of retrieving resource instances for a specific type of resource, it can be exposed on the API as a query parameter on the resource’s endpoint. Let’s say q. Search queries should be passed straight to the search engine and API output should be in the same format as a normal list result.
Combining these together, we can build queries like:
GET /cats?sort=-lastUpdateDate – Retrieve recently updated cats
GET /cats?state=vaccinated&sort=-lastUpdateDate – Retrieve recently vaccinated cats
GET /cats?q=sick&state=unvaccinated&sort=-lastUpdateDate Retrieve the list of cats that are unvaccinated that mentioning the word ‘sick’
Note: If you do support these advanced features, ensure that you support the basics too. You want to allow developers flexibility without requiring them to know everything about your API.
Aliases for common queries
To make the API experience more pleasant for the average consumer, consider packaging up sets of conditions into easily accessible RESTful paths. For example, the recently closed cats query above could be packaged up as GET /cats/vaccinated
Limiting which fields are returned by the API
The API consumer doesn’t always need the full representation of a resource. The ability select and chose returned fields goes a long way in letting the API consumer minimize network traffic and speed up their own usage of the API.
Use a fields query parameter that takes a comma separated list of fields to include. For example, the following request would retrieve just enough information to display a sorted listing of vaccinated cats:
GET /cats?fields=id,name,birthdate,lastUpdateDate &state=vaccinated&sort=-lastUpdateDate
Updates and inserts should return a resource representation which would include any server generated fields such as id, create date, modified date, etc.
JSON only responses
It’s time to support JSON only and leave XML behind in APIs. It’s verbose, make the output much larger, it’s hard to parse, it’s hard to read, its data model isn’t compatible with how most programming languages model data and its extendibility advantages are irrelevant when your output representation’s primary needs are serialization from an internal representation.
snake_case vs camelCase for field names
Many popular JSON APIs use snake_case. I suspect this is due to serialization libraries following naming conventions of the underlying language they are using. Perhaps we need to have JSON serialization libraries handle naming convention transformations.
JSON encoded POST, PUT & PATCH bodies
If you’re following the approach in this post, then you’ve embraced JSON for all API output. Let’s consider JSON for API input.
Many APIs use URL encoding in their API request bodies. URL encoding is exactly what it sounds like – request bodies where key value pairs are encoded using the same conventions as one would use to encode data in URL query parameters. This is simple, widely supported and gets the job done.
However, URL encoding has a few issues that make it problematic. It has no concept of data types. This forces the API to parse integers and booleans out of strings. Furthermore, it has no real concept of hierarchical structure. Although there are some conventions that can build some structure out of key value pairs (like appending [ ] to a key to represent an array), this is no comparison to the native hierarchical structure of JSON.
If the API is simple, URL encoding may suffice. However, complex APIs should stick to JSON for their API input. Either way, pick one and be consistent throughout the API.
An API that accepts JSON encoded POST, PUT & PATCH requests should also require the Content-Type header be set to application/json or throw a 415 Unsupported Media Type HTTP status code.
Envelope loving APIs typically include pagination data in the envelope itself. And I don’t blame them – until recently, there weren’t many better options. The right way to include pagination details today is using the Link header introduced by RFC 5988.
An API that uses the Link header can return a set of ready-made links so the API consumer doesn’t have to construct links themselves. This is especially important when pagination is cursor based. Here is an example of a Link header used properly, grabbed from GitHub’s documentation:
But this isn’t a complete solution as many APIs do like to return the additional pagination information, like a count of the total number of available results. An API that requires sending a count can use a custom HTTP header like X-Total-Count.
Auto loading related resource representations
There are many cases where an API consumer needs to load data related to (or referenced) from the resource being requested. Rather than requiring the consumer to hit the API repeatedly for this information, there would be a significant efficiency gain from allowing related data to be returned and loaded alongside the original resource on demand.
However, as this does go against some RESTful principles, we can minimize our deviation by only doing so based on an embed (or expand) query parameter.
In this case, embed would be a comma separated list of fields to be embedded. Dot-notation could be used to refer to sub-fields. For example:
This would return a ticket with additional details embedded, like:
Of course, ability to implement something like this really depends on internal complexity. This kind of embedding can easily result in an N+1 select issue.
Overriding the HTTP method
Some HTTP clients can only work with simple GET and POST requests. To increase accessibility to these limited clients, the API needs a way to override the HTTP method. Although there aren’t any hard standards here, the popular convention is to accept a request header X-HTTP-Method-Override with a string value containing one of PUT, PATCH or DELETE.
Note that the override header should only be accepted on POST requests. GET requests should never change data on the server!
To prevent abuse, it is standard practice to add some sort of rate limiting to an API. RFC 6585 introduced a HTTP status code 429 Too Many Requests to accommodate this.
However, it can be very useful to notify the consumer of their limits before they actually hit it. This is an area that currently lacks standards but has a number of popular conventions using HTTP response headers.
At a minimum, include the following headers (using Twitter’s naming conventions as headers typically don’t have mid-word capitalization):
X-Rate-Limit-Limit – The number of allowed requests in the current period
X-Rate-Limit-Remaining – The number of remaining requests in the current period
X-Rate-Limit-Reset – The number of seconds left in the current period
Why is number of seconds left being used instead of a time stamp for X-Rate-Limit-Reset?
A RESTful API should be stateless. This means that request authentication should not depend on cookies or sessions. Instead, each request should come with some sort authentication credentials.
By always using SSL, the authentication credentials can be simplified to a randomly generated access token that is delivered in the user name field of HTTP Basic Auth. The great thing about this is that it’s completely browser explorable – the browser will just popup a prompt asking for credentials if it receives a 401 Unauthorized status code from the server.
However, this token-over-basic-auth method of authentication is only acceptable in cases where it’s practical to have the user copy a token from an administration interface to the API consumer environment. In cases where this isn’t possible, OAuth 2 should be used to provide secure token transfer to a third party. OAuth 2 uses Bearer tokens & also depends on SSL for its underlying transport encryption.
An API that needs to support JSONP will need a third method of authentication, as JSONP requests cannot send HTTP Basic Auth credentials or Bearer tokens. In this case, a special query parameter access_token can be used. Note: there is an inherent security issue in using a query parameter for the token as most web servers store query parameters in server logs.
For what it’s worth, all three methods above are just ways to transport the token across the API boundary. The actual underlying token itself could be identical.
HTTP provides a built-in caching framework! All you have to do is include some additional outbound response headers and do a little validation when you receive some inbound request headers.
There are 2 approaches: ETag and Last-Modified
ETag: When generating a request, include a HTTP header ETag containing a hash or checksum of the representation. This value should change whenever the output representation changes. Now, if an inbound HTTP requests contains a If-None-Match header with a matching ETag value, the API should return a 304 Not Modified status code instead of the output representation of the resource.
Last-Modified: This basically works like to ETag, except that it uses timestamps. The response header Last-Modified contains a timestamp in RFC 1123 format which is validated against If-Modified-Since. Note that the HTTP spec has had 3 different acceptable date formats and the server should be prepared to accept any one of them.
Just like an HTML error page shows a useful error message to a visitor, an API should provide a useful error message in a known consumable format. The representation of an error should be no different than the representation of any resource, just with its own set of fields.
The API should always return sensible HTTP status codes. API errors typically break down into 2 types: 400 series status codes for client issues & 500 series status codes for server issues. At a minimum, the API should standardize that all 400 series errors come with consumable JSON error representation. If possible (i.e. if load balancers & reverse proxies can create custom error bodies), this should extend to 500 series status codes.
A JSON error body should provide a few things for the developer – a useful error message, a unique error code (that can be looked up for more details in the docs) and possibly a detailed description. JSON output representation for something like this would look like:
Validation errors for PUT, PATCH and POST requests will need a field breakdown. This is best modeled by using a fixed top-level error code for validation failures and providing the detailed errors in an additional errors field.
HTTP status codes
HTTP defines a bunch of meaningful status codes that can be returned from your API. These can be leveraged to help the API consumers route their responses accordingly. I’ve curated a short list of the ones that you definitely should be using:
200 OK – Response to a successful GET, PUT, PATCH or DELETE. Can also be used for a POST that doesn’t result in a creation.
201 Created – Response to a POST that results in a creation. Should be combined with a Location header pointing to the location of the new resource
204 No Content – Response to a successful request that won’t be returning a body (like a DELETE request)
304 Not Modified – Used when HTTP caching headers are in play
400 Bad Request – The request is malformed, such as if the body does not parse
401 Unauthorized – When no or invalid authentication details are provided. Also useful to trigger an auth popup if the API is used from a browser
403 Forbidden – When authentication succeeded but authenticated user doesn’t have access to the resource
404 Not Found – When a non-existent resource is requested
405 Method Not Allowed – When an HTTP method is being requested that isn’t allowed for the authenticated user
410 Gone – Indicates that the resource at this end point is no longer available. Useful as a blanket response for old API versions
415 Unsupported Media Type – If incorrect content type was provided as part of the request
422 Unprocessable Entity – Used for validation errors
429 Too Many Requests – When a request is rejected due to rate limiting
In the next release, we will go into a walk through on how to develop the business and data access layers for your RESTful service.