Joseph  Norton

Joseph Norton


An Intro to GraphQL API

Today, I want to show you how to build serverless backends with the Hasura GraphQL API. After looking at GraphQL and its advantages, we will learn how to create new tables for our API. Next, we want to fill our database with real data. Of course, we want to have relationships between our tables. Finally, we will learn how to manipulate the data using mutations. No previous knowledge of GraphQL is required to follow this tutorial.

Table of Contents

  • About GraphQL
  • About Hasura
  • Creating a project
  • Create tables
  • Insert data
  • Queries
  • Relationships
  • Object relationship
  • Array relationship
  • Many-to-many relationship
  • Mutations

About GraphQL

GraphQL is a typed query language for APIs. More and more tech companies, including tech giants like Facebook, Twitter and GitHub, are switching from common REST apis to GraphQL solutions. The main advantages of GraphQL over other API architectures like REST are:

  • About GraphQL
  • About Hasura
  • Creating a project
  • Create tables
  • Insert data
  • Queries
  • Relationships
  • Object relationship
  • Array relationship
  • Many-to-many relationship
  • Mutations

Here is a sample query:

And its corresponding result:

As you can see, the query is very intuitive and the result is predictable. You get exactly what you ask for: not more and not less.

As web applications tend to get more complex, there is a growing need for fast and easily maintainable solutions. So this is probably a good time to have a glimpse at GraphQL. But how do we use it? Do I need to build my own server? How can we connect it to our frontend? Don’t worry, we’ll get there.

About Hasura

Hasura provides you with an open source GraphQL engine that runs in a Docker container. Hasura connects to the Postgres database that is created with the project. You can also run Hasura GraphQL on top of an existing project. This can in particular be useful if you want to migrate to GraphQL, as it allows you to do the migration in smaller steps.

There are several options as to where you can deploy your GraphQL API: Heroku, Docker, Digital Ocean, Azure, AWS and Google Cloud.

Creating a project

In this post, we will get started with Heroku. We are going to create a Harry Potter api 🤓

On the dashboard, choose a (unique) name for your api and click the “Deploy” button:

That was easy, right? Now, if you scroll to the bottom you will see this:

When you click on “View”, the Hasura console will open in the GraphiQL tool, which is also one of the features that makes your life with GraphQL super easy. In the Hasura console, you can create tables and test queries. Let’s have a quick look at the console:

  1. This is the (only) endpoint used to interact with the api. When we later poll data from external services, this is the URL we need to access. And yes, you’ve seen correctly: requests to GraphQL are always POST requests.
  2. Here, you can add request headers. If you want to add authentication (e.g. with JWT tokens) later, you can add the headers here.
  3. This is the field where you can test queries.
  4. Here, the results will be displayed.
  5. We will go there next, to create our first table.

Create tables

We first want to create a table to store movies. Let’s do that!

  1. This is the (only) endpoint used to interact with the api. When we later poll data from external services, this is the URL we need to access. And yes, you’ve seen correctly: requests to GraphQL are always POST requests.
  2. Here, you can add request headers. If you want to add authentication (e.g. with JWT tokens) later, you can add the headers here.
  3. This is the field where you can test queries.
  4. Here, the results will be displayed.
  5. We will go there next, to create our first table.

Create the following two tables:

characters (id: UUID, name: Text, hair_color: Text, house: Text, wizard: Boolean, birth_year: Integer, patronus: Text)

actors (id: UUID, name: Text, birth_year: Integer, awards: Integer)

Insert data

Let’s add some data data:

Add one other character, as well as two movies and two actors.


Now that we have some data, we can make our first query in GraphiQL.

It will return the two characters that we have already inserted into our characters table.

There are a lot of different constraints you can add to your queries. For example, you can make sure only to get a certain number of objects. Or only get the objects where a certain condition is true. All this is very well documented by Hasura: You can read through it and tweak your queries, so that they return different results. You might have to add some more data in order to do so.


Currently, we have three tables that are all independent from each other. With a query, we can retrieve movies, characters and actors. But we cannot retrieve the movies with their characters and in turn the respective actors. In order to do this, we need to define relationships.

There are two different types of relationships: the object relationship and the array relationship. The object relationship is a one-to-one relationship. For example, a character has a single nested resource that is called actor. The array relationship is a one-to-many relationship. For example, a movie will have an array of nested resources called scenes.

Object relationship

Let’s first model the relationship between characters and actors. The first step is to add a actor_id to the characters table:

After adding the column, we need to edit it and to make sure that the actor_id is actually a foreign key, pointing to the actors table.

When we go to the tab “Relationships” on characters, a suggested relationship will appear. That’s right — Hasura detects foreign keys automatically and makes suggestions regarding relationships. As a name, we’ll take “actor”.

Next, we want to connect the characters with the corresponding actors in our database. When we now look into the characters table, we can see that the actor_id for the previously created characters is NULL. We can now edit the data and add the ids of the actors that correspond to these characters.

Now the characters and their actors are linked. Now we can access fields from the actors along with the characters in the same query:

Array relationship

The array relationship is a one-to-many relationship. This means that one object of a table can have several objects of another table. Let’s say in our example, one movie can have several scenes and each scene belongs to one movie. A scene has an id, a name, a location and a movie_id. So let’s create a new table called “scenes” to our database:

Great! Now, just like we did before, we need to modify the table and make the movie_id a foreign key:

When we now go to the movies table and click on “Relationships”, we can see the suggested array relationship for scenes. Let’s add this relationship and call it “scenes”. This is all that is necessary to create an array relationship. To test it, insert some rows into the scenes table.

Many-to-many relationship

As explained before, the array relationship is a one-to-many relationship. However, in our case of movies and characters, we have a many-to-many relationship. One movie can have several characters and one character can appear in several movies. For this scenario, we need to create a join table that we will call “movie_characters” in which we can store the relationship between one movie and one character. Let’s create the “movie_characters” table that has an ID, a movie_id and a character_id.

From the perspective of the movie_characters table, we need object relationships to both the movies table and the characters table. This is because in each movie_character, there is one movie and one character stored.

Like above, edit both the movie_id and the character_id on the movie_character table and tick the checkbox for them to be foreign keys. Then add the correct reference table and the reference column. For the movie_id, the reference table is movies and for the character_id, the reference table is characters. For both reference columns, it will be ID.

When you now click the tab “Relationships”, you’ll see two suggestions for object relationships. Add them both and call them “movie” and “character”. Once added, it should look like this:

Of course, like above, we need to create the relationships with our data. Create new rows in the movie_characters table for each movie — character relationship, using their IDs.

Yayy, now all our tables are modelled with their correct relationships. Let’s test it with a query.

Isn’t this neat? With just one query, we are able to access several resources with those fields we want. Compared to REST where usually the whole object is returned, we can reduce the query to the essentials. This makes the API more efficient, more lightweight and easier to handle.


So far, we learned how to get data from our API. But what about adding new data? In our case, we might want to add a movie or a character. For this, we need mutations. Mutations are easy to use with the GraphQL API and just like queries, we can try them in the Hasura console:

Let me explain what is happening here. Inside a mutation, we can call different methods like insert, update or delete on the resources that we store in our database. In our case, we want to insert a new movie. We need to pass the movies as objects and it is possible to insert several objects in one mutation. In the end, we need to return something, which is the ID of the newly created object in our example.

Again, there is full documentation on mutations on the Hasura website: Go through the examples and try some other mutations, like deleting a movie.

That is it for now. I hope you had fun learning about GraphQL and that you are eager to extend your Harry Potter API with lots of new tables and data. If something is not clear, you can always send me an email at or message me over Twitter:

Stay tuned for updates. I will soon publish another blogpost on how to connect your Hasura backend to your VueJS frontend 🎉

#graphql #database

What is GEEK

Buddha Community

An Intro to GraphQL API

Top 10 API Security Threats Every API Team Should Know

As more and more data is exposed via APIs either as API-first companies or for the explosion of single page apps/JAMStack, API security can no longer be an afterthought. The hard part about APIs is that it provides direct access to large amounts of data while bypassing browser precautions. Instead of worrying about SQL injection and XSS issues, you should be concerned about the bad actor who was able to paginate through all your customer records and their data.

Typical prevention mechanisms like Captchas and browser fingerprinting won’t work since APIs by design need to handle a very large number of API accesses even by a single customer. So where do you start? The first thing is to put yourself in the shoes of a hacker and then instrument your APIs to detect and block common attacks along with unknown unknowns for zero-day exploits. Some of these are on the OWASP Security API list, but not all.

Insecure pagination and resource limits

Most APIs provide access to resources that are lists of entities such as /users or /widgets. A client such as a browser would typically filter and paginate through this list to limit the number items returned to a client like so:

First Call: GET /items?skip=0&take=10 
Second Call: GET /items?skip=10&take=10

However, if that entity has any PII or other information, then a hacker could scrape that endpoint to get a dump of all entities in your database. This could be most dangerous if those entities accidently exposed PII or other sensitive information, but could also be dangerous in providing competitors or others with adoption and usage stats for your business or provide scammers with a way to get large email lists. See how Venmo data was scraped

A naive protection mechanism would be to check the take count and throw an error if greater than 100 or 1000. The problem with this is two-fold:

  1. For data APIs, legitimate customers may need to fetch and sync a large number of records such as via cron jobs. Artificially small pagination limits can force your API to be very chatty decreasing overall throughput. Max limits are to ensure memory and scalability requirements are met (and prevent certain DDoS attacks), not to guarantee security.
  2. This offers zero protection to a hacker that writes a simple script that sleeps a random delay between repeated accesses.
skip = 0
while True:    response ='' + skip),                      headers={'Authorization': 'Bearer' + ' ' + sys.argv[1]})    print("Fetched 10 items")    sleep(randint(100,1000))    skip += 10

How to secure against pagination attacks

To secure against pagination attacks, you should track how many items of a single resource are accessed within a certain time period for each user or API key rather than just at the request level. By tracking API resource access at the user level, you can block a user or API key once they hit a threshold such as “touched 1,000,000 items in a one hour period”. This is dependent on your API use case and can even be dependent on their subscription with you. Like a Captcha, this can slow down the speed that a hacker can exploit your API, like a Captcha if they have to create a new user account manually to create a new API key.

Insecure API key generation

Most APIs are protected by some sort of API key or JWT (JSON Web Token). This provides a natural way to track and protect your API as API security tools can detect abnormal API behavior and block access to an API key automatically. However, hackers will want to outsmart these mechanisms by generating and using a large pool of API keys from a large number of users just like a web hacker would use a large pool of IP addresses to circumvent DDoS protection.

How to secure against API key pools

The easiest way to secure against these types of attacks is by requiring a human to sign up for your service and generate API keys. Bot traffic can be prevented with things like Captcha and 2-Factor Authentication. Unless there is a legitimate business case, new users who sign up for your service should not have the ability to generate API keys programmatically. Instead, only trusted customers should have the ability to generate API keys programmatically. Go one step further and ensure any anomaly detection for abnormal behavior is done at the user and account level, not just for each API key.

Accidental key exposure

APIs are used in a way that increases the probability credentials are leaked:

  1. APIs are expected to be accessed over indefinite time periods, which increases the probability that a hacker obtains a valid API key that’s not expired. You save that API key in a server environment variable and forget about it. This is a drastic contrast to a user logging into an interactive website where the session expires after a short duration.
  2. The consumer of an API has direct access to the credentials such as when debugging via Postman or CURL. It only takes a single developer to accidently copy/pastes the CURL command containing the API key into a public forum like in GitHub Issues or Stack Overflow.
  3. API keys are usually bearer tokens without requiring any other identifying information. APIs cannot leverage things like one-time use tokens or 2-factor authentication.

If a key is exposed due to user error, one may think you as the API provider has any blame. However, security is all about reducing surface area and risk. Treat your customer data as if it’s your own and help them by adding guards that prevent accidental key exposure.

How to prevent accidental key exposure

The easiest way to prevent key exposure is by leveraging two tokens rather than one. A refresh token is stored as an environment variable and can only be used to generate short lived access tokens. Unlike the refresh token, these short lived tokens can access the resources, but are time limited such as in hours or days.

The customer will store the refresh token with other API keys. Then your SDK will generate access tokens on SDK init or when the last access token expires. If a CURL command gets pasted into a GitHub issue, then a hacker would need to use it within hours reducing the attack vector (unless it was the actual refresh token which is low probability)

Exposure to DDoS attacks

APIs open up entirely new business models where customers can access your API platform programmatically. However, this can make DDoS protection tricky. Most DDoS protection is designed to absorb and reject a large number of requests from bad actors during DDoS attacks but still need to let the good ones through. This requires fingerprinting the HTTP requests to check against what looks like bot traffic. This is much harder for API products as all traffic looks like bot traffic and is not coming from a browser where things like cookies are present.

Stopping DDoS attacks

The magical part about APIs is almost every access requires an API Key. If a request doesn’t have an API key, you can automatically reject it which is lightweight on your servers (Ensure authentication is short circuited very early before later middleware like request JSON parsing). So then how do you handle authenticated requests? The easiest is to leverage rate limit counters for each API key such as to handle X requests per minute and reject those above the threshold with a 429 HTTP response. There are a variety of algorithms to do this such as leaky bucket and fixed window counters.

Incorrect server security

APIs are no different than web servers when it comes to good server hygiene. Data can be leaked due to misconfigured SSL certificate or allowing non-HTTPS traffic. For modern applications, there is very little reason to accept non-HTTPS requests, but a customer could mistakenly issue a non HTTP request from their application or CURL exposing the API key. APIs do not have the protection of a browser so things like HSTS or redirect to HTTPS offer no protection.

How to ensure proper SSL

Test your SSL implementation over at Qualys SSL Test or similar tool. You should also block all non-HTTP requests which can be done within your load balancer. You should also remove any HTTP headers scrub any error messages that leak implementation details. If your API is used only by your own apps or can only be accessed server-side, then review Authoritative guide to Cross-Origin Resource Sharing for REST APIs

Incorrect caching headers

APIs provide access to dynamic data that’s scoped to each API key. Any caching implementation should have the ability to scope to an API key to prevent cross-pollution. Even if you don’t cache anything in your infrastructure, you could expose your customers to security holes. If a customer with a proxy server was using multiple API keys such as one for development and one for production, then they could see cross-pollinated data.

#api management #api security #api best practices #api providers #security analytics #api management policies #api access tokens #api access #api security risks #api access keys

Autumn  Blick

Autumn Blick


Public ASX100 APIs: The Essential List

We’ve conducted some initial research into the public APIs of the ASX100 because we regularly have conversations about what others are doing with their APIs and what best practices look like. Being able to point to good local examples and explain what is happening in Australia is a key part of this conversation.


The method used for this initial research was to obtain a list of the ASX100 (as of 18 September 2020). Then work through each company looking at the following:

  1. Whether the company had a public API: this was found by googling “[company name] API” and “[company name] API developer” and “[company name] developer portal”. Sometimes the company’s website was navigated or searched.
  2. Some data points about the API were noted, such as the URL of the portal/documentation and the method they used to publish the API (portal, documentation, web page).
  3. Observations were recorded that piqued the interest of the researchers (you will find these below).
  4. Other notes were made to support future research.
  5. You will find a summary of the data in the infographic below.


With regards to how the APIs are shared:

#api #api-development #api-analytics #apis #api-integration #api-testing #api-security #api-gateway

An API-First Approach For Designing Restful APIs | Hacker Noon

I’ve been working with Restful APIs for some time now and one thing that I love to do is to talk about APIs.

So, today I will show you how to build an API using the API-First approach and Design First with OpenAPI Specification.

First thing first, if you don’t know what’s an API-First approach means, it would be nice you stop reading this and check the blog post that I wrote to the Farfetchs blog where I explain everything that you need to know to start an API using API-First.

Preparing the ground

Before you get your hands dirty, let’s prepare the ground and understand the use case that will be developed.


If you desire to reproduce the examples that will be shown here, you will need some of those items below.

  • NodeJS
  • OpenAPI Specification
  • Text Editor (I’ll use VSCode)
  • Command Line

Use Case

To keep easy to understand, let’s use the Todo List App, it is a very common concept beyond the software development community.

#api #rest-api #openai #api-first-development #api-design #apis #restful-apis #restful-api

Marcelle  Smith

Marcelle Smith


What Are Good Traits That Make Great API Product Managers

As more companies realize the benefits of an API-first mindset and treating their APIs as products, there is a growing need for good API product management practices to make a company’s API strategy a reality. However, API product management is a relatively new field with little established knowledge on what is API product management and what a PM should be doing to ensure their API platform is successful.

Many of the current practices of API product management have carried over from other products and platforms like web and mobile, but API products have their own unique set of challenges due to the way they are marketed and used by customers. While it would be rare for a consumer mobile app to have detailed developer docs and a developer relations team, you’ll find these items common among API product-focused companies. A second unique challenge is that APIs are very developer-centric and many times API PMs are engineers themselves. Yet, this can cause an API or developer program to lose empathy for what their customers actually want if good processes are not in place. Just because you’re an engineer, don’t assume your customers will want the same features and use cases that you want.

This guide lays out what is API product management and some of the things you should be doing to be a good product manager.

#api #analytics #apis #product management #api best practices #api platform #api adoption #product managers #api product #api metrics

Autumn  Blick

Autumn Blick


54% of Developers Cite Lack of Documentation as the Top Obstacle to Consuming APIs

Recently, I worked with my team at Postman to field the 2020 State of the API survey and report. We’re insanely grateful to the folks who participated—more than 13,500 developers and other professionals took the survey, helping make this the largest and most comprehensive survey in the industry. (Seriously folks, thank you!) Curious what we learned? Here are a few insights in areas that you might find interesting:

API Reliability

Whether internal, external, or partner, APIs are perceived as reliable—more than half of respondents stated that APIs do not break, stop working, or materially change specification often enough to matter. Respondents choosing the “not often enough to matter” option here came in at 55.8% for internal APIs, 60.4% for external APIs, and 61.2% for partner APIs.

Obstacles to Producing APIs

When asked about the biggest obstacles to producing APIs, lack of time is by far the leading obstacle, with 52.3% of respondents listing it. Lack of knowledge (36.4%) and people (35.1%) were the next highest.

#api #rest-api #apis #api-first-development #api-report #api-documentation #api-reliability #hackernoon-top-story