Build an API Using Go and MySQL

The project scope is to build an API to manage content posts. You’ll create an API with three functionalities: create a post, read a single post, and list posts. The database is MySQL installed in localhost.

The database library is using https://github.com/jmoiron/sqlx.

The HTTP routing library is using https://github.com/gin-gonic/gin.

Since the Go community already has a wonderful library, there is almost no reason to write everything from scratch.

---

Application Design

Project Application Design

We have two packages: main and post.

The main package is an executable package in Golang that runs the application. It consists of an instance from the package post (postClient) and three functions to handle routing (listPost, readPost, and createPost).

The post package is the package that interacts with the database to manage the post. It has two object types: Client and Post. Client is an interface to use the package. Post is an abstraction of the real-world content post model. The instance of Client has three functionalities to run a query or insert to the database.

The database structure of this project is only one table named “post” to store the object Post in the package post. The table structure is the following.

---

Code

'post’ package

These following code blocks explain how we build the Client and Post types and the NewClient function that requires DB input. The DB input is using a package that is initialized outside the package. The idea of this approach is the package does not care who and what creates the Client instance, as long as it provides a working DB connection pool. The inline comment explains the code.

// Client is instance of module, the attribute is DB instance
	type Client struct {
		DB *sqlx.DB
	}

	// NewClient is function to create new instance of Post module.
	func NewClient(db *sqlx.DB) (c Client) {
		return Client{
			DB: db,
		}
	}

	// Post is object structure of real-world post model
	type Post struct {
		ID         int64     `json:"id"`
		Content    string    `json:"content"`
		CreateTime time.Time `json:"create_time"`
	}

The next code block shows the function inside the Client. All of the functions are using a function from sqlx.

// CreatePost is function to create new content, require a content in string
	func (c *Client) CreatePost(content string) (id int64, err error) {
		// run the insert script to db
		result, err := c.DB.Exec(`
			INSERT INTO post (content, create_time)
			VALUES (?, now())
		`,
			content)
		if err != nil {
			log.Println(err)
			return
		}

		// get the last insert id
		id, err = result.LastInsertId()
		if err != nil {
			log.Println(err)
			return
		}

		return
	}

	// ReadPost is function to read single post
	func (c *Client) ReadPost(id int64) (post Post, err error) {
		// run the query with given id
		row := c.DB.QueryRow(`
				SELECT id, content, create_time
				FROM post
				WHERE id = ?`,
			id)

		// assign the query result to 'post' object
		err = row.Scan(&post.ID,
			&post.Content,
			&post.CreateTime)

		if err != nil {
			log.Println(err)
			return
		}

		return
	}

	// ListPost is function to read list of post with limit
	func (c *Client) ListPost(limit int64) (posts []Post, err error) {
		// run the query with limit
		rows, err := c.DB.Query(`
				SELECT id, content, create_time
				FROM post
				ORDER BY id DESC
				LIMIT ?`,
			limit)

		if err != nil {
			log.Println(err)
			return
		}

		// loop the result and assign each row to single object
		defer rows.Close()
		for rows.Next() {
			post := Post{}

			err = rows.Scan(&post.ID,
				&post.Content,
				&post.CreateTime)

			if err != nil {
				log.Println(err)
				return
			}
			posts = append(posts, post)

		}

		return
	}

#software-engineering #programming #golang #api #data-science

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Best MySQL DigitalOcean Performance – ScaleGrid vs. DigitalOcean Managed Databases

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MySQL is the all-time number one open source database in the world, and a staple in RDBMS space. DigitalOcean is quickly building its reputation as the developers cloud by providing an affordable, flexible and easy to use cloud platform for developers to work with. MySQL on DigitalOcean is a natural fit, but what’s the best way to deploy your cloud database? In this post, we are going to compare the top two providers, DigitalOcean Managed Databases for MySQL vs. ScaleGrid MySQL hosting on DigitalOcean.

At a glance – TLDR
ScaleGrid Blog - At a glance overview - 1st pointCompare Throughput
ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads. Read now

ScaleGrid Blog - At a glance overview - 2nd pointCompare Latency
On average, ScaleGrid achieves almost 30% lower latency over DigitalOcean for the same deployment configurations. Read now

ScaleGrid Blog - At a glance overview - 3rd pointCompare Pricing
ScaleGrid provides 30% more storage on average vs. DigitalOcean for MySQL at the same affordable price. Read now

MySQL DigitalOcean Performance Benchmark
In this benchmark, we compare equivalent plan sizes between ScaleGrid MySQL on DigitalOcean and DigitalOcean Managed Databases for MySQL. We are going to use a common, popular plan size using the below configurations for this performance benchmark:

Comparison Overview
ScaleGridDigitalOceanInstance TypeMedium: 4 vCPUsMedium: 4 vCPUsMySQL Version8.0.208.0.20RAM8GB8GBSSD140GB115GBDeployment TypeStandaloneStandaloneRegionSF03SF03SupportIncludedBusiness-level support included with account sizes over $500/monthMonthly Price$120$120

As you can see above, ScaleGrid and DigitalOcean offer the same plan configurations across this plan size, apart from SSD where ScaleGrid provides over 20% more storage for the same price.

To ensure the most accurate results in our performance tests, we run the benchmark four times for each comparison to find the average performance across throughput and latency over read-intensive workloads, balanced workloads, and write-intensive workloads.

Throughput
In this benchmark, we measure MySQL throughput in terms of queries per second (QPS) to measure our query efficiency. To quickly summarize the results, we display read-intensive, write-intensive and balanced workload averages below for 150 threads for ScaleGrid vs. DigitalOcean MySQL:

ScaleGrid MySQL vs DigitalOcean Managed Databases - Throughput Performance Graph

For the common 150 thread comparison, ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads.

#cloud #database #developer #digital ocean #mysql #performance #scalegrid #95th percentile latency #balanced workloads #developers cloud #digitalocean droplet #digitalocean managed databases #digitalocean performance #digitalocean pricing #higher throughput #latency benchmark #lower latency #mysql benchmark setup #mysql client threads #mysql configuration #mysql digitalocean #mysql latency #mysql on digitalocean #mysql throughput #performance benchmark #queries per second #read-intensive #scalegrid mysql #scalegrid vs. digitalocean #throughput benchmark #write-intensive

APIs for Beginners - How to use an API (Full Course / Tutorial)

What is an API? Learn all about APIs (Application Programming Interfaces) in this full tutorial for beginners. You will learn what APIs do, why APIs exist, and the many benefits of APIs. APIs are used all the time in programming and web development so it is important to understand how to use them.

You will also get hands-on experience with a few popular web APIs. As long as you know the absolute basics of coding and the web, you’ll have no problem following along.
⭐️ Unit 1 - What is an API
⌨️ Video 1 - Welcome (0:00:00)
⌨️ Video 2 - Defining Interface (0:03:57)
⌨️ Video 3 - Defining API (0:07:51)
⌨️ Video 4 - Remote APIs (0:12:55)
⌨️ Video 5 - How the web works (0:17:04)
⌨️ Video 6 - RESTful API Constraint Scavenger Hunt (0:22:00)

⭐️ Unit 2 - Exploring APIs
⌨️ Video 1 - Exploring an API online (0:27:36)
⌨️ Video 2 - Using an API from the command line (0:44:30)
⌨️ Video 3 - Using Postman to explore APIs (0:53:56)
⌨️ Video 4 - Please please Mr. Postman (1:03:33)
⌨️ Video 5 - Using Helper Libraries (JavaScript) (1:14:41)
⌨️ Video 6 - Using Helper Libraries (Python) (1:24:40)

⭐️ Unit 3 - Using APIs
⌨️ Video 1 - Introducing the project (1:34:18)
⌨️ Video 2 - Flask app (1:36:07)
⌨️ Video 3 - Dealing with API Limits (1:50:00)
⌨️ Video 4 - JavaScript Single Page Application (1:54:27)
⌨️ Video 5 - Moar JavaScript and Recap (2:07:53)
⌨️ Video 6 - Review (2:18:03)
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=GZvSYJDk-us&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=5
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#apis #apis for beginners #how to use an api #apis for beginners - how to use an api #application programming interfaces #learn all about apis

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 = requests.post('https://api.acmeinc.com/widgets?take=10&skip=' + 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

Build a Go Web API with the New Digital Ocean App Platform: A How-To Guide

Recently, Digital Ocean announced they’re entering the PaaS market with their new application platform. They’ve hosted virtual machines (droplets) and Kubernetes based services for years, but now they’re creating a platform that’s a simple point and click to get an application up and running.

So I decided to try it. In this tutorial, we’re going to build an application on that platform. I will use Go to make a small web API and have it backed by a SQLite database. I’ll show you the steps required, and we’ll see just how easy it is (or isn’t) to deploy applications on the platform.

We’ll create a small service that:

• Takes a city name as input
• searches against a database
• Returns ZIP code and other information for that city

If you want to follow along with this tutorial, here’s what you’ll need:

• Computer with Go Installed

• A Digital Ocean Account

- DB Browser for SQL Lite

- Download this CSV

Creating Your Repository

The first thing we’ll need to do is create a repository on GitHub. The Digital Ocean app platform uses your repos to pull code from and builds from there.

Now, clone the Digital Ocean sample repository to another folder:

Now, you can fork this. However, since we’re not going to be contributing changes back to that repo, and we don’t want to pull changes from it, it’s essentially a new project. So I’m just going to copy the files from that repo into mine.

Now I have the sample code in my own repo:

Cool, now let’s push it up to Github.

git add .
git commmit -m "Initial Commit"
git push origin main

Now the sample project is available on my Github, where I can connect to it.

#programming #api #golang #golang-api #api-development #go #build-a-go-web-api #digital-ocean

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.

Method

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.

Data

With regards to how the APIs are shared:

• Documentation is where just the Swagger/OpenAPI docs are hosted somewhere. e.g. https://api.linkgroup.com/member/docs/index
• Portal is where an interactive portal has been developed. e.g. https://dev.telstra.com/
• The web page is where the company has a single page that isn’t interactive explaining their Public APIs. e.g. https://www.bendigoadelaide.com.au/banking-products-api.asp

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