Colorkrew Blog

It is almost impossible for a backend engineer to be oblivious to RESTful API in the 21st century, as it is one of the most popular API types. We can mostly attribute its popularity to its scalability, flexibility, and simplicity, all of which are highly sought-after qualities in modern APIs. If you also find these qualities desirable, you should consider building APIs following the RESTful principles. In this article, I will explain what counts as a RESTful API and demonstrate how to design one from scratch.

The first programming paradigm that most programmers in the 21st century learn is probably Object Oriented Programming (or OOP for short). Object Oriented Programming allows us to transform real-world entities into highly abstract models with descriptive properties and executable methods to simulate their behaviors in the real world. Despite its numerous advantages, such as readability, reusability, and maintainability, it also introduces immense complexity to state management. The difficulty in keeping track of the states of objects has led head-scratching exhausted programmers to churn out error-prone code and cause bugs that would take hours, or even days, to locate and fix. “Is there a way out of this undesirable situation,” you might ask. Here is the good news: a lesser-known yet widely-used programming paradigm called Functional Programming (or FP for short) can help turn the tide around and decrease the number of bugs we cause. In this article, I will explain what Functional Programming is and why it can help us avoid bugs.

Incorporating OAuth (short for Open Authorization) into an application might seem somewhat intimidating and disheartening for many entry-level software engineers. After all, they need to spend hours—or even days—implementing a complicated authentication process with the correct configuration, only to realize they have merely completed a tiny feature. Despite all the hard work it entails, OAuth is a safe and efficient way for users to grant websites and applications access to their personal information. Therefore, it is worth the effort to comprehend how OAuth works. In this article, I will break down all the steps involved in the OAuth process to help you kick-start your OAuth journey.

Dear Diary – An opportunity

In October 2022, I embarked on my journey to Japan as a Japanese Language School student with the aim of starting anew in my professional career and evaluating my comfort level for potentially living here for the next decade. At that time, my proficiency in Japanese was limited to JLPT N4 certification, barely allowing me to engage in conversations or read signboards. Nevertheless, I felt optimistic about my upcoming Japanese Language education. 

This Developer Camp holds a special place in my heart as it was my inaugural experience attending a developer camp. Set against the picturesque coastline of Enoshima, Japan, this camp combined technical presentations, team activities, and beachside brainstorming sessions.

Day 1: Arrival, Introductions, and Technical Insights:

We arrived at Ofuna station, did a quick grocery trip to stock up. then, we made our way to the accomodation located by the ocean in Enoshima. The first order of business was the introductory presentations. We had two sessions lined up. - 1st presentation allowed each participant to introduce themselves and share their background, fostering a sense of familiarity and camaraderie within the group. - 2nd presentation focused on technical topics, encouraging us to explore innovative ways to enhance our product or delve into any other relevant technical subject.

If you became a frontend engineer after 2015, chances are that you have used or at least heard about Promise. As I have covered in my previous blog, Promise can help us specify sequential relations between operations in asynchronous programming in a readable and maintainable manner. Promise object in JavaScript has methods, such as then and catch, that can help us organize the sequential execution of operations in a pattern called Promise Chaining. Clean and organized as Promise Chaining is, some people—especially those more accustomed to synchronous programming—find it unintuitive and confusing. Lucky for them, ECMAScript 2017 introduced a new feature that allows us to write asynchronous code as if it were synchronous. This new feature consists of two keywords: async and await. In this article, I will cover the fundamentals of async/await and how to transition from Promise Chaining to using async/await.

As I sit here reflecting on my first three months at Colorkrew, I am filled with excitement for what the future holds. I joined the Biz team in January 2023.

From day one, I was welcomed with open arms by my friendly coworkers and immediately felt a sense of belonging that was amplified by the fact that software that we developing is also the one we use in our everyday work. I knew I had made the right choice in joining this amazing team.

If you have done any web development after 2015, chances are that you have heard of the concept of Promise. It wouldn’t be an overstatement to claim that Promise is ubiquitous in modern-day front-end codebases. However, many web developers—especially those who do not have much experience in front-end development—have been using Promise without thoroughly understanding its inner working. This has led to countless misuses of Promise and consequent bugs. In this article, I will walk you through what motivated the creation of Promise, how Promise works, and how we should use it in our code, under the assumption that you don’t have much experience in front-end development.

Just like real life, the world of computer science is replete with trade-offs. Relational databases are no exception. When interacting with relational databases, we face the dilemma between data consistency and transaction concurrency. The former guarantees the data is trustworthy, while the latter ensures relational databases can conduct transactions swiftly. Both are desirable qualities of relational databases, but we cannot simultaneously achieve them to the fullest extent. Today, I will discuss how isolation levels can help us structure our decision-making regarding this dilemma.

In the previous blog, I introduced the famous CAP Theorem (please give it a read if you haven’t already before you start reading this one). It involves a trilemma of needing to give up one of the following three qualities: consistency, availability, and partition tolerance. Since all three are desirable features of modern-day distributed systems, determining which one to relinquish has become one of the most important and delicate decisions for designers of complicated distributed systems. While the CAP Theorem is widely-known in computer science, its extension, the PACELC theorem, has received less attention. Today, I will shine a long-overdue spotlight on the PACELC theorem.

The world that we live in is far from perfect. We constantly find ourselves in dilemmas, sometimes even trilemmas, that require us to make trade-offs. When shopping, we can only choose two out of “cheap,” “fast,” and “good.” In economics, a government cannot enjoy “sovereign monetary policy,” “fixed exchange rate,” and “free capital flow” at the same time. It can only achieve two of them by giving up the third. Similarly, the CAP (consistency, availability, and partition tolerance) theorem involves an equally head-scratching trilemma that has troubled computer scientists and software engineers ever since distributed computing became a popular solution to large-scale computation. Today, we will dive deep into the CAP theorem and learn how to make wise trade-offs based on our needs.

There’s no denying that we have already ushered in the era of big data. An enormous amount of information is generated every second. While decision-makers can gain invaluable insights from this ever-growing data, its sheer volume also poses considerable challenges to data engineers–greater demand for storage spaces, the need to handle increasingly complex data formats, and highly unpredictable network traffic. Luckily, recent years have witnessed the creation of various technologies devoted to efficiently digesting big data, and Kafka is one of them. Today, I will demonstrate how Kafka works to help kick-start your Kafka journey.

As a data engineer, you probably have heard about Hadoop. It is one of the most popular frameworks for distributed processing of large data sets. It is less costly and more secure than other frameworks. At its center is a programming model called MapReduce. Today we will take a closer look at MapReduce to understand the inner working of Hadoop.

As a data engineer, you probably have heard of the data integration methodology called ETL (Extract-Transform-Load). It has been around for a while, and many data engineers have used this methodology to build data pipelines. However, ETL is not the only option up our sleeves. Recently, ELT has also been gaining a lot of popularity. In this article, I will compare ETL and ELT to help you understand their respective advantages and drawbacks so that you can choose the methodology more suitable for your project.