Culture
Introduction
My first encounter with 'Lablup' was in the summer of 2019. At that time, I attended a GDG Seoul 'Everyone's Toy Story' event because someone I knew was presenting there. I had the opportunity to sit in on a presentation by Lablup about their GPU virtualization tools for machine learning, and that piqued my interest. At that time, my fascination with machine learning was at its peak, and the technical depth of their presentation was impressive—it was my introduction to a company pioneering in this field.
Subsequently, I reconnected with the company at the 42 Seoul open source hackathon. This was an event focused on developing a product using a designated open source within a limited timeframe, where I became a part of the Backend.AI team. Despite it being three years since the initial presentation at GDG Seoul, the impression it left was so profound that the company's name was instantly familiar to me. Throughout the contest, the guidance provided by Jungkyu (CEO of Lablup) was instrumental, contributing significantly to our achievement being a second place at a hackathon.
In May 2022, I was working on a school-based internship at a company called SATREC INITIATIVE. As my internship was drawing to a close, I came across an announcement for Lablup's summer internship on Facebook. Recalling the valuable mentorship from Mr. Shin during a competition, and with a keen interest in the developer community and open source, I chose Lablup as my next destination.
At that period, I was engaged in a project named 42 World, which was a significant phase of learning and growth for me. In my interview with Lablup, I detailed my experiences with the 42 World project, particularly the challenges I faced while implementing a MonoRepo. Interestingly, Lablup had encountered similar issues with MonoRepo in Backend.AI, allowing us to exchange a sense of empathy as developers during our conversation.
After being accepted into the Lablup internship, I started my internship with four other interns. I joined the company about a week later than the others to give myself time to finish my existing internship and relocate. My first week was dedicated to orientation, familiarizing myself with Backend.AI, and acclimating to the company's culture. The onboarding documentation was comprehensive, contributing to a welcoming environment for newcomers to quickly adapt. A significant portion of my orientation involved installing and configuring Backend.AI. Since I began a week after the other interns, they were able to assist me, which made the orientation process relatively smooth.
Getting to my work
During the second week, I began tackling the actual tasks. I opted to collaborate with the DevOps, Frontend, and Research teams. Each chapter leader provided me with a 'good-first-issue' to address. My choice was the DevOps team. My initial task involved refactoring the 'run' command, which initiates a session and runs the specified code. The goal was to integrate 'start', to launch the session, and 'exec', to execute the code, thereby minimizing redundant code.
I faced challenges with the first issue assigned to me as it required a thorough understanding of Backend.AI's repository structure, irrespective of the implementation difficulty. I realized that while it's important to know why an issue exists, it's also important to know exactly what Backend.AI is trying to accomplish and understand how the issue needs to be solved to achieve that goal so that I can solve it correctly.
After addressing the initial issue, I took on the task of testing a feature in development known as vfolder clone. My role was solely focused on DevOps, providing me with my inaugural experience with Backend.ai-webui, a Frontend chapter project. My involvement wasn't limited to just testing the vfolder clone; I also executed it personally, identifying areas for improvement and bugs, which I then documented as issues. This made me feel somewhat guilty, as it seemed I was generating work for other teams. However, the Frontend chapter's encouragement to contribute assuaged my concerns. This experience reaffirmed my understanding that open-source contributions extend beyond code; there are numerous ways to contribute.
Improving CI/CD
As I've always been interested in CI/CD, I was intrigued by the actions utilized in Backend.AI. At the time, Backend.AI could bypass CI with the skip:ci tag, but I noticed that neither skip:ci nor skip:changelog tags would work if the PR was labeled after creation, necessitating an extra commit. Since external contributors lack label permissions and Backend.AI is open source, resolving this seemed crucial. After exploring GitHub Actions, I discovered a trigger for labeling, which allowed me to address the issue. My proactive approach in finding and fixing problems independently, rather than through assigned tasks, was highly appreciated by the company. This experience deepened my interest in actions, leading to further enhancements. Noticing frequent omissions in assignments, I proposed the auto-auth-assign action for automation, which I had previously utilized. Subsequently, I considered automating the labeling process. Although new to the labeler action, I conducted multiple tests in a test repository before implementing it in Backend.AI, successfully automating the labeling of various systems integrated into a monolith. During this process, I identified the benefit of linking labels from issues to PRs. Unable to find an existing action, I took the initiative to create the auto-label-in-issue action, learning the GitHub API and action scripting in the process.
Finishing my Internship
This internship has been a significant learning experience for me. Although it's my second internship, it's my first within an IT company, as my previous employer wasn't in this sector. What draws me to Lablup is its commitment to open-source products and the active contributions to the community. The company's horizontal structure allowed me to freely share my thoughts, making me wonder if a company could really operate so collaboratively. One of the greatest aspects of Lablup is the autonomy it offers, allowing you to pursue what you're passionate about rather than what you're obliged to do.
Having developed a strong understanding of the project, I was disappointed when the internship neared its conclusion. Fortunately, Lablup offered me the opportunity to extend my internship, which I accepted, and continued to work on action issues. As there are few developers specializing in this area, I recently presented on the subject at GDG Daejeon. This led to the amusing nickname "Action Mask" from my colleagues.
I have shared my internship experience with the Open Source Contribution Academy, where I performed well. I believe that my experience at the company was the foundation for that.
