backend.ai

In this post, I'll share my experience as a developer at Lablup over the past 9 months.

Table of Contents

• Motivation to apply
• From Intern to DevOps!
• rraft-py Development
• Open Source Contribution Academy Regional Sprint Backend.AI Mentoring
• Attending various conferences
• 2023 Open Source Contribution Academy
• Presenting at PyCon
• Conclusion

Motivation to apply

Even before I joined Lablup, I knew that I wanted to have a career where I could continue to help others through the programs I develop, whether as a hobby or during work hours.

Open source was particularly appealing to me because it meant that not only could my code help others, but that they could freely modify and utilize it if they wanted to.

One of the things I realized after working on my own project, Arvis, for my graduation project, is that it's not really easy to keep a project going simply because it's something I love to do, as it keeps growing in size. I tried to plan and execute the project carefully from the beginning, but in the end, I realized that I underestimated the time and effort required to maintain the project.

In that regard, Lablup, which actively encourages and supports open source-related activities and even develops core parts of its source code as open source, was the company of my dreams.

From Intern to DevOps!

The last three weeks of My internship at OSSCA Lablupwere spent studying and researching distributed systems, specifically implementing the Raft algorithm. Although my job title changed from intern to DevOps, I still felt like I was expanding on my internship learning, including Raft, to solve issues I worked on during my internship.

I've been involved in a variety of other activities that I'll mention below, but my main work at the company to date has been writing a Python binding of the Raft algorithm implementation to replace the existing distributed lock structure, including writing rraft-py, and thinking about how to integrate it with Backend.AI.

rraft-py Development

rraft-py is a Python binding implementation of tikv/raft-rs, and you can read more about it in the GitHub Readme / Wiki. I'll also be presenting some technical details on the topic in my PyCon 2023 KR talk next month, if you're interested.

For now, I'm going to focus on my experience as a Lablup developer, leaving aside the technical details of what I learned while developing rraft-py.

I had to think a lot about rraft-py because it was not just about fixing an issue in Backend.AI, but also about creating a separate project and integrating that project with Backend.AI.

Overall, there were several mile stones in the project, and I feel like I was able to move forward with the project with a little more stability after each mile stone. There was definitely a high sense of accomplishment each time, but there were also many times when I was frustrated because I realized later that the code I had initially written didn't work the way I intended. But Lablup allowed me the time to do these shoveling sessions, and I think I've gotten to where I am today because of the things I've learned that I would have otherwise dismissed as "shoveling".

Results of running the rraft-py example code

There's still a long way to go to integrate rraft-py into Backend.AI, but the bottom line is that it's great to have the experience of thinking for yourself and making your own decisions as you continue to evolve your project, and for developers who like this kind of experience, Lablup could be one of the best options out there.

Open Source Contribution Academy Regional Sprints Backend.AI Mentoring

While rraft-py development was my main focus, as it required more time than I had anticipated, I also had the opportunity to work on a variety of other projects.

One of the most memorable experiences was participating in the 1st Daegu Open Source Contribution Academy Regional Sprint as a Backend.AI mentor.

In fact, I participated as a mentor without a deep understanding of Backend.AI, and to make matters worse, the sprint period was only 2 days, so I was worried about many things.

In order to make sure that the mentees learn at least one thing and go home as satisfied as possible, I had to think about how to explain Backend.AI to those who don't know it at all, and how to build a development environment on different platforms (personally, I usually only develop on macOS + docker desktop environment, but some of the mentees were working on Windows environment, so I had to shovel while building the development environment). I had to think about a lot of things and prepare.

In conclusion, I was able to learn a lot more than I thought because I was unfamiliar with these processes, and the mentees followed along better than I thought, so I think it was a meaningful time for everyone to create more than one PR.

The 1st Daegu Open Source Contribution Academy Regional Sprint

Participation in various conferences

We had the opportunity to participate in various conferences and exhibitions such as AI Expo, AWS Summit, and Next Rise. It was great to learn how to explain Backend.AI to different types of people, and it was also interesting to see the different technologies of other companies.

AI EXPO KOREA 2023

2023 Open Source Contribution Academy

As a company with an open source culture, Lablup actively participates in the Open Source Contribution Academy every year. This year, I also participated in the Open Source Contribution Academy, which encourages participation in various other projects besides the Backend.AI team, so I've been working on GlueSQL as a mentee.

I think this culture of freedom is very attractive to developers with a strong desire to grow.

(In addition to myself, there are two other people involved in other projects in the 2023 Contribution Academy).

PyCon announcement

Based on my experience in developing rraft-py at my company, I was also given the opportunity to present at 2023 PyCon KR.

Personally, I'm a bit nervous because it's my first time presenting in public, but I'm doing my best to prepare. For those who are interested in presenting, I am looking forward to sharing not only the presentation materials but also the source code and work history through GitHub.

Conclusion

Lablup is a company with a strong open source culture, encouraging participation in various open source and community-related events such as the Open Source Contribution Academy (https://www.oss.kr/contribution_academy) and PyCon, and giving developers the opportunity to take initiative in their work.

I hope to continue to participate, learn, grow, and contribute to open source activities of various nature at Lablup.

This post is automatically translated from Korean