Awesome-runbook, the open-source project for runbook curation
Progress Updates & Retrospective
We recently took a big step by launching Runbear. It was an exciting milestone, but not without its challenges.
We encountered two primary issues. First, even with the assistance of our generative AI, users still found it challenging to create runbooks, exemplifying the cold start problem. Second, the low execution frequency of our service led to a high pain/gain ratio for our customers.
Looking back, we didn’t fully adhere to the working backward approach. The main takeaway is that we need to offer ready-to-use runbooks right from the start to ease the initial user experience.
Awesome Runbook Project
To address these issues, we initiated an “Awesome Runbook” project. The goals were to share our knowledge, build a community, and validate interest in runbooks. It took us half a day to set up a GitHub repository, refine it, and share it across various subreddits. The outcome? In just less than a week, our repository received 100 stars, mostly from Reddit, and even got featured in a newsletter. It has 173 stars as of now.
We learned two vital lessons. First, working backward is challenging but essential. Second, goodwill-based projects resonate with people. As we advance, we plan to launch Awesome Runbook on Product Hunt, refine our list, and integrate this content into Runbear to create a more cohesive experience.
By focusing on these areas, we aim to alleviate the initial hurdles for our customers and make Runbear more user-friendly and valuable.
Closing Thoughts
We’ve navigated through some growing pains since our launch but have emerged wiser. We plan to keep iterating and fine-tuning Runbear, guided by our learnings and future strategies.
In summary, while challenges lie ahead, we’re optimistic about Runbear’s trajectory and the valuable lessons we’ve learned on this journey.
Cheers, and Run, Bear, Run!
