More Signal, Less Noise: How GitHub Issue Reactions Help Prioritize
Did you know that OpenTelemetry has had more than 23,000 contributors—that’s individuals who shared issues, commits, pull requests, or comments on GitHub—since the project started? We always encourage everyone to get involved, whether that’s by joining one of our (many!) CNCF Slack channels, or dropping into any public meeting to listen in and share different perspectives. This openness is one of our greatest strengths, but it also means we get a firehose of feedback via many different routes: GitHub, Slack, StackOverflow, meetings, and even posts on social media.
As someone who is active in the project and works with end-users daily, I see both sides of the contribution coin. Users file GitHub issues hoping to get a bug fixed or a feature built, and maintainers sift through a mountain of notifications trying to figure out where to best spend their limited time. To give you an idea of the scale, in 2024 alone, the number of GitHub issues closed across the project was over 7,000!
With such an active project, one of the biggest challenges has always been understanding what’s the most important thing to focus on, as seen by OpenTelemetry users and contributors. And, when we consider GitHub issues, a stream of “+1” or “me too!” comments does not make this any easier. While the sentiment is valuable, the method creates a lot of noise and makes it more difficult for maintainers to gauge how many people are really affected by an issue.
We want to make this easier for everyone. That’s why, as part of the End-User SIG, we’ve been working on a small but important change to how we use GitHub: promoting the use of 👍 issue reactions as the primary way to express interest.
A Better Signal to Help Prioritize
The goal here is simple: provide a clear, low-effort, data-driven way for the community to signal what matters most. For maintainers, this system cuts through the notification noise. They can sort issues by reaction count to get a quick, at-a-glance view of what the community is clamoring for. This helps SIGs and maintainers make more informed decisions when prioritizing their backlogs.
For you, the end-user, it means your feedback is more visible. Instead of your “+1” comment getting lost in a long thread, your 👍 becomes a quantifiable piece of data that helps give the issue more weight.
To make this change stick, we’ve rolled out a few things. We’ve published recommendations for OpenTelemetry maintainers on how to manage and interpret these reactions, and our website now has a section explaining what this means for end-users. You’ll also see a friendly reminder in a new footnote on issue templates across all OTel repositories. If you’re opening a new issue, please leave that footer in place so that others have first-hand access to this advice.
Your Quick Guide to Making an Impact
So what does this mean for you in practice? It’s easy.
The next time you’re browsing issues, don’t just read and leave. When you find an issue that describes a problem you’re also facing or a feature you’d like to see implemented, just give the issue description a 👍 reaction. That’s it. Like and subscribe. That’s the signal.
Of course, if you have a new, unique use case, a technical detail that hasn’t been mentioned, or other information that would help a maintainer solve the problem, then please do leave a comment. That kind of context is incredibly valuable! Just remember that a high reaction count is a strong signal, but it doesn’t automatically guarantee an issue becomes the top priority.
Open source is a team sport, and this is a perfect example of how small actions can collectively have a huge impact.
Thanks for helping us make OpenTelemetry better, together.