Overview
The E4S community provides multiple ways for developers, users, and contributors to connect, collaborate, and stay informed. The primary communication channels include the E4S Slack workspace, GitHub Discussions, and issue tracking via E4S GitHub repositories. These venues enable open and inclusive participation across the scientific software ecosystem.
Join the E4S Slack Workspace
| Step |
Description |
| Purpose |
The E4S Slack workspace provides real-time communication among developers, maintainers, and users. It is an informal, collaborative environment for asking questions, sharing updates, and coordinating across E4S projects. |
| Access |
The Slack workspace is open to anyone involved in or interested in the E4S community. |
| How to Join |
Visit the E4S website at https://e4s.io and navigate to the Join section. There you will find an invitation link to the E4S Slack workspace. |
| Channels |
Common channels include #general, #releases, #spack, #performance-tools, #programming-models, and others that correspond to E4S product families and working groups. |
| Conduct |
Participants are expected to follow the E4S community code of conduct and maintain a collaborative, respectful environment. |
Participate in GitHub Discussions
| Step |
Description |
| Purpose |
GitHub Discussions serve as a forum for asynchronous conversation about E4S-wide topics, proposals, and community coordination. It provides a structured place for technical and strategic discussions outside of the issue tracker. |
| Access |
Discussions are public and open to anyone with a GitHub account. You do not need to be an E4S developer to participate. |
| How to Join |
Navigate to the E4S Organization Discussion Forum linked from the E4S website or the main E4S GitHub organization. Discussions are typically hosted in a repository such as e4s-project/community or a similarly named repository dedicated to cross-project discussions. |
| Typical Topics |
Common discussion categories include roadmap planning, product integration, community events, and questions about contributing. |
| Guidelines |
Before posting, search existing discussions to avoid duplication. Keep threads focused and constructive. |
Submit Issues to E4S Repositories
| Step |
Description |
| Purpose |
GitHub Issues are used to track bugs, requests, and proposed improvements across the E4S suite of repositories. |
| Main Repositories |
The primary repositories for issues are e4s-project/e4s for the E4S release bundle and e4s-project/e4s.github.io for the website. |
| E4S Product Issues |
For issues specific to individual products, users are encouraged to submit issues directly to that product’s repository. Each E4S package entry in the E4S Product Catalog links to its source repository. |
| How to Submit |
Visit the appropriate repository on GitHub and click on the Issues tab. Review existing issues to check for duplicates before opening a new one. Use templates provided to categorize the issue (bug, feature, documentation, etc.). |
| Expectations |
Provide clear descriptions, relevant logs, and version information. The E4S integration team and product maintainers will triage and respond to new issues as part of the continuous integration and release cycle. |
Getting Help
| Resource |
Description |
| Slack |
For informal and interactive help, join the Slack workspace. |
| GitHub Discussions |
For design questions, proposals, or long-term ideas, start or reply to a GitHub Discussion. |
| GitHub Issues |
For bugs, errors, or requests tied to specific repositories, open a GitHub Issue. |
| Website Contact |
For general inquiries or assistance joining any communication channel, visit the contact page at https://e4s.io/contact or email the E4S coordination team listed there. |
Summary
E4S welcomes participation from the broader community of software developers, facility staff, and users of scientific software. Whether through Slack conversations, GitHub Discussions, or issue submissions, every contribution strengthens the ecosystem and supports the mission of open, collaborative, high-performance computing for science.