Erlang Ecosystem Foundation
Supporting the next generation of advanced, reliable, realtime applications
The Erlang Ecosystem Foundation is a 501(c)(3) not-for-profit organization supported by over 750 members who embrace its collaborative Working Group model, and community-building events.
Our members include industry leaders who are dedicated to furthering state of the art for Erlang, Elixir, LFE and other technologies based on the BEAM.Join Now →
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What does the Erlang Ecosystem Foundation do?
In order to meet the needs of the ecosystem, the ErlEF sponsors Working Groups to solve specific challenges faced by users of BEAM technology. Areas of particular interest include documentation, interoperability, and performance.
To evolve the tools in the ecosystem related to building, documenting, and deploying code, with a strong focus on interoperability between BEAM languages.Learn More →
Facilitate, evolve education and training and consolidate educational material(s) for all BEAM languages and the BEAM itself.Learn More →
Standardize, improve, and promote the APIs, tooling, and infrastructure for building embedded systems and IoT devices usingErlang VMsLearn More →
External Process Communication, Interoperability and RobustnessLearn More →
To formally nominate community members for a fellowship role according to the Erlang Ecosystem Foundation bylaws. Creating and maintaining the criteria and procedure for nomination of fellows.Learn More →
Facilitate the reuse of software components that target the Erlang Runtime.Learn More →
To expand awareness of Erlang Ecosystem and participation in its community. To promote the Erlang Ecosystem Foundation and its activities, and to increase engagement in the foundation.Learn More →
To evolve the tools in the ecosystem related to observability, such as metrics, distributed tracing and logging, with a strong focus on interoperability between BEAM languages.Learn More →
The mission of the Security Working Group is to identify security issues, and provide solutions, develop guidance, standards, technical mechanisms and documentation.Learn More →
To develop the ecosystem on all aspects in the context of Machine Learning, from native compilation to high-level abstractions and auxiliary projects.Learn More →