GraphCanon updated 2w · GitHub synced 2w
Decision brief
MOE optimizes real-world metrics via automated black-box processes. It is written in C++.
Good fit when
- When you require an optimization engine that operates as a global, isolated system through Docker containers.
- For tasks demanding high performance and precision due to its foundation in C++.
Avoid when
- If your team lacks the knowledge or experience to configure and run Docker environments.
- Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios.
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Archived (1228d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- 15 low (15 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/YelpArchive/MOESimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
The repository contains a tool that optimizes real-world metrics through automated black-box optimization processes.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 4, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 4, 2026
- Languages
- c++
Source: github.language · Aug 4, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 4, 2026)
[9]: http://yelp.github.io/MOE/moe.optimal_learning.python.python_version.htmlSource link
Tags
README
Install in docker:
This is the recommended way to run the MOE REST server. All dependencies and building is done automatically and in an isolated container.
Docker (http://docs.docker.io/) is a container based virtualization framework. Unlike traditional virtualization Docker is fast, lightweight and easy to use. Docker allows you to create containers holding all the dependencies for an application. Each container is kept isolated from any other, and nothing gets shared.
$ docker pull yelpmoe/latest # You can also pull specific versions like yelpmoe/v0.1.0
$ docker run -p 6543:6543 yelpmoe/latest
If you are on OSX, or want a build based on the current master branch you may need to build this manually.
$ git clone https://github.com/Yelp/MOE.git
$ cd MOE
$ docker build -t moe_container .
$ docker run -p 6543:6543 moe_container
The webserver and REST interface is now running on port 6543 from within the container. http://localhost:6543
Install from source:
License
MOE is licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0
For agents
This page has a .md twin and JSON over the API.