Search

More Filters

Show More
Add Listing
Go Back

OpenDerisk

0
New
Multi-Agent Platforms & Frameworks
Report

Report Abuse

Basic Information

OpenDeRisk is an open-source AI-native risk intelligence system designed to perform continuous, in-depth diagnosis and management of application and infrastructure risks. The repository provides a multi-agent architecture that coordinates specialized digital employees such as SRE-Agent, Code-Agent, ReportAgent, Vis-Agent, and Data-Agent to analyze logs, traces, and code and to perform root cause analysis. It is intended to be run locally or in development environments using the provided startup flow: sync packages with the uv tool, configure an API key and a local copy of the OpenRCA dataset (around 20–26GB), and run the Python server to access a browser-based UI. The project emphasizes an open architecture so components and frameworks can be reused or extended in other open-source projects. Roadmap items show incremental goals toward MCP services, production integration, and end-to-end agentic evaluation.

Links

Stars
604
App URL
https://github.com/derisk-ai/OpenDerisk
Github Repository
https://github.com/derisk-ai/OpenDerisk/blob/main/README.md

Categorization

App Details

Features
The README highlights several main features: DeepResearch RCA for automated, model-driven root cause analysis across logs, traces, and code; a Visualized Evidence Chain that renders the diagnostic process and supports judgment of accuracy; Multi-Agent Collaboration enabling role-based coordination among SRE-Agent, Code-Agent, ReportAgent, Vis-Agent, and Data-Agent; and an open, extensible architecture. The technical design is layered into Data, Logic, and Visualization layers. The Code-Agent can dynamically generate code for final analysis. The system uses the open OpenRCA dataset as its primary training/test corpus and the Vis protocol to render processing flows and evidence chains. Quick start scripts and package sync instructions are provided to bootstrap the system.
Use Cases
OpenDeRisk helps site reliability engineers, DevOps teams, and developers accelerate fault diagnosis and remediation by automating deep investigations that would otherwise require manual triage. The multi-agent setup breaks complex troubleshooting into specialized roles, enabling parallel analysis, evidence aggregation, and visual presentation of findings. Visualized evidence chains and reports make it easier to verify diagnoses and track how conclusions were reached. The project also aims to support automated troubleshooting and fixes, a domain knowledge engine, and MCP services in future releases, which would reduce mean time to resolution in operational environments. Being open-source, it allows teams to adapt components, extend agents, and integrate the system with existing toolchains.

Categories

Content Creation (5042)
Monetization & Business (2246)
Development Tools (1407)
Marketing & Social Media (1403)
Education & Career (1380)
Multi-Agent Platforms & Frameworks (1009)
Health & Life (957)
AI Resources (920)
Agents & Automation (778)
Data & Analytics (764)
Productivity Tools (679)
Writing & Editing (666)

Similar Listings

listing image

virtual lab

0 (0 review)
listing image

mnemo

0 (0 review)
listing image

EdgeChains

0 (0 review)
listing image

RAG Agents Accelerator

0 (0 review)
listing image

LLM Zero to Hundred

0 (0 review)

Featured Listings

Tags

Please fill the required fields*