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AkôFlow is an open-source middleware for orchestrating and executing container-based scientific workflows across heterogeneous environments. It was originally developed within the e-Science Research Group at the Institute of Computing, Fluminense Federal University (UFF).
Although initially focused on Kubernetes-based workloads, AkôFlow has evolved to support general containerized execution across multiple infrastructures.
- Operating System: Linux, macOS or WSL2 (Windows Subsystem for Linux)
 - Docker: Install Docker
 - kubectl: Install kubectl
 - Kubernetes Cluster: One of the following:
- Kind (local)
 - Docker Desktop Kubernetes (enable Kubernetes in settings)
 - Cloud providers (e.g., EKS, GKE, AKS)
 
 
Run the following command to install AkôFlow:
curl -fsSL https://akoflow.com/run | bashAkôFlow will be available at http://localhost:8080.
To view the full documentation, click here.
AkôFlow Demonstration (In Portuguese)
- Kubernetes (public cloud providers: AWS, GCP, Azure, etc.)
 - Singularity (for local or HPC isolated execution)
 - SDumont supercomputer (LNCC - Brazil)
 
- D.Sc. Daniel de Oliveira — Research Advisor
 - Wesley Ferreira - @ovvesley — Maintainer - IC/UFF
 - Liliane Kunstmann - COPPE/UFRJ
 - Debora Pina - COPPE/UFRJ
 - Raphael Garcia — IC/UFF
 - Yuri Frota — IC/UFF
 - Marcos Bedo — IC/UFF
 - Aline Paes — IC/UFF
 - Luan Teylo — INRIA/Université de Bordeaux
 
- 
Ferreira, W., Kunstmann, L., Paes, A., Bedo, M., & de Oliveira, D. (2024, October).
AkôFlow: um Middleware para execução de Workflows científicos em múltiplos ambientes conteinerizados. In 39th Simpósio Brasileiro de Banco de Dados (SBBD) (pp. 27-39). SBC. (DOI:10.5753/sbbd.2024.241126.) - 
Ferreira, W., Kunstmann, L., Garcia R., Bedo, M., & de Oliveira, D. (2025, October). Plug and Flow: Execução de Workflows Científicos em Contêineres com o Middleware
AkôFlow. In 40th Simpósio Brasileiro de Banco de Dados (SBBD). (Paper just accepted) 
AkôFlow originated as a final undergraduate project and has since expanded with broader contributions and integrations. It continues to serve both academic and industrial workflow execution scenarios.