@techreport{TR-IC-PFG-23-66,
   number = {IC-PFG-23-66},
   author = {Ramon Galate Baptista Ribeiro and Edson Borin},
   title = {{A Framework for running DASF applications with Kubernetes
                   and Argo}},
   month = {December},
   year = {2023},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 48 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       The  present  report details the development of a framework for
       the   construction   of  self-  contained  pipelines  for  data 
       processing,  using  Dask  and  Argo for the generation of these
       pipelines.   This   structure  benefits  from  Dask  Kubernetes 
       Operator   for   adaptive   scaling,   automatically  adjusting 
       according to demand and complexity of tasks. Implemented on the
       Kubernetes   platform,   this  framework  ensures  scalability, 
       flexibility,  and  optimization  of  resources.  The system was
       designed  to  cater  to  a  wide  range  of applications, being
       especially  relevant in areas such as seismic data analysis and
       ETL (Extraction, Transformation, and Loading) processes. Thanks
       to   the   efficient  integration  between  Dasf,  Dask,  Argo, 
       RapidsAI, and Kubernetes, it is possible to handle workloads of
       various  sizes  and  intensities,  enhancing the processing and
       analysis  of  large  volumes  of data. In a scenario where data
       production  is  growing  exponentially, the need for robust and
       scalable solutions like this becomes essential. This project is
       an  important  step  towards scalable solutions, paving the way
       for  future  innovations  in  the  field  of  large-scale  data 
       processing.
  }
}