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Overview

Challenges in setting up environments for engineers

Introduction​

Setting up a personal or professional software environment can be daunting, especially when dealing with tools like zsh, micromamba, Singularity, and SLURM. Each field—data engineering, software engineering, and bioinformatics—comes with its own set of challenges in configuring these tools efficiently.

Common Challenges​

1. Dependency Management​

  • Software often requires multiple dependencies that may conflict with one another.
  • Package managers like micromamba and conda help, but ensuring compatibility across different packages can be tricky.
  • Dependency resolution in Singularity containers must account for both system libraries and containerized environments.

2. System Compatibility​

  • Different operating systems (Linux, macOS, Windows) require different installation methods and configurations.
  • Some tools (e.g., SLURM) are designed for Linux-based HPC environments, making local testing on macOS or Windows difficult.
  • Ensuring compatibility across clusters and local machines requires effort.

3. Shell Environment Customization (zsh)​

  • Working with remote server, it is quitely painful when you type on the terminal
  • Want to reuse the old command
  • If you want to develop software on the remote server, a git respository does not show branch
  • Sometimes you make a small typo for a command but you do not known what is wrong with it

4. Containerization and Virtualization (Singularity)​

  • Building reproducible containers that include all necessary dependencies.
  • Managing user permissions when running Singularity in HPC environments.
  • Ensuring compatibility between different host systems and containerized applications.

5. Export the web service on the HPC to access on your local network automatically (SLURM)​

  • You want run a web service or a notebook on the HPC
  • You want to share the running service

Conclusion​

Setting up a software environment is a non-trivial task that requires deep knowledge of system configurations, dependency management, and performance tuning. Each engineering field faces unique challenges, but with proper planning, automation, and documentation, it is possible to create a stable and efficient working environment. As a result, with standard setup, I create the river-utils which helps to solve the above issue. Beside, it also works with the riverxdata platform where it helps to work with data on hydrid computing resources.