Container Image Build And Deployment

---
name: container-image-build-and-deployment
description: Use when you have a Dockerfile and source repository for a bioinformatics
  tool (e.g., CloMet) and need to verify that the tool can be containerized, deployed,
  and made executable in an isolated environment.
license: CC-BY-4.0
metadata:
  edam_operation: http://edamontology.org/operation_3443
  edam_topics:
  - http://edamontology.org/topic_3572
  - http://edamontology.org/topic_0091
  tools:
  - Docker
  techniques:
  - NMR
  license_tier: open
  provenance_tier: literature
derived_from:
- doi: 10.1021/acs.jproteome.2c00602
  title: CloMet
evidence_spans: []
claims: []
provenance:
  collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v2
  assembled_by: scripts/collect_metabolomics_collection.py
  sources:
  - build: coll_clomet_cq
    doi: 10.1021/acs.jproteome.2c00602
    title: CloMet
  dedup_kept_from: coll_clomet_cq
schema_version: 0.2.0
attribution:
  generator: AgenticScienceBuilder
  original_doi: 10.1021/acs.jproteome.2c00602
  all_source_dois:
  - 10.1021/acs.jproteome.2c00602
  zenodo_doi: 10.5281/zenodo.20794027
  curators: []
  promoter: Louis-Félix Nothias
  sponsor: CNRS & Université Côte d'Azur
---

# container-image-build-and-deployment

## Summary

Build and deploy a containerized bioinformatics tool (CloMet) using Docker to establish a reproducible, isolated runtime environment for NMR-based metabolomics data harmonization. This skill ensures first-time users can reliably instantiate the tool across different operating systems without dependency conflicts.

## When to use

You have a Dockerfile and source repository for a bioinformatics tool (e.g., CloMet) and need to verify that the tool can be containerized, deployed, and made executable in an isolated environment. This skill is appropriate when distributing software that must run consistently across heterogeneous host systems or when you need to validate that all tool dependencies are correctly declared and bundled.

## When NOT to use

- The tool is already available as a pre-built, verified image in a public registry (e.g., Docker Hub); proceed directly to deployment.
- You do not have permission to install Docker or cannot use containerization technology on your system.
- The source repository lacks a Dockerfile or equivalent container specification; build instructions must first be authored and tested.

## Inputs

- Dockerfile (container build specification)
- Source code repository (e.g., GitHub repository URL)
- Docker installation for the target operating system

## Outputs

- Built Docker image (tagged and stored in local or remote registry)
- Running container instance with mounted volumes
- Verification output from tool help/version command

## How to apply

Follow a five-step workflow: (1) install Docker for your target operating system via the official Docker installation procedure; (2) clone the source repository (e.g., github:rmallol__clomet); (3) build the Docker image by running `docker build` against the provided Dockerfile; (4) deploy and run the container with appropriate volume mounts to verify initialization without errors; and (5) execute an initial command (e.g., help, version check) within the running container to confirm tool functionality and CLI accessibility. Success is confirmed when the container starts cleanly and the tool responds to diagnostic commands.

## Related tools

- **Docker** (Container runtime and build system used to construct and execute the isolated CloMet tool environment)

## Examples

```
docker build -t clomet:latest . && docker run --rm -v $(pwd):/data clomet:latest clomet --help
```

## Evaluation signals

- Docker image builds successfully without errors and is tagged in the local Docker image repository.
- Container starts without fatal errors when invoked with `docker run` and appropriate volume mounts.
- Tool help or version command executes within the running container and returns expected output (e.g., usage text or version string).
- Mounted volumes are accessible from inside the container and data can be read/written with correct permissions.
- Container process runs stably and exits cleanly when tool commands complete or when the container is stopped.

## Limitations

- The provided article does not specify operating system–specific Docker installation differences; users must adapt installation steps for their platform (Linux, macOS, Windows).
- No changelog is available in the repository, making it difficult to track breaking changes between versions or identify backward compatibility concerns.
- The First Steps diagram is referenced but visual instructions cannot be parsed from the README text; users must access the GitHub web interface to view step-by-step guidance.

## Evidence

- [readme] Follow these steps to install Docker and run CloMet for the first time: "Follow these steps to install Docker and run CloMet for the first time"
- [other] 1. Install Docker following the official installation procedure for the target operating system. 2. Clone the CloMet repository from github:rmallol__clomet. 3. Build the CloMet Docker image from the provided Dockerfile. 4. Run the CloMet container with appropriate volume mounts and verify that the containerized tool starts without errors. 5. Execute an initial CloMet command (e.g., help or version check) to confirm the tool is functional and accessible within the container.: "Install Docker following the official installation procedure for the target operating system. Clone the CloMet repository from github:rmallol__clomet. Build the CloMet Docker image from the provided"
- [readme] CloMet eases the connection between public data repositories and data analysis platforms by harmonizing the file systems of available data sets, with a focus on NMR-based metabolomics: "CloMet eases the connection between public data repositories and data analysis platforms by harmonizing the file systems of available data sets, with a focus on NMR-based metabolomics"