---
name: container-orchestration-verification
description: Use when when a software tool is distributed as a Docker image and you need to confirm it is available on a registry (e.g., Docker Hub), that the image pulls without corruption, and that the application's entry point (help command, version output, or interactive shell) is accessible and responsive.
license: CC-BY-4.0
metadata:
  edam_operation: http://edamontology.org/operation_3443
  edam_topics:
  - http://edamontology.org/topic_0769
  tools:
  - R
  - Docker
  - tima
derived_from:
- doi: 10.3389/fpls.2019.01329
  title: tima
evidence_spans:
- The initial work is available at <https://doi.org/10.3389/fpls.2019.01329>
claims: []
provenance:
  collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v1
  assembled_by: scripts/collect_metabolomics_collection.py
  sources:
  - build: coll_tima
    doi: 10.3389/fpls.2019.01329
    title: tima
  dedup_kept_from: coll_tima
schema_version: 0.2.0
---

# container-orchestration-verification

## Summary

Verify that a containerized software environment (Docker image) successfully pulls, launches, and executes its entry point without errors. This skill confirms reproducibility and functional integrity of the containerized workflow before committing to full analysis runs.

## When to use

When a software tool is distributed as a Docker image and you need to confirm it is available on a registry (e.g., Docker Hub), that the image pulls without corruption, and that the application's entry point (help command, version output, or interactive shell) is accessible and responsive. Use this before running large analyses to catch environmental or dependency failures early.

## When NOT to use

- The software is not distributed as a container image; use native package installation or source compilation workflows instead.
- Docker daemon is not available or not permitted in your environment; fall back to native installation or request container access.
- You only need to verify the availability of the image on the registry, not its functional integrity; a registry API query is sufficient and faster.

## Inputs

- Docker image registry URL (e.g., Docker Hub image reference)
- Docker daemon (locally running or accessible via socket)

## Outputs

- Confirmation of successful image pull
- Exit code and stdout/stderr from entry-point command
- Running container instance (if left running for further checks)

## How to apply

Pull the Docker image from its registry using `docker pull` with the full image reference (e.g., `adafede/tima-r`). Launch a container instance from the pulled image using `docker run` with appropriate memory and volume bindings if needed. Execute a lightweight command within the running container—such as a help or version flag—to confirm the entry point is accessible and functional. If the command succeeds without error, the container environment is verified. This approach avoids the cost of a full workflow execution while catching missing dependencies, network issues, or image corruption.

## Related tools

- **Docker** (Container runtime and orchestration engine used to pull, build, and run container images) — https://www.docker.com
- **tima** (Example containerized application (R package for metabolite annotation) whose Docker image (adafede/tima-r) serves as the subject of verification) — https://github.com/taxonomicallyinformedannotation/tima

## Examples

```
docker pull adafede/tima-r && docker run --user tima-user --memory="12g" adafede/tima-r tima --version
```

## Evaluation signals

- docker pull command exits with status 0 and image appears in local image list
- docker run launches a container without errors and does not immediately exit with non-zero status
- Entry-point command (e.g., tima help, version, or interactive shell) produces expected output (help text, version string, or prompt) and exits cleanly
- Container does not report missing dependencies or library linking errors in stderr during launch or command execution
- Container logs or stdout include no error messages, warnings about unmet requirements, or segmentation faults

## Limitations

- This skill verifies functional integrity at the container entry point only; it does not test full end-to-end workflows or data processing correctness.
- The test command (help, version) may succeed even if critical downstream dependencies or data resources are missing; more thorough smoke tests (e.g., running on example data) are recommended before production use.
- Docker daemon must be running and accessible; verification will fail in sandboxed or restricted environments (e.g., some HPC clusters) even if the image itself is valid.
- Image availability on a registry does not guarantee the image is compatible with your host OS or architecture; pulling an image for an incompatible platform (e.g., ARM64 on x86) will fail at runtime.

## Evidence

- [other] Pull the Docker image adafede/tima-r from Docker Hub, launch a container, and execute a help/version command: "1. Pull the Docker image adafede/tima-r from Docker Hub using docker pull. 2. Launch a container instance from the pulled image. 3. Execute a tima help or version command within the running container"
- [readme] Docker is the tool used for container orchestration in this workflow: "docker pull adafede/tima-r
# docker build inst/. -t adafede/tima-r --no-cache"
- [readme] The Docker image is available and documented in the README with launch instructions: "A container is also available, together with a small compose file. Main commands are below:

``` bash
docker pull adafede/tima-r"
- [other] Research question confirms the goal is to verify successful pull and launch without errors: "Does the tima Docker container (adafede/tima-r) successfully pull and launch without errors?"
- [other] The Docker image is available at a specific repository on Docker Hub: "A Docker image for tima is available at the repository adafede/tima-r on Docker Hub."