Run KUTTL in Zuul #64
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@@ -82,7 +82,7 @@ endif | |
| # Be aware that the target commands are only tested with Docker which is | ||
| # scaffolded by default. However, you might want to replace it to use other | ||
| # tools. (i.e. podman) | ||
| CONTAINER_TOOL ?= podman | ||
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There was a problem hiding this comment. 🎯 Functional Correctness | 🟠 Major | ⚡ Quick win 🧩 Analysis chain🏁 Script executed: #!/bin/bash
set -euo pipefail
image="docker.io/library/alpine:3.20"
podman pull "$image"
if docker image inspect "$image" >/dev/null 2>&1; then
echo "Docker and Podman share image visibility on this runner."
else
echo "Docker cannot see the image pulled by Podman."
exit 1
fiRepository: openstack-k8s-operators/lightspeed-operator Length of output: 225 🏁 Script executed: #!/bin/bash
set -euo pipefail
printf '%s\n' '--- candidate files ---'
git ls-files | rg '(^|/)(Makefile|.*build-and-push.*\.ya?ml)$|\.github/workflows'
printf '%s\n' '--- container-tool references ---'
rg -n -C 4 'CONTAINER_TOOL|docker (build|tag|push)|podman (build|tag|push)|make (docker|bundle|catalog)' Makefile .github/workflows 2>/dev/null || trueRepository: openstack-k8s-operators/lightspeed-operator Length of output: 13010 🏁 Script executed: #!/bin/bash
set -euo pipefail
printf '%s\n' '--- workflow ---'
cat -n .github/workflows/build-and-push.yaml | sed -n '1,125p'
printf '%s\n' '--- Makefile build/push targets ---'
cat -n Makefile | sed -n '176,210p;382,442p'
printf '%s\n' '--- change summary ---'
git diff --stat
git diff -- Makefile .github/workflows/build-and-push.yaml | sed -n '1,180p'Repository: openstack-k8s-operators/lightspeed-operator Length of output: 9535 🌐 Web query:
💡 Result: GitHub-hosted runners using the ubuntu-latest label (currently Ubuntu 24.04 LTS) come with Podman pre-installed [1]. Runner Software and Podman: The standard GitHub-hosted ubuntu-latest runner includes a variety of container tools, including Podman, Buildah, Skopeo, Docker, and Docker Compose [1]. While Podman is available on these images, it is important to note that the default container runtime used by GitHub Actions for job isolation and service containers is Docker [2][3]. Using Podman in Workflows: You can use Podman directly in your workflow steps by calling the podman command (e.g., podman build, podman push) [4]. Because Podman is daemonless and rootless-capable, it functions differently than the standard Docker-in-Docker setup [2][5]. Key Considerations: 1. Compatibility and Hooks: GitHub Actions does not natively replace its internal Docker-based runner execution with Podman [2]. To use Podman as the primary runtime for container actions (e.g., the container: keyword in a job), you would need to implement custom Runner Container Hooks, which allow you to override the default Docker-based container lifecycle management [2][3]. 2. Storage and Docker-in-Docker: Standard workflows that rely on Docker-in-Docker (using the Docker socket at /var/run/docker.sock) are designed for the Docker daemon [2][3]. While you can use Podman to interact with the local Docker daemon (e.g., using the docker-daemon: transport), users have previously encountered compatibility issues when versions of Podman and the Docker daemon/API do not align [6]. 3. Official Documentation: GitHub's official documentation focuses on the environment specifications of the runners (e.g., available tools and hardware) [7] but does not provide official, supported guidance for migrating the runner's native container runtime from Docker to Podman [2]. Custom implementations for such migrations are community-driven [5][3]. In summary, while Podman is pre-installed and available for use within your CI/CD steps, the underlying runner infrastructure remains architected around Docker. Advanced use cases requiring Podman to handle the full container execution lifecycle require custom configuration via Runner Container Hooks [2][3]. Citations:
🌐 Web query:
💡 Result: Podman and Docker do not share image storage and operate independently, as they are distinct container engines with different architectures [1][2][3]. Podman is a daemonless container engine [4][5], while Docker relies on a centralized, root-privileged daemon [1][6]. Because of these fundamental differences in architecture and management, they maintain separate, non-overlapping image repositories [2][7]. Key details regarding their separation: 1. Different Default Storage Locations: - Docker: Typically stores images in /var/lib/docker/ [6][8]. - Podman (Rootful): Typically stores images in /var/lib/containers/storage/ [9][10]. - Podman (Rootless): Typically stores images in $HOME/.local/share/containers/storage/ [9][8][10]. 2. Lack of Native Sharing: Because they use separate storage paths and management mechanisms, images pulled or built by one engine are not natively visible or accessible to the other [2][7]. If you run the command podman images or docker images, you will only see the images managed by that specific engine [2][7]. 3. Interoperability via Transport: While they do not share a storage directory, Podman can interact with the Docker daemon's storage indirectly using the docker-daemon transport [11][7]. For example, you can run an image stored in the Docker daemon using the following syntax: podman run docker-daemon:docker.io/library/image_name [11][7] This command pulls the image out of the Docker daemon's storage, copies it into Podman's local storage, and then runs the container [7]. Similarly, images can be moved between them using tools like docker save and podman load [2]. For developers working in environments where both are installed, they can coexist without conflict because they use separate sockets and storage paths [6][2][3]. However, they remain distinct and independent systems [1][2]. Citations:
Use one container runtime in the build workflow. When the workflow uses the new default, 🤖 Prompt for AI AgentsSource: Path instructions |
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| # Setting SHELL to bash allows bash commands to be executed by recipes. | ||
| # Options are set to exit when a recipe line exits non-zero or a piped command fails. | ||
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🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
🧩 Analysis chain
🏁 Script executed:
Repository: openstack-k8s-operators/lightspeed-operator
Length of output: 234
🏁 Script executed:
Repository: openstack-k8s-operators/lightspeed-operator
Length of output: 1475
🌐 Web query:
Zuul irrelevant-files regular expression matching semantics re.match file names💡 Result:
In Zuul, the irrelevant-files matcher (as well as the files matcher) uses the RE2 regular expression library [1][2][3]. Regarding matching semantics, Zuul regular expressions for these options behave as if there is an implicit ^ anchor at the beginning of the string [1][4][2]. This means the pattern must match the start of the file path [1][4]. To match at an arbitrary position within the file path, you must explicitly prepend.* to your regular expression [1][4][3]. Zuul moved away from standard Python regular expression matching (which historically might have been used in older versions) to the RE2 library to ensure speed and safety [5][6][7]. Because RE2 is used, backreferences are not supported [6][8]. If you need to perform a partial match or search for a pattern anywhere in the file path, simply using the pattern without anchors will not work as it does in some other contexts; you must account for the implicit start-of-string anchor [1][2].
Citations:
Restrict the irrelevant-file pattern to Markdown files.
.*/*.mdmatches thecmdprefix ofcmd/main.go, so a source-only change can skipopenstack-operator-kuttl. Use^.*\.md$instead.🤖 Prompt for AI Agents