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Process
In general, the process to build a multiplatform-cpu architecture agnostic container image follows the flow depicted on the following figure.
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| Gliffy Diagram | ||||
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Example using a Python Micro-Service
Main steps
The following diagram captures the main steps we need to take to enable multiplatform-cpu architecture agnostic containers:
(1) and (2) Build and push container images for each cpu-architectureplatform.
(3) Create and push a manifest list for the images above
(4) Pull and run the exact same image/tag on different cpu architecturesplatforms.
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Manifest List and Image Layers
Digging a little bit deeper into step (4), the following diagram shows the relationship between a manifest list and image manifests for our multiplatform-cpu architecture agnostic image (tag).
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The following sections describe the commands needed to create a multi-cpu architecture container image. Let's call the image onap/py-app.
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For the release process, the flow will implemented using CI/CD pipelines as shown in the next section.
Source code
Code structure
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. ├── app │ ├── main.py │ └── requirements.txt └── Dockerfile |
Python App
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from flask import Flask
import platform
app = Flask(__name__)
@app.route("/")
def hello():
return "Hello ONAP. I am a Python service running on " + platform.machine()
if __name__ == "__main__":
app.run(host='0.0.0.0', debug=True, port=5000)
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Requirements
| Code Block |
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Flask==0.10.1 |
Dockerfile
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FROM python:2.7-alpine LABEL maintainer="adolfo@orangemonk.net" # Keep it simple COPY ./app /app WORKDIR /app RUN pip install -r requirements.txt ENTRYPOINT ["python"] CMD ["main.py"] |
Build arm image (A)
Log into an arm server, copy the code into the structure depicted above.
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docker build -t onap/py-app-arm64 . |
Push arm image to the registry
Once the image has been successfully built, push it to the repository.
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docker push onap/py-app-arm64arm64v8:latest |
Build Intel image (B)
Log into an intel server, setup the code structure as before.
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| Code Block |
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docker build -t onap/py-app-amd64 . |
Push Intel image to the registry
| Code Block |
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docker push onap/py-app-amd64:latest |
Create a manifest list for image A and image B
Now that we have built and pushed layers for each cpu architecture, we can create the manifest list to put the final container image together with
| Code Block |
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docker manifest create onap/py-app \
onap/py-app-arm64arm64v8 \
onap/py-app-amd64 |
Verify that the manifest describes a
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platform-
...
agnostic container image.
| Code Block |
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docker manifest inspect --verbose onap/py-app |
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| Code Block |
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[
{
"Ref": "docker.io/onap/py-app-amd64:latest",
"Descriptor": {
"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
"digest": "sha256:4b1b8361d47770668ff4c728dc388f376158d9e8d82c0b4cdb22147cc8ca1be6",
"size": 1579,
"platform": {
"architecture": "amd64",
"os": "linux"
}
},
"SchemaV2Manifest": {
"schemaVersion": 2,
"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
"config": {
"mediaType": "application/vnd.docker.container.image.v1+json",
"size": 6616,
"digest": "sha256:f2947f4a0e9d5d0a4ccf74a7b3ad94611a8921ca022b154cabcad9e453ea6ec5"
},
"layers": [
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 2206931,
"digest": "sha256:4fe2ade4980c2dda4fc95858ebb981489baec8c1e4bd282ab1c3560be8ff9bde"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 308972,
"digest": "sha256:1b23fa3ccba56eced7bd53d424b29fd05cd66ca0203d90165e988fdd8e71fed7"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 17711780,
"digest": "sha256:b714494d7662fbb89174690cefce1051117ed524ec7995477b222b8d96fb8f0c"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 1776866,
"digest": "sha256:1098418f3d2f83bcccdbb3af549d75d9a5e9c37420e5c0d474fd84b022f6c995"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 360,
"digest": "sha256:ca727cee7c2469ab6edb7ca86378985b3747938a325ddb7d90f3b85a3d14b34f"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 4315553,
"digest": "sha256:767bbe8ba063767093b0350e8d1b86b438c677e3884c2a21851c00970d88317c"
}
]
}
},
{
"Ref": "docker.io/onap/py-app-arm64arm64v8:latest",
"Descriptor": {
"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
"digest": "sha256:8a06f997353177dae82d7e01bc3893b2f05c6ac27b317655df3ca2287f9b83a9",
"size": 1786,
"platform": {
"architecture": "arm64",
"os": "linux"
}
},
"SchemaV2Manifest": {
"schemaVersion": 2,
"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
"config": {
"mediaType": "application/vnd.docker.container.image.v1+json",
"size": 6864,
"digest": "sha256:b097a21c92a9a0dde06f9b36bf10def56a028b3b9b1617d6d6c6a8559d14d9d7"
},
"layers": [
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 2099514,
"digest": "sha256:47e04371c99027fae42871b720fdc6cdddcb65062bfa05f0c3bb0a594cb5bbbd"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 176,
"digest": "sha256:b4103359e1ecd9a7253d8b8a041d4e81db1ff4a5e1950bc0e02305d221c9e6c2"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 308518,
"digest": "sha256:92079a442932f09a622f4a0f863e5cc2f6e0471a98e5121fa719d2a276440386"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 18605961,
"digest": "sha256:f1fc35806f46347993a2cd1eb7f7dd7837b0bef0392c8e2c973b24c02ad874a9"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 1786389,
"digest": "sha256:c2983ee3d71107a9a0bc1996fc3a58e050026995fad4aee9d72539153db1df3d"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 391,
"digest": "sha256:44c3eae5ed66bb040727a64fd78573fe6cc4a94a9317d5cd6f39e53332c2ae21"
},
{
"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
"size": 4305558,
"digest": "sha256:8daa79c3024a565c320ff69990ad48273937cc3f6f0cdb324e086c268cf6245e"
}
]
}
}
]
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Push the manifest list to the registry
| Code Block |
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docker manifest push onap/py-app |
Building Multi-CPU container images using CI/CD pipelines
The following diagram depicts a CI/CD flow that implements the production of multi-cpu architecture container images.
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| Gliffy Diagram | ||||||
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The following view illustrates intermediate step of building and storing executable and sequence of image processing
| Gliffy Diagram | ||||
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Intermediate Image Naming Convention
As described above, multiplatform-cpu architecture agnostic support requires platform specific images that are put together to expose a multi-platform image. Architectures Platform architectures include, among others, arm,intel, mips, ppc64le, and s390x
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Note: This table does not contain a exhaustive list of options and must only be used as an image naming guide. Because ONAP is vendor-agnostic, it the list is not intended as a statement of what architectures or OSs ONAP must support.
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