我正在尝试在gitlab上使用kaniko构建docker映像,并将该映像放置在AWS ECR服务中。现在,在执行指令以构建dockerfile的过程中,我得到一个错误,指出它无法解析dockerfile,并且在第一行失败。从控制台错误开始时的<!DOCTYPE指示来看,我会说它可能无法找到dockerfile,但是,我指定了我认为的文件的正确路径。我也有权访问存储库以及推送到ECR。
这是我最终在出错时得到的确切输出控制台输出:
# Normalize data
scaler = StandardScaler()
scaler.fit(X_train)
...
# Create model
model = Sequential(...)
# Compile and train
...
# Save model with normalization mean and var
model.normalization_mean = scaler.mean_
model.normalization_var = scaler.var_
keras.models.save_model(model = model,
filepath = ...)
# Reload model
model = keras.models.load_model(filepath = ...)
hasattr(model, 'normalization_mean') # False
hasattr(model, 'normalization_var') # False
这是我的gitlab-ci.yml
Checking out xxxxx as develop...
Updating/initializing submodules recursively...
$ mkdir -p $HOME/.docker/ && echo "{ \"proxies\": { \"default\": { \"httpProxy\": \"$HTTP_PROXY\", \"httpsProxy\": \"$HTTPS_PROXY\", \"noProxy\": \"$NO_PROXY\" } } }" > $HOME/.docker/config.json
00:01
$ mkdir -p /kaniko/.docker
$ echo "{\"credsStore\":\"ecr-login\"}" > /kaniko/.docker/config.json
$ /kaniko/executor --context $AWS_PROJECT_DIR --dockerfile $AWS_PROJECT_DIR_DOCKERFILE/Dockerfile --destination $AWS_REGISTRY_IMAGE:latest
error building image: parsing dockerfile: Dockerfile parse error line 1: unknown instruction: <!DOCTYPE
ERROR: Job failed: exit code 1
这是我的dockerfile:
.iat_variables: &iat_variables
AWS_PROJECT_DIR_DOCKERFILE: some-git-repo-url/aws/eks/awx/-/tree/develop
AWS_PROJECT_DIR: some-git-repo-url/aws/eks/awx/-/tree/develop
AWS_REGISTRY_IMAGE: some-ecr-registry-url/awx
variables:
GIT_DEPTH: 10
GIT_SUBMODULE_STRATEGY: recursive
stages:
- build
build:
image:
name: gcr.io/kaniko-project/executor:debug
entrypoint: [""]
stage: build
variables:
<<: *iat_variables
tags:
- aws
only:
- develop
script:
- mkdir -p /kaniko/.docker
- echo "{\"credsStore\":\"ecr-login\"}" > /kaniko/.docker/config.json
- /kaniko/executor --context $AWS_PROJECT_DIR --dockerfile $AWS_PROJECT_DIR_DOCKERFILE/Dockerfile --destination $AWS_REGISTRY_IMAGE:latest
when: manual