We’ve had pipelines setup for multiple GitLab.com repos that run successfully using shared runners for some time now but just recently they started failing when triggered from a commit/push with this error:
Found errors in your .gitlab-ci.yml:
- Included file
.gitlab-ci.ymldoes not have valid YAML syntax!You can also test your .gitlab-ci.yml in CI Lint
The CI Lint indicates the yml is valid and when using the GitLab.com UI and going to Pipelines > Run Pipeline it executes without any issues. Here’s the CI with sensitive info removed (it deploys an AWS Lambda):
From: https://gist.github.com/m8r1x/8b5c8267078007984a29b03c2db1fe05
variables:
LAMBDA_NAME: 'LambdaName' # Replace it with the name of aws lambda function you want.
LAMBDA_ARN: 'arn:aws:lambda:us-east-1:AccountNumber:function:LambdaName' # ARN associated with this lambda function.
ZIP_FILENAME: 'LambdaName.zip' # This is the name of the ZIP package that will be created and uploaded to S3
LAMBDA_ENVIRONMENT_DEFAULT: "Variables={ENV=dev}"
LAMBDA_ENVIRONMENT_STAGE: "Variables={ENV=stage}"
LAMBDA_ENVIRONMENT_PROD: "Variables={ENV=prod}"
# The following vars generally stay the same
LAMBDA_HANDLER: 'lambda_function.lambda_handler' # This is default lambda handler.
LAMBDA_RUNTIME: 'python3.7'
S3_BUCKET: 'BucketName' # Replace it with the name of Bucket that will hold the zip code.
LAMBDA_ROLE_ARN: 'arn:aws:iam::AccountNumber:role/RoleName'
LAYERS_ARN: 'arn:aws:lambda:us-east-1:AccountNumber:layer:LayerName:114 arn:aws:lambda:us-east-1:AccountNumber:layer:OtherLayerName:108'
LAMBDA_TIMEOUT: 900 # Default is 3, up to 900. Setting this to 30 for all "local" functions, and 90 for ones using external APIs
LAMBDA_MEMORY: 3008 # Default is 128, up to 3008 in 64 MB increments
image: python:latest
before_script:
- apt-get update -y # Updating the Ubuntu Docker instance.
- python -V # Print out python version for debugging.
- apt install -y zip jq
- pip install awscli --upgrade --user --trusted-host=pypi.python.org --trusted-host=pypi.org --trusted-host=files.pythonhosted.org
- export PATH=~/.local/bin:$PATH # Required for awscli.
- aws --version # Print out aws cli version for debugging.
stages:
- deploy-dev
- deploy-stage # manual deploy
- deploy-prod # manual deploy
deploy-dev:
stage: deploy-dev
only:
- dev # We will run the CD only when something is going to change in dev branch.
before_script:
- apt-get update -y # Updating the Ubuntu Docker instance.
- python -V # Print out python version for debugging.
- apt install -y zip jq
- pip install awscli --upgrade --user
- export PATH=~/.local/bin:$PATH # Required for awscli.
- aws --version # Print out aws cli version for debugging.
# set dev LAMBDA_ENVIRONMENT and vars
- export LAMBDA_ENVIRONMENT=$LAMBDA_ENVIRONMENT_DEFAULT
- echo $LAMBDA_ENVIRONMENT
- export LAMBDA_ALIAS="DEV"
- echo $LAMBDA_ALIAS
script:
# Archive the code repository.
- zip -r $ZIP_FILENAME . -x \*.pyc *.git*
# Upload archive into s3.
- aws s3 cp $ZIP_FILENAME s3://$S3_BUCKET/$ZIP_FILENAME
# Update the Lambda with the uploaded code
- aws lambda update-function-code --function-name $LAMBDA_NAME --zip-file fileb://$ZIP_FILENAME || aws lambda create-function --function-name $LAMBDA_NAME --runtime $LAMBDA_RUNTIME --role $LAMBDA_ROLE_ARN --handler $LAMBDA_HANDLER --code S3Bucket=$S3_BUCKET,S3Key=$ZIP_FILENAME --memory-size $LAMBDA_MEMORY --layers $LAYERS_ARN --environment $LAMBDA_ENVIRONMENT --timeout $LAMBDA_TIMEOUT
# Create lambda alias in case it doesn't exist
# Update the Lambda config to use the layers specified above, and the environment vars corresponding to this branch
- aws lambda create-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version '$LATEST' || aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT
# Publish a new version of the Lambda (including the environment vars set in the previous step), catch the Version number from the output
- "export LAMBDA_VERSION=$(aws lambda publish-version --function-name $LAMBDA_NAME --query \'Version\' --output text)"
# Update the Lambda alias corresponding to this branch to use the Version we just published
- aws lambda update-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version $LAMBDA_VERSION
# Reset Lambda config environment vars to default so Latest has the dev vars
- aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT_DEFAULT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT
environment:
name: dev
deploy-stage:
stage: deploy-stage
only:
- stage # We will run the CD only when something is going to change in stage branch.
before_script:
- apt-get update -y # Updating the Ubuntu Docker instance.
- python -V # Print out python version for debugging.
- apt install -y zip jq
- pip install awscli --upgrade --user
- export PATH=~/.local/bin:$PATH # Required for awscli.
- aws --version # Print out aws cli version for debugging.
# set stage LAMBDA_ENVIRONMENT and vars
- export LAMBDA_ENVIRONMENT=$LAMBDA_ENVIRONMENT_STAGE
- echo $LAMBDA_ENVIRONMENT
- export LAMBDA_ALIAS="STAGE"
- echo $LAMBDA_ALIAS
script:
# Archive the code repository.
- zip -r $ZIP_FILENAME . -x \*.pyc *.git*
# Upload archive into s3.
- aws s3 cp $ZIP_FILENAME s3://$S3_BUCKET/$ZIP_FILENAME
# Update the Lambda with the uploaded code
- aws lambda update-function-code --function-name $LAMBDA_NAME --zip-file fileb://$ZIP_FILENAME || aws lambda create-function --function-name $LAMBDA_NAME --runtime $LAMBDA_RUNTIME --role $LAMBDA_ROLE_ARN --handler $LAMBDA_HANDLER --code S3Bucket=$S3_BUCKET,S3Key=$ZIP_FILENAME --memory-size $LAMBDA_MEMORY --layers $LAYERS_ARN --environment $LAMBDA_ENVIRONMENT --timeout $LAMBDA_TIMEOUT --runtime $LAMBDA_RUNTIME
# Create lambda alias in case it doesn't exist
# Update the Lambda config to use the layers specified above, and the environment vars corresponding to this branch
- aws lambda create-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version '$LATEST' || aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT --runtime $LAMBDA_RUNTIME
# Publish a new version of the Lambda (including the environment vars set in the previous step), catch the Version number from the output
- "export LAMBDA_VERSION=$(aws lambda publish-version --function-name $LAMBDA_NAME --query \'Version\' --output text)"
# Update the Lambda alias corresponding to this branch to use the Version we just published
- aws lambda update-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version $LAMBDA_VERSION
# Reset Lambda config environment vars to default so Latest has the dev vars
- aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT_DEFAULT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT --runtime $LAMBDA_RUNTIME
environment:
name: stage
when: manual
deploy-prod:
stage: deploy-prod
only:
- prod # We will run the CD only when something is going to change in prod branch.
before_script:
- apt-get update -y # Updating the Ubuntu Docker instance.
- python -V # Print out python version for debugging.
- apt install -y zip jq
- pip install awscli --upgrade --user
- export PATH=~/.local/bin:$PATH # Required for awscli.
- aws --version # Print out aws cli version for debugging.
# set prod LAMBDA_ENVIRONMENT and vars
- export LAMBDA_ENVIRONMENT=$LAMBDA_ENVIRONMENT_PROD
- echo $LAMBDA_ENVIRONMENT
- export LAMBDA_ALIAS="PROD"
- echo $LAMBDA_ALIAS
script:
# Archive the code repository.
- zip -r $ZIP_FILENAME . -x \*.pyc *.git*
# Upload archive into s3.
- aws s3 cp $ZIP_FILENAME s3://$S3_BUCKET/$ZIP_FILENAME
# Update the Lambda with the uploaded code
- aws lambda update-function-code --function-name $LAMBDA_NAME --zip-file fileb://$ZIP_FILENAME || aws lambda create-function --function-name $LAMBDA_NAME --runtime $LAMBDA_RUNTIME --role $LAMBDA_ROLE_ARN --handler $LAMBDA_HANDLER --code S3Bucket=$S3_BUCKET,S3Key=$ZIP_FILENAME --memory-size $LAMBDA_MEMORY --layers $LAYERS_ARN --environment $LAMBDA_ENVIRONMENT --timeout $LAMBDA_TIMEOUT
# Create lambda alias in case it doesn't exist
# Update the Lambda config to use the layers specified above, and the environment vars corresponding to this branch
- aws lambda create-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version '$LATEST' || aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT
# Publish a new version of the Lambda (including the environment vars set in the previous step), catch the Version number from the output
- "export LAMBDA_VERSION=$(aws lambda publish-version --function-name $LAMBDA_NAME --query \'Version\' --output text)"
# Update the Lambda alias corresponding to this branch to use the Version we just published
- aws lambda update-alias --function-name $LAMBDA_NAME --name $LAMBDA_ALIAS --function-version $LAMBDA_VERSION
# Reset Lambda config environment vars to default so Latest has the dev vars
- aws lambda update-function-configuration --function-name $LAMBDA_NAME --layers $LAYERS_ARN --handler $LAMBDA_HANDLER --environment $LAMBDA_ENVIRONMENT_DEFAULT --memory-size $LAMBDA_MEMORY --timeout $LAMBDA_TIMEOUT
environment:
name: prod
when: manual