TFLint is a Terraform linter for detecting errors that can not be detected by terraform plan. |
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Docker image for TfLint
TFLint is a Terraform linter focused on possible errors, best practices, etc.
You can see the cli reference here.
Usage
You can run awscli to manage your AWS services.
aws iam list-users
aws s3 cp /tmp/foo/ s3://bucket/ --recursive --exclude "*" --include "*.jpg"
aws sts assume-role --role-arn arn:aws:iam::123456789012:role/xaccounts3access --role-session-name s3-access-example
Pull latest image
docker pull cardboardci/tflint
Test interactively
docker run -it cardboardci/tflint /bin/bash
Run basic AWS command
docker run -it -v "$(pwd)":/workspace cardboardci/tflint aws s3 cp file.txt s3://bucket/file.txt
Run AWS CLI with custom profile
docker run -it -v "$(pwd)":/workspace -v "~/.aws/":/cardboardci/.aws/ cardboardci/tflint aws s3 cp file.txt s3://bucket/file.txt
Continuous Integration Services
For each of the following services, you can see an example of this image in that environment:
Tagging Strategy
Every new release of the image includes three tags: version, date and latest
. These tags can be described as such:
latest
: The most-recently released version of an image. (cardboardci/tflint:latest
)<version>
: The most-recently released version of an image for that version of the tool. (cardboardci/tflint:1.0.0
)<version-date>
: The version of the tool released on a specific date (cardboarci/awscli:1.0.0-20190101
)
We recommend using the digest for the docker image, or pinning to the version-date tag. If you are unsure how to get the digest, you can retrieve it for any image with the following command:
docker pull cardboardci/tflint:latest
docker inspect --format='{{index .RepoDigests 0}}' cardboardci/tflint:latest
Fundamentals
All images in the CardboardCI namespace are built from cardboardci/ci-core. This image ensures that the base environment for every image is always up to date. The common base image provides dependencies that are often used building and deploying software.
By having a common base, it means that each image is able to focus on providing the optimal tooling for each development workflow.