Quick start run CLI using docker 🐳

No installation needed, you will run a public docker image of cloud-scanner CLI.

Pre-requisites

  • Docker.
  • A working AWS account (and your AWS CLI profile already configured)

Run cloud-scanner cli

docker pull ghcr.io/boavizta/cloud-scanner-cli:latest
docker run -it ghcr.io/boavizta/cloud-scanner-cli:latest --help

# Ensure you have a working AWS profile setup locally (like you would do for AWS CLI)
# Note
# - we map local credentials on the container (-v)
# - we force a using 'myprofile' profile by setting the AWS_PROFILE environment variable with -e flag
# - the -it flag is optional, only purpose is to get colored output if any

# Just list instances
docker run -it -v $HOME/.aws/credentials:/root/.aws/credentials:ro -e AWS_PROFILE='myprofile' ghcr.io/boavizta/cloud-scanner-cli:latest inventory

# List instances and standard impacts (for 10 hours of use)
docker run -it -v $HOME/.aws/credentials:/root/.aws/credentials:ro -e AWS_PROFILE='myprofile' ghcr.io/boavizta/cloud-scanner-cli:latest estimate --use-duration-hours 10

# Serve metrics
# /!\ Note that we need to provide CA certificates and bind listen address to 0.0.0.0.
docker run -it -p 8000:8000 -v /etc/ssl/certs/ca-certificates.crt:/etc/ssl/certs/ca-certificates.crt -v $HOME/.aws/credentials:/root/.aws/credentials:ro -e ROCKET_ADDRESS=0.0.0.0 -e ROCKET_PORT=8000 -e AWS_PROFILE='myprofile'  ghcr.io/boavizta/cloud-scanner-cli:latest serve

⚠ This method of passing credentials is not secure nor very practical. In a production setup on AWS, you should rather rely on the role of the instance that execute the container to manage authentication of the cli.

⚠ Running metric server in container require setting extra variables:

  • to map AWS credentials
  • to map SSL ca certificates
  • and more importantly to configure Rocket to listen to 0.0.0.0 instead of default 127.0.0.1 (which is internal to the container. This is done with the extra variable: ROCKET_ADDRESS=0.0.0.0

Alternatively you may build and use a local docker image, See build a local docker image