Python库 | nitor_deploy_tools-1.51.tar.gz

# Nitor Deploy Tools [](https://travis-ci.org/NitorCreations/nitor-deploy-tools) [](https://coveralls.io/github/NitorCreations/nitor-deploy-tools?branch=master) ## Released version 1.51 Nitor deploy tools are a set of tools to implement a true Infrastructure As Code workflow with AWS and CloudFormation. ## Rationale We at Nitor are software engineers with mostly a developer or architect background, but a lot of us have had to work closely with various Operations teams around the world. DevOps has a natural appeal to us and immediately "infrastructure as code" meant for us that we should apply the best development practices to infrastructure development. It starts with version control and continues with testing new features in isolation and a workflow that supports this. Our teams usually take into use a feature branch workflow if it is feasible and we expect all of the tools and practices to support this. For infrastructure this type of branching means that you should be able to spin up enough of the infrastructure to be able to verify the changes you want to implement in production. Also the testing environment should be close enough to the target environment for the results to be valid. So the differences between testing and production environments should be minimized and reviewable. With the popular tools like Ansible, Terraform, Chef etc. you need to come up with and implement the ways to achieve the goals above. As far as I know, no tool besides ndt has at it's core a thought-out way of a branching infrastructure development model. ## What it is nitor-deploy-tools works by defining _Amazon Machine Images_, _Docker containers_, _Serverless services_ and deploying _[CloudFormation](https://aws.amazon.com/cloudformation/) stacks_ of resources. ## Installation ``` pip install nitor-deploy-tools ``` On OSX you may need to add `--ignore-installed` to get around platform installed versions of `six` and other packages. ## Getting started To use nitor-deploy-tools you need to set up a _project repository_ that describes the images you want to build, and the stacks you want to deploy them in. See [ndt-project-template](https://github.com/NitorCreations/ndt-project-template) for an example. Here are few commands you can use. All of these are run in your project repository root. You need to have AWS credentials for command line access set up. * To bake a new version of an image: `ndt bake-image <image-name>` * To build a new Docker container image `ndt bake-docker <component> <docker-name>` * To deploy a stack: * with a known AMI id: `ndt deploy-stack <image-name> <stack-name> <AMI-id>` * with the newest AMI id by a given bake job: `ndt deploy-stack <image-name> <stack-name> "" <bake-job-name>` * To undeploy a stack: `ndt undeploy-stack <image-name> <stack-name>` For full list of commands see [here](docs/commands.md) ## Documentation - [Command Reference](docs/commands.md) - [ndt workspace tooling](docs/workspace.md) - [Template Pre-Processing](docs/template-processing.md) - [Multifactor Authentication](docs/mfa.md) - [Common parameters](docs/parameters.md) ## Versioning This library uses a simplified semantic versioning scheme: major version change for changes that are not backwards compatible (not expecting these) and the minor version for all backwards compatible changes. We won't make the distinction between new functionality and bugfixes, since we don't think it matters and is not a thing worth wasting time on. We will release often and if we need changes that are not comptatible, we will fork the next major version and release alphas versions of that until we are happy to release the next major version and try and have a painless upgrade path.