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πŸ•Ή macOS setup πŸ›Ή development workflow πŸš€ CI/CD building blocks πŸŽ‰

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nhs-england-tools/make-devops

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Make DevOps

If you hear your teams or individuals saying "It will take days to onboard a new member...", "It works on my machine..." or "Our pipeline is to complex and no one really understands how it all works..." then you need to invest more in automation and perhaps take an interest in this project. This project will help you to make your deploys boring!

Use cases

  • Service team AWS accounts setup with predefined base components to speed up configuration
  • CI/CD building blocks to support a clean implementation of your pipelines and make them vendor agnostic as much as it is feasible
  • Development workflow with highly customisable project automation scripts (inspired by dotfiles) for advanced *NIX shell scripting
  • macOS setup to complement the above and fully automate development environment provisioning

Installation

  • Set up your development environment on a macOS - this command will install/update and configure your OS packages: curl -L bit.ly/make-devops-macos | bash
  • Instrument your project with the automation scripts - this command will update the existing git project structure in the current directory: curl -L bit.ly/make-devops-project | bash
  • Use the make targets to support your CI/CD flow
  • Configure AWS service team accounts using Terraform templates

Features

  • Shell native
  • Automated setup
  • Local development flow support
  • Pipeline consistency and testability
  • Highly customisable and flexible implementation
  • Integration with a 3rd-party packages and services
  • Documentation templates
  • Unit and integration tests
  • Example of the repository structure that can consist of a single or multiple projects
  • Deployment profiles
    • A password, key, tokens etc. should be represented by a corresponding system variable in the profile files
    • No sensitive information should be stored in the profile files
      • An exception is the local profile where it is acceptable to set all the configuration options, e.g. ADMIN_PASSWORD = secret
      • The same variable in any other profile i.e. live should be defined as #ADMIN_PASSWORD = [secret] by a convention
      • All the sensitive variables should be sourced from the AWS Secrets Manager using eval $$(make secret-fetch-and-export-variables NAME=secret-name)
  • Data Docker image to run SQL scripts against a database instance
  • Tools Docker image with various command-line utilities pre-installed
  • Git hooks
  • Git secrets
  • Visual Studio Code and iTerm configuration
  • Virtual environments for Python, Go, Java and Node.js
  • Texas AWS MFA script
  • Texas AWS SSM Session Manager script
  • Toggle natural scrolling script
  • Remote pair programming and live collaboration

Usage

  • Run make help-all to see all available targets
  • Update the toolchain scripts to the most recent version by executing make devops-synchronise
  • Use make devops-print-variables to print out all the effective variables. Include PROFILE=[name] to evaluate profile specific variables
  • To run unit test suite use make devops-test-suite or alternatively to run a single one execute make devops-test-single NAME=[test target name]. Set the DEBUG=true flag to run the tests in the verbose mode
  • To provision your macOS run make macos-setup or alternatively update configuration make macos-config

Conventions

  • Set all the profile specific information in a build/automation/var/profile/[name].mk file
  • Set all the project specific information in the build/automation/var/project.mk file. There is set of mandatory variables that must be defined for the library to function correctly. For more details, please refer to the build/automation/var/project.mk file from the Project Template workspace
  • Your development flow should be described in the main Makefile in the root directory of the project. Content of that file must meet certain implementation requirements and include some predefined sections
  • Create custom helper targets in the Makefile file or in the individual sub-project directories. These targets should be lower-level targets supporting your project's development flow
  • If a library target does not work in the expected way there are two ways of solving that issue
    • Create a patch, raise an MR and assign it to one of the library maintainers
    • Override the make target by creating it with the same name in the build/automation/var/project.mk file
  • Target name convention
    • Use descriptive-name
    • Create project-* targets for the ops work flow or production usage, e.g. project-build, project-deploy
    • Create dev-* targets for the dev work flow, e.g. dev-build
    • Create [component]-[activity] complementary targets
    • Prefix target with the underscore i.e. _descriptive-name to indicate that it is a 'private' target
    • Do not exceed 40 characters
  • Target help convention
    • Sample format is # Target description - mandatory: ARG1=[argument description]; optional: ARG2="argument-value"; return: [string]. A mandatory argument name can be concise e.g. IMAGE, however to avoid unpredicted behaviour while constructing higher lever make targets use more descriptive naming convention for the optional arguments e.g. DOCKER_IMAGE
    • Prefix with # to indicate a project specific development workflow target listed by make help or help-project-development
    • Prefix with ## to indicate a project specific supporting or deployment target listed by make help-project-supporting
    • Prefix with ### to indicate library target, use make help-all to see the full list of available targets
    • An argument is mandatory when target cannot function without it being specified and this argument is not a configuration option
    • An argument is optional when it is provided by a profile, however it is intended to be set from the command-line depending on the context
  • Best practices
    • Use the same names for secret keys and make variables defined in your profiles
    • Group variables logically, e.g. DB_HOST, DB_PORT, DB_NAME, DB_USERNAME, DB_PASSWORD create a one group
    • Sort a group of variables alphabetically if there is no direct correlation between them, e.g. TF_VAR_route53_terraform_state_key, TF_VAR_vpc_terraform_state_key
    • Never modify library files, except the Makefile and files that are in the build/automation/var directory which are project-specific
    • Always use a single tab character for code indentations
    • Follow the variable assignment rules to avoid an unexpected result
      • Any project or profile specific variable should be recursively expanded by using the = operator
      • Best practice is to keep all the modules variable assignments as recursively expanded which will allow to override and customise the configuration
      • However, within the build/automation/init.mk simply expanded variables (using :=) are preferred as this will enable to inherit value from a corresponding shell variable e.g. export PROFILE=dev will work as expected in line PROFILE := $(or $(PROFILE), local) and set the profile to dev
    • Naming
      • Service tag: $(PROJECT_GROUP_SHORT) or its prefix
      • ECR image: $(PROJECT_GROUP_SHORT)/$(PROJECT_NAME_SHORT)/$(NAME)
      • K8s namespace: $(PROJECT_ID)-$(ENVIRONMENT) or $(PROJECT_ID)-$(ENVIRONMENT)-job
      • Terraform state: $(PROJECT_ID)/$(ENVIRONMENT)/$(STACK)
      • AWS tags: TagSet=[{key=Programme,value=$(PROGRAMME)},{key=Service,value=$(SERVICE_TAG),{key=Environment,value=$(ENVIRONMENT)},{key=Profile,value=$(PROFILE)}]
      • AWS resources prefix: $(PROJECT_ID)-*
      • AWS secret name for deployment: $(PROJECT_ID)-$(PROFILE)/deployment
      • AWS bucket name for deployment: $(PROJECT_ID)-$(PROFILE)-deployment
      • AWS table name for deployment: $(PROJECT_ID)-deployment
      • AWS database instance: $(PROJECT_ID)-$(ENVIRONMENT) or $(PROJECT_ID)-$(NAME)-$(ENVIRONMENT)
      • Local domain names: $(PROJECT_NAME_SHORT).local, $(PROJECT_NAME).local, $(PROJECT_NAME_SHORT)-$(PROJECT_GROUP_SHORT).local
    • SSL certificate
      • A default SSL certificate for development is going to be created by the automation scripts in the build/automation/etc/certificate directory
      • Commit the relevant files and use this certificate to enable encrypted communication between components within the project
    • Versioning
      • Library build: [YYYYmmdd] - fixed on the date of modification as a Docker tag
      • User build: [YYYYmmddHHMMss]-[hash] - dynamic, set during the build process as a Docker tag
      • On demand deployment: [YYYYmmddHHMMss]-[env] - set by a developer as a Git tag and then as a Docker tag as well on the corresponding image

Guiding Principles

  • Simplicity and usability
  • Do one thing well
  • Clear intent, principle of least surprise
  • Non-enforcing and supporting role
  • Well documented, documentation as code
  • A pipeline can run anywhere, e.g. any *NIX like system
  • Technology agnostic and universal design that can support Java, .NET, Python, Go, Node and others

Maintenance

  • Update software versions
    • Docker base images version in the build/automation/lib/docker.mk file and all the related modules
    • Python packages version from the PYTHON_BASE_PACKAGES list in the build/automation/lib/python.mk file
    • Tools version in the build/automation/lib/docker/image/tools/Dockerfile file
    • Gunicorn version in the build/automation/lib/docker/image/python-app/Dockerfile file
    • Docker library images version in any build/automation/lib/docker/image/*/VERSION file
    • Terraform modules in the build/automation/lib/terraform/template/modules directory

You can also check the versions alignment across the library by running the make devops-check-versions command.

CI/CD Design

DevOps Pipelines

Status

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Automated Test CircleCI

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