toddlipcon / cb-cli

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DataPlane - Command Line Interface

Install

Each Git TAG (without the leading 'v') is built and uploaded to S3 where you can download from:

export VERSION=2.1.0-dev.X

curl -LO "https://s3-eu-west-1.amazonaws.com/dp-cli/dp-cli_${VERSION}_Darwin_x86_64.tgz"
curl -LO "https://s3-eu-west-1.amazonaws.com/dp-cli/dp-cli_${VERSION}_Linux_x86_64.tgz"
curl -LO "https://s3-eu-west-1.amazonaws.com/dp-cli/dp-cli_${VERSION}_Windows_x86_64.tgz"

Usage

To see the available commands dp -h.

NAME:
   DataPlane command line tool
USAGE:
   dp [global options] command [command options]

VERSION:
   snapshot-2018-11-19T19:59:11

AUTHOR(S):
   Hortonworks

COMMANDS:
     audit                 audit related operations
     blueprint     blueprint related operations
     cloud                 information about cloud provider resources
     cluster               cluster related operations
     completion            prints the bash completion function
     configure             configure the server address and credentials used to communicate with this server
     credential            credential related operations
     database              database management related operations
     env                   environment related operations
     imagecatalog          imagecatalog related operations
     ldap                  ldap related operations
     mpack                 management pack related operations
     proxy                 proxy related operations
     recipe                recipe related operations
     user                  user related operations
     workspace             workspace related operations
     help, h               Shows a list of commands or help for one command

GLOBAL OPTIONS:
   --debug        debug mode [$DEBUG]
   --help, -h     show help
   --version, -v  print the version

Each command provides a help flag with a description and the accepted flags and subcommands, e.g: dp configure -h.

NAME:
   DataPlane command line tool

USAGE:
   Hortonworks DataPlane command line tool configure [command options]

DESCRIPTION:
   it will save the provided server address and credential to ~/.dp/config

REQUIRED OPTIONS:
   --server value  server address [$CB_SERVER_ADDRESS]

OPTIONS:
   --profile value       selects a config profile to use [$CB_PROFILE]
   --workspace value     name of the workspace [$CB_WORKSPACE]
   --apikeyid value      API key ID
   --privatekey value    API private key
   --output value        supported formats: json, yaml, table (default: "json") [$CB_OUT_FORMAT]

Configure

Although there is an option to provide some global flags to every command to which DataPlane to connect to, it is recommended to save the configuration. A configuration entry contains the DataPlane server's address, the username and optionally the password and the output format. Multiple configuration profiles can be saved by specifying the --profile switch. The same switch can be used as a global flag to the other commands to use a specific profile. If the profile switch is omitted, the default profile is saved and used.

dp configure --server https://ec2-52-29-224-64...compute.amazonaws.com --workspace your@email --profile dataplane-staging

Note: in case you are using a mocked UMS you can use the following command to generate an accesskey/privatekey pair that is accepted by the mock.

dp generate-mock-apikeys --tenant-name default --tenant-user myusername@cloudera.com

You need to update your ~/.dp/config file with these values.

The provided parameters will be saved into the configuration profile in the user's home directory. To see its content: cat ~/.dp/config. If this config file is present you don't need to specify the connection flags anymore, otherwise you need to specify these flags to every command.

dp cluster list --server https://ec2-52-29-224-64...compute.amazonaws.com --workspace your@email

The --apikeyid and --privatekey configuration parameters are generated by Cloudera Altus, please refer to the documentation.

Create cluster

To create a cluster with the CLI, a cluster descriptor file needs to be put together and specified as an input to the cluster create command:

dp cluster create --cli-input-json create_cluster.json

The cluster descriptor is basically the JSON request that's being sent to the DataPlane API. The full reference of this descriptor file can be found in the API docs. The CLI can help with creating the skeleton of the cluster descriptor JSON. The following command outputs a descriptor file with empty values:

dp cluster generate-template aws existing-subnet --blueprint-name "my-custom-blueprint"

The aws and existing-subnet keywords are subcommands to the cluster generate-template command and help with creating a skeleton with proper entries for the selected cloud provider and network configuration. Use the -h option to see the available subcommands, e.g.:

dp cluster generate-template -h

Direct the output to a file to save the skeleton locally.

dp cluster generate-template aws existing-subnet > create_cluster.json

To create a cluster, fill the empty values or change the existing ones and use the create-cluster command above.

Terminate cluster

To terminate the previously created cluster use the delete-cluster command.

dp cluster delete --cluster-name my-cluster

Describe cluster

If you want to check out the properties of a running cluster the describe-cluster command can be useful.

dp cluster describe --cluster-name my-cluster

Bash completion

To enable bash completion run the following command and follow the instructions:

dp completion

Debug

To enable the debug logging use the --debug global switch

dp --debug cluster list

or provide it as an environment variable export DEBUG=1 or inline

DEBUG=1 dp clusters list

Proxy settings

To use the dp cli behind a proxy you must use the following environment variable:

 export HTTP_PROXY=10.0.0.133:3128

or with basic auth:

export HTTP_PROXY=http://user:pass@10.0.0.133:3128/

Dependency management

This project uses Go modules for dependency management, introduced in golang 1.11. The Makefile enables module support explicitly on build goals, but you can also choose enable it in your system, by setting:

export GO111MODULE=on

Implementing new commands

Top level commands like cluster are separated into a cmd package. You can see an example for these commands in the dataplane/cmd folder. Each of these resource separated files contain an init function that adds the resource specific commands to an internal array:

func init() {
    DataPlaneCommands = append(DataPlaneCommands, cli.Command{})
}

The init() function is automatically invoked for each file in the cmd folder, because it is referenced from the main.go file:

import (
	"github.com/hortonworks/cb-cli/dataplane/cmd"
)

and then added to the main app:

app.Commands = append(app.Commands, cmd.DataPlaneCommands...)

To implement new top level commands you can create your own folder structure and reproduce the above specified:

- Create your own resource separation files/folders etc..
- Implement the init() function for these files
- Reference these files from the main.go file
- Add your commands to the app.Commands

If you'd like to introduce sub-commands for already existing top level commands that are not DataPlane specific you can move the cluster.go file (for example) from the dataplane/cmd folder to a top level cmd folder and reference it from the main.go file as describe above.

Plugins

The CLI also supports a plugin model. This means that you can create similar CLI tools like this one and build them independently/separately, but get them invoked by the main CLI tool. Let's assume you'd like to create a dlm CLI, but develop it outside from this repository, but with the same framework. If you create the dlm binary and put it in your $PATH you can invoke with the main CLI tool like:

dp dlm my-command

In order to do this the main CLI needs to be built with plugin mode enabled:

PLUGIN_ENABLED=true make build

This way you have introduced another top level command, but you have the advantage to:

* dynamically install/enable/disable top level commands without re-building/downloading the top level CLI
* dynamically upgrade commands without re-building/downloading the top level CLI
* develop it independently from this repository
* have an independent CLI tool that can be invoked without the top level CLI

Functional Testing

This repository contains also functional tests for CB-CLI (in End to End and Integration suites).

About

License:Apache License 2.0


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