Tembo CLI

Tembo CLI allows users to experience Tembo locally, as well as, manage and deploy to Tembo Cloud. It abstracts away complexities of configuring, managing, and running Postgres.

Getting Started

Installing CLI

Using homebrew

brew tap tembo-io/tembo
brew install tembo-cli

Using cargo

cargo install tembo-cli

Commands

tembo init

The tembo init command initializes your environment with following files. Run init in the directory you want to create the tembo.toml file.

• tembo.toml example configuration file
• ~/.tembo/context file with various contexts user can connect to
• ~/.tembo/credentials file with credentials & api urls

For more information: tembo init --help

Add Tembo Cloud info

To provision instances on Tembo Cloud using CLI you will need to configure org_id & tembo_access_token

• fetch the org_id from Tembo Cloud and add it as org_id in context file generated above
• generate a JWT token using steps here & add it as tembo_access_token to the credentials file generated above.

tembo context list/set

tembo context works like kubectl context. User can set context for local docker environment or tembo cloud (dev/qa/prod) with org_id. When they run any of the other commands it will run in the context selected. Default context will be local.

tembo validate

Validates tembo.toml and other configurations files.

tembo apply

Validates tembo.toml (same as tembo validate) and applies the changes to the context selected.

Environment:

• Local Docker:

  • runs docker-compose down to bring down all existing containers
  • generates Dockerfile for each instance & builds a docker image
  • generates docker-compose to provision all instances
  • runs docker-compose up -d to spin up all instances

• Tembo-Cloud:

  • Creates/updates instance on tembo-cloud by calling the api against the appropriate environment

Flags:

• --merge: Overlays Tembo.toml by another toml file for a specific context
• --set : Specifies a single instance setting by assigning a new value

tembo logs

Retrieves log data from the specified Tembo instances. Depending on your current context, it will fetch logs from either local Docker containers or Tembo Cloud instances.

tembo delete

• local docker: runs docker-compose down command to bring down all containers
• tembo-cloud: deletes the instance on tembo-cloud by calling the api

Developing Tembo CLI

Local Testing

Clone this repo and run:

cargo install --path .

If the install path is in your shell path, you can then run tembo help and other tembo commands.

You can run this command to use the local code for any tembo command during development:

alias tembo='cargo run --'

Generating Rust Client from API

OpenAPI Generator tool is used to generate Rust Client.

Install OpenAPI Generator if not already by following steps here

Data plane API client

Go to tembodataclient directory in your terminal.

Delete the contents of the directory first and then run following command to re-generate the rust client code for the API.

openapi-generator generate -i https://api.data-1.use1.tembo.io/api-docs/openapi.json  -g rust -o . --additional-properties=packageName=tembodataclient

• Go to tembodataclient/src/lib.rs & add following line at the top to disable clippy for the generated code

#![allow(clippy::all)]

Control plane API client

Go to temboclient directory in your terminal.

Delete the contents of the directory first and then run following command to re-generate the rust client code for the API.

openapi-generator generate -i https://api.tembo.io/api-docs/openapi.json  -g rust -o . --additional-properties=packageName=temboclient

• Go to temboclient/src/lib.rs & add following line at the top to disable clippy for the generated code

#![allow(clippy::all)]

• Create temboclient/src/models/impls.rs file & add following code to it:

use std::str::FromStr;

use super::{Cpu, Environment, Memory, StackType, Storage};

impl FromStr for Cpu {
    type Err = ();

    fn from_str(input: &str) -> core::result::Result<Cpu, Self::Err> {
        match input {
            "0.25" => Ok(Cpu::Variant0Period25),
            "0.5" => Ok(Cpu::Variant0Period5),
            "1" => Ok(Cpu::Variant1),
            "2" => Ok(Cpu::Variant2),
            "4" => Ok(Cpu::Variant4),
            "8" => Ok(Cpu::Variant8),
            "16" => Ok(Cpu::Variant16),
            "32" => Ok(Cpu::Variant32),
            _ => Err(()),
        }
    }
}

impl FromStr for Memory {
    type Err = ();

    fn from_str(input: &str) -> core::result::Result<Memory, Self::Err> {
        match input {
            "1Gi" => Ok(Memory::Variant1Gi),
            "2Gi" => Ok(Memory::Variant2Gi),
            "4Gi" => Ok(Memory::Variant4Gi),
            "8Gi" => Ok(Memory::Variant8Gi),
            "16Gi" => Ok(Memory::Variant16Gi),
            "32Gi" => Ok(Memory::Variant32Gi),
            _ => Err(()),
        }
    }
}

impl FromStr for Environment {
    type Err = ();

    fn from_str(input: &str) -> core::result::Result<Environment, Self::Err> {
        match input {
            "dev" => Ok(Environment::Dev),
            "test" => Ok(Environment::Test),
            "prod" => Ok(Environment::Prod),
            _ => Err(()),
        }
    }
}

impl FromStr for Storage {
    type Err = ();

    fn from_str(input: &str) -> core::result::Result<Storage, Self::Err> {
        match input {
            "10Gi" => Ok(Storage::Variant10Gi),
            "50Gi" => Ok(Storage::Variant50Gi),
            "100Gi" => Ok(Storage::Variant100Gi),
            "200Gi" => Ok(Storage::Variant200Gi),
            "300Gi" => Ok(Storage::Variant300Gi),
            "400Gi" => Ok(Storage::Variant400Gi),
            "500Gi" => Ok(Self::Variant500Gi),
            _ => Err(()),
        }
    }
}

impl FromStr for StackType {
    type Err = ();

    fn from_str(input: &str) -> core::result::Result<StackType, Self::Err> {
        match input {
            "Standard" => Ok(StackType::Standard),
            "MessageQueue" => Ok(StackType::MessageQueue),
            "MachineLearning" => Ok(StackType::MachineLearning),
            "OLAP" => Ok(StackType::Olap),
            "VectorDB" => Ok(StackType::VectorDb),
            "OLTP" => Ok(StackType::Oltp),
            "DataWarehouse" => Ok(StackType::DataWarehouse),
            "Geospatial" => Ok(StackType::Geospatial),
            "Timeseries" => Ok(StackType::Timeseries),
            _ => Err(()),
        }
    }
}

• Add following line towards the end of temboclient/src/models/mod.rs

pub mod impls;

Contributing

Before you start working on something, it's best to check if there is an existing plan first. Join our Slack community and ask there.

Semver

Tembo CLI is following Semantic Versioning 2.0.