This section provides step-by-step guides for installing Meltano in various environments. Currently, we provide detailed intructions for:
DigitalOcean provides a simple container for spinning up a server where Meltano can be deployed to the Cloud. Install the Meltano 1-Click App in the DigitalOcean Marketplace
Get $50 Worth of DigitalOcean Credits for Free
When you create a new DigitalOcean account using this link (which contains our referral code) you will receive $50 of free credit over 30 days.
Please note, at times the Meltano version on DigitalOcean may be slightly behind the current PyPi version.
Create Meltano Droplet
If you are not logged in already, you will be asked to login, or create a new DigitalOcean account
By default, your droplet will come with the following settings that you can customize if desired
Add authentication to your droplet via SSH
Once your Droplet is created, it will have its own IP address displayed in the DigitalOcean user interface.
Now that you've got your Meltano instance up and running, visit our Getting Started Guide to connect some data sources and start building your data pipelines and dashboards!
Build a Custom Meltano Droplet on DigitalOcean
Looking to customize your DigitalOcean Droplet build and configuration? Please follow the instructions in our Advanced Tutorial: Manually Creating a DigitalOcean Droplet.
This guide assumes that you have a functioning Docker image where your Meltano project is already bundled with the Meltano installation. To track this issue, follow meltano#624.
In this section, we will be going over how you can deploy a Meltano Docker image to AWS.
Configurebutton in the custom card
Updatebutton to finish setting up your container defintion
Editnext to the Task defintion heading
Nextto move to the next step
Nextto move on to the next step
The main configuration here is the Cluster name. We provide a suggestion below, but feel free to name it as you wish.
After you click
Next, you will have the opportunity to review all of the properties that you set. Once you confirm that the settings are correct, click
Create to setup your ECS.
You should now see a page where Amazon prepares the services we configured. There will be spinning icons on the right of each service that will live update as it finished. Once you see everything has setup properly, you're cluster has been successfully deployed!
RUNNINGfor Last Status
The IP address can be mapped to a domain using Route53. We will be writing up a guide on how to do this. You can follow along at meltano#625.
This section is only necessary if you do not have a Security Group that allows for port 5000,5010 inbound.
Once you complete the cluster setup, you should be brought to the detail page for the service. You should be default on a tab called Details with a Network Access section.
Add Rulewith the following properties:
In this section, we will install Meltano as an application you can access locally from your browser and on the command line. If you prefer to install to Docker, please view the installation instructions here.
We do not have a double click installer at this time, but it is in our roadmap and we will be sure to update this page when we do!
Before you install Meltano, make sure you have the following requirements installed and up to date.
You may refer to https://realpython.com/installing-python/ for platform specific installation instructions.
To check if you have the correct Python version, open your terminal and use the following commands to check the version:
If you've installed Python 3, but are not getting the result you expect, you may have installed Python 3 alongside an existing Python 2 installation. In this case, please use
pip3 wherever this guide refers to the
pip is a package installer that comes automatically with Python 3+. This is also what we will be using to install Meltano. Here are some commands related to
pip that may be of interest:
# Check for current version of pip pip --version # Update pip pip install --upgrade pip
If you installed Python 3 alongside an existing Python 2 installation, you'll want to use
Unless you are building a Docker image, It is strongly recommended that Meltano be installed inside a virtual environment in order to avoid potential system conflicts that may be difficult to debug.
Why use a virtual environment?
Your local environment may use a different version of Python or other dependencies that are difficult to manage. The virtual environment provides a "clean" space to work without these issues.
We suggest you create a directory where you want your virtual environments to be saved, e.g.:
Then create a new virtual environment inside that directory:
# Linux, macOS mkdir ~/virtualenvs python -m venv ~/virtualenvs/meltano # Windows mkdir %ALLUSERSPROFILE%\\virtualenvs python -m venv %ALLUSERSPROFILE%\\virtualenvs\\meltano
Activate the virtual environment using:
# Linux, macOS source ~/virtualenvs/meltano/bin/activate # Windows %HOME%\\virtualenvs\\meltano\\Scripts\\activate.bat
If the virtual environment was activated successfully, you'll see a
(meltano) indicator added to your prompt.
Once a virtual environment is activated, it stays active until the current shell is closed. In a new shell, you must re-activate the virtual environment before interacting with the
meltano command that will be installed in the next step.
To streamline this process, you can define a shell alias that'll be easier to remember than the entire activation invocation:
# Add to `~/.bashrc`, `~/.zshrc`, etc, depending on the shell you use: alias meltano!="source ~/virtualenvs/meltano/bin/activate" # Use as follows, after creating a new shell: meltano!
Now that you have your virtual environment set up and running, run the following command to install the Meltano package:
pip install meltano
Once the installation completes, you can check if it was successful by running:
That's it! Meltano is now be available for you to use.
Now that you have successfully installed Meltano and its requirements, you can create your first project.
To initialize a new project, open your terminal and navigate to the directory that you'd like to store your Meltano projects in.
Next, to create your project, you will use the
meltano init command which takes a
PROJECT_NAME that is of your own choosing. For this guide, let's create a project called "meltano-carbon."
Meltano shares anonymous usage data with the team through Google Analytics. This is used to help us learn about how Meltano is being used to ensure that we are making Meltano even more useful to our users.
If you would prefer to use Meltano without sending the team this data, learn how to configure this through our environment variables docs.
meltano init meltano-carbon
This will create a new directory named
meltano-carbon and initialize Meltano's basic directory structure inside it.
Now that you've created your first Meltano project, let's change directory to our new project and start Meltano UI:
cd meltano-carbon meltano ui
Meltano is now running and should open a new tab at http://localhost:5000.
You are now ready to add data sources, configure reporting databases, schedule updates and build dashboards!
Docker is an alternative installation option to using a virtual environment to run Meltano. To use these instructions you will need to install Docker onto your computer and have it running when you execute the commands below.
We provide the meltano/meltano docker image with Meltano pre-installed and ready to use.
Note: The meltano/meltano docker image is also available in GitLab's registry:
This image contains everything you need to get started with Meltano.
# download or update to the latest version docker pull meltano/meltano # look the currently installed version docker run meltano/meltano --version
Once you have Docker installed, running, and have pulled the pre-built image you can use Meltano just as you would in our Getting Started Guide. However, the command line syntax is slightly different. For example, let's create a new Meltano project:
docker run -v $(pwd):/projects \ -w /projects \ meltano/meltano init YOUR_PROJECT_NAME
Then you can
cd into your new project:
We can then start the Meltano UI. Since
ui is the default command, we can omit it.
docker run -v $(pwd):/project \ -w /project \ -p 5000:5000 \ meltano/meltano
You can now visit http://localhost:5000 to access the Meltano UI.
If you are a Meltano end-user who is not going to be contributing code to our open source repository, you should be able to use Meltano entirely from the UI at this point.
Follow the steps in our Getting Started Guide to get started.
Here are some example of CLI commands you may need to run if you are working with Meltano as an open source contributor:
To run the ELT and extract some data from the tap-carbon-intensity into target-sqlite:
docker run -v $(pwd):/project \ -w /project \ meltano/meltano elt tap-carbon-intensity target-sqlite
Now that we have data in your database, let's add the corresponding model bundle as the basis of our analysis.
docker run -v $(pwd):/project \ -w /project \ meltano/meltano add model model-carbon-intensity-sqlite
We release new versions of Meltano weekly. To update Meltano to the latest version, run the following command in your terminal:
pip install --upgrade meltano
Are you having installation or deployment problems? We are here to help you. Please fill out this issue template and we'll get back to you as soon as we can!