Getting Started

Woops! You fell for the marketing babble. Let's try and get through this together.

Install

The easiest way to install Benthos is with this handy script:

curl -Lsf https://sh.benthos.dev | bash

Or you can grab an archive containing Benthos from the releases page.

Docker

If you have docker installed you can pull the latest official Benthos image with:

docker pull jeffail/benthos
docker run --rm -v /path/to/your/config.yaml:/benthos.yaml jeffail/benthos

Homebrew

On macOS, Benthos can be installed via Homebrew:

brew install benthos

Serverless

For information about serverless deployments of Benthos check out the serverless section here.

Run

A Benthos stream pipeline is configured with a single config file, you can generate a fresh one with:

benthos create > config.yaml

The main sections that make up a config are input, pipeline and output. When you generate a fresh config it'll simply pipe stdin to stdout like this:

input:
type: stdin
pipeline:
processors: []
output:
type: stdout

Eventually we'll want to configure a more useful input and output, but for now this is useful for quickly testing processors. You can execute this config with:

benthos -c ./config.yaml

Anything you write to stdin will get written unchanged to stdout, cool! Resist the temptation to play with this for hours, there's more stuff to try out.

Next, let's add some processing steps in order to mutate messages. The most powerful one is the bloblang processor which allows us to perform mappings, let's add a mapping to uppercase our messages:

input:
type: stdin
pipeline:
processors:
- bloblang: root = content().uppercase()
output:
type: stdout

Now your messages should come out in all caps, how whacky! IT'S LIKE BENTHOS IS SHOUTING BACK AT YOU!

You can add as many processing steps as you like, and since processors are what make Benthos powerful they are worth experimenting with. Let's create a more advanced pipeline that works with JSON documents:

input:
type: stdin
pipeline:
processors:
- sleep:
duration: 500ms
- bloblang: |
root.doc = this
root.first_name = this.names.index(0).uppercase()
root.last_name = this.names.index(-1).hash("sha256").encode("base64")
output:
type: stdout

First, we sleep for 500 milliseconds just to keep the suspense going. Next, we restructure our input JSON document by nesting it within a field doc, we map the upper-cased first element of names to a new field first_name. Finally, we map the hashed and base64 encoded value of the last element of names to a new field last_name.

Try running that config with some sample documents:

echo '
{"id":"1","names":["celine","dion"]}
{"id":"2","names":["chad","robert","kroeger"]}' | benthos -c ./config.yaml

You should see (amongst some logs):

{"doc":{"id":"1","names":["celine","dion"]},"first_name":"CELINE","last_name":"1VvPgCW9sityz5XAMGdI2BTA7/44Wb3cANKxqhiCo50="}
{"doc":{"id":"2","names":["chad","robert","kroeger"]},"first_name":"CHAD","last_name":"uXXg5wCKPjpyj/qbivPbD9H9CZ5DH/F0Q1Twytnt2hQ="}

How exciting! I don't know about you but I'm going to need to lie down for a while. Now that you are a Benthos expert might I suggest you peruse these sections to see if anything tickles your fancy?