Benthos is a high performance and resilient stream processor, able to connect various sources and sinks and perform arbitrary actions, transformations and filters on payloads. It is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary or a docker image.

Stream pipelines are defined in a single config file, allowing you to declare connectors and a list of processing stages:

input:
  kafka_balanced:
    addresses: [ TODO ]
    topics: [ foo, bar ]
    consumer_group: foogroup

pipeline:
  threads: 4
  processors:
  - jmespath:
      query: '{ message: @, meta: { link_count: length(links) } }'

output:
  s3:
    bucket: TODO
    path: "${!metadata:kafka_topic}/${!json_field:message.id}.json"

Delivery Guarantees

Benthos implements transaction based resiliency with back pressure. When connecting to at-least-once sources and sinks it guarantees at-least-once delivery without needing to persist messages during transit.

When running a Benthos stream with a buffer there are various options for choosing a level of resiliency that meets your needs.

Serverless

There are also specialised distributions of Benthos for serverless deployment.

Supported Sources & Sinks

• AWS (DynamoDB, Kinesis, S3, SQS, SNS)
• Elasticsearch (output only)
• File
• GCP (pub/sub)
• HDFS
• HTTP(S)
• Kafka
• Memcached (output only)
• MQTT
• Nanomsg
• NATS
• NATS Streaming
• NSQ
• RabbitMQ (AMQP 0.91)
• Redis (streams, list, pubsub, hashes)
• Stdin/Stdout
• TCP & UDP
• Websocket
• ZMQ4

Documentation

Documentation for Benthos components, concepts and recommendations can be found on the documentation site, or within the repo at the docs directory.

For guidance on how to configure more advanced stream processing concepts such as stream joins, enrichment workflows, etc, check out the cookbooks section.

For guidance on building your own custom plugins check out this example repo.

Run

benthos -c ./config.yaml

Or, with docker:

# Send HTTP /POST data to Kafka:
docker run --rm \
	-e "INPUT_TYPE=http_server" \
	-e "OUTPUT_TYPE=kafka" \
	-e "OUTPUT_KAFKA_ADDRESSES=kafka-server:9092" \
	-e "OUTPUT_KAFKA_TOPIC=benthos_topic" \
	-p 4195:4195 \
	jeffail/benthos

# Using your own config file:
docker run --rm -v /path/to/your/config.yaml:/benthos.yaml jeffail/benthos

Monitoring

Health Checks

Benthos serves two HTTP endpoints for health checks:

• /ping can be used as a liveness probe as it always returns a 200.
• /ready can be used as a readiness probe as it serves a 200 only when both the input and output are connected, otherwise a 503 is returned.

Metrics

Benthos exposes lots of metrics either to Statsd, Prometheus or for debugging purposes an HTTP endpoint that returns a JSON formatted object. The target can be specified via config.

Tracing

Benthos also emits opentracing events to a tracer of your choice (currently only Jaeger is supported) which can be used to visualise the processors within a pipeline.

Configuration

Benthos provides lots of tools for making configuration discovery, debugging and organisation easy. You can read about them here.

You can also find runnable example configs demonstrating each input, output, buffer and processor option here.

Environment Variables

It is possible to select fields inside a configuration file to be set via environment variables. The docker image, for example, is built with a config file where all common fields can be set this way.

Install

Grab a binary for your OS from here.

Or pull the docker image:

docker pull jeffail/benthos

On macOS, Benthos can be installed via Homebrew:

brew install benthos

Build with Go (1.11 or later):

git clone git@github.com:Jeffail/benthos
cd benthos
make

Plugins

It's pretty easy to write your own custom plugins for Benthos, take a look at this repo for examples and build instructions.

Docker Builds

There's a multi-stage Dockerfile for creating a Benthos docker image which results in a minimal image from scratch. You can build it with:

make docker

Then use the image:

docker run --rm \
	-v /path/to/your/benthos.yaml:/config.yaml \
	-v /tmp/data:/data \
	-p 4195:4195 \
	benthos -c /config.yaml

There are a few examples here that show you some ways of setting up Benthos containers using docker-compose.

ZMQ4 Support

Benthos supports ZMQ4 for both data input and output. To add this you need to install libzmq4 and use the compile time flag when building Benthos:

make TAGS=ZMQ4

Or to build a docker image using CGO, which includes ZMQ:

make docker-cgo

Contributing

Contributions are welcome, please read the guidelines, come and chat in the #benthos Gophers slack channel (get an invite), and watch your back.