Bento is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads.
It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck.
Bento is declarative, with stream pipelines defined in as few as a single config file, allowing you to specify connectors and a list of processing stages:
input:
gcp_pubsub:
project: foo
subscription: bar
pipeline:
processors:
- mapping: |
root.message = this
root.meta.link_count = this.links.length()
root.user.age = this.user.age.number()
output:
redis_streams:
url: tcp://TODO:6379
stream: baz
max_in_flight: 20
Delivery guarantees can be a dodgy subject. Bento processes and acknowledges messages using an in-process transaction model with no need for any disk persisted state, so when connecting to at-least-once sources and sinks it's able to guarantee at-least-once delivery even in the event of crashes, disk corruption, or other unexpected server faults.
This behaviour is the default and free of caveats, which also makes deploying and scaling Bento much simpler.
AWS (DynamoDB, Kinesis, S3, SQS, SNS), Azure (Blob storage, Queue storage, Table storage), GCP (Pub/Sub, Cloud storage, Big query), Kafka, NATS (JetStream, Streaming), NSQ, MQTT, AMQP 0.91 (RabbitMQ), AMQP 1, Redis (streams, list, pubsub, hashes), Cassandra, Elasticsearch, HDFS, HTTP (server and client, including websockets), MongoDB, SQL (MySQL, PostgreSQL, Clickhouse, MSSQL), and you know what just click here to see them all, they don't fit in a README.
Connectors are being added constantly, if something you want is missing then open an issue.
If you want to dive fully into Bento then don't waste your time in this dump, check out the documentation site.
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 in Go check out the public APIs.
We're working on the release process, but you can either compile from source or pull the docker image:
docker pull public.ecr.aws/warpstream-labs/warpstream_bento:0.0.1-rc1
For more information check out the getting started guide.
bento -c ./config.yaml
Or, with docker:
# Using a config file
docker run --rm -v /path/to/your/config.yaml:/bento.yaml public.ecr.aws/warpstream-labs/warpstream_bento
# Using a series of -s flags
docker run --rm -p 4195:4195 public.ecr.aws/warpstream-labs/warpstream_bento \
-s "input.type=http_server" \
-s "output.type=kafka" \
-s "output.kafka.addresses=kafka-server:9092" \
-s "output.kafka.topic=bento_topic"
Bento 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.
Bento exposes lots of metrics either to Statsd, Prometheus, a JSON HTTP endpoint, and more.
Bento also emits open telemetry tracing events, which can be used to visualise the processors within a pipeline.
Bento provides lots of tools for making configuration discovery, debugging and organisation easy. You can read about them here.
Build with Go (any currently supported version):
git clone [email protected]:warpstreamlabs/bento
cd bento
make
go build -o bento ./cmd/bento/main.go
Bento uses golangci-lint for linting, which you can install with:
curl -sSfL https://raw.githubusercontent.com/golangci/golangci-lint/master/install.sh | sh -s -- -b $(go env GOPATH)/bin
And then run it with make lint
.
It's pretty easy to write your own custom plugins for Bento in Go, for information check out the API docs, and for inspiration there's an example repo demonstrating a variety of plugin implementations.
By default Bento does not build with components that require linking to external libraries, such as the zmq4
input and outputs. If you wish to build Bento locally with these dependencies then set the build tag x_bento_extra
:
# With go
go install -tags "x_bento_extra" github.com/warpstreamlabs/bento/v4/cmd/bento@latest
# Using make
make TAGS=x_bento_extra
Note that this tag may change or be broken out into granular tags for individual components outside of major version releases. If you attempt a build and these dependencies are not present you'll see error messages such as ld: library not found for -lzmq
.
There's a multi-stage Dockerfile
for creating a Bento 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/bento.yaml:/config.yaml \
-v /tmp/data:/data \
-p 4195:4195 \
bento -c /config.yaml
Contributions are welcome, please read the guidelines, come and chat (links are on the community page), and watch your back.