xk6-kafka

The xk6-kafka project is a k6 extension that enables k6 users to load test Apache Kafka using a producer and possibly a consumer for debugging.

The real purpose of this extension is to test the system you meticulously designed to use Apache Kafka. So, you can test your consumers, hence your system, by auto-generating messages and sending them to your system via Apache Kafka.

You can send many messages with each connection to Kafka. These messages are arrays of objects containing a key and a value in various serialization formats, passed via configuration objects. Various serialization formats are supported, including strings, JSON, binary, Avro, and JSON Schema. Avro and JSON Schema can either be fetched from Schema Registry or hard-code directly in the script. SASL PLAIN/SCRAM authentication and message compression are also supported.

For debugging and testing purposes, a consumer is available to make sure you send the correct data to Kafka.

If you want to learn more about the extension, see the article explaining how to load test your Kafka producers and consumers using k6 on the k6 blog.

Supported Features

Produce/consume messages as String, stringified JSON, ByteArray, Avro and JSON Schema format
Support for user-provided Avro and JSON Schema key and value schemas in the script
Authentication with SASL PLAIN and SCRAM
Create, list and delete topics
Support for loading Avro schemas from Schema Registry
Support for byte array for binary data (from binary protocols)
Support consumption from all partitions with a group ID
Support Kafka message compression: Gzip, Snappy, Lz4 & Zstd
Support for sending messages with no key
Support for k6 thresholds on custom Kafka metrics
Support for headers on produced and consumed messages
Lots of exported metrics, as shown in the result output of the k6 test script

Backward Compatibility Notice

If you want to keep up to date with the latest changes, please follow the project board. Also, since v0.9.0, the main branch is the development branch and usually has the latest changes and might be unstable. If you want to use the latest features, you might need to build your binary by following the build from source instructions. In turn, the tagged releases and the Docker images are more stable.

I make no guarantee to keep the API stable, as this project is in active development unless I release a major version. The best way to keep up with the changes is to follow the xk6-kafka API and look at the scripts directory.

CycloneDX SBOM

Since v0.9.0, CycloneDX SBOMs will be generated for go.mod and it can be accessed from the latest build of GitHub Actions for a tagged release, for example, this one. The artifacts are only kept for 90 days.

The Release Process

The main branch is the development branch, and the pull requests will be squashed and merged into the main branch. When a commit is tagged with a version, for example, v0.10.0, the build pipeline will build the main branch on that commit. The build process creates the binaries and the Docker image. If you want to test the latest unreleased features, you can clone the main branch and instruct the xk6 to use the locally cloned repository instead of using the @latest, which refers to the latest tagged version, as explained in the build for development section.

The Official Docker Image

Since v0.8.0, there is an official Docker image plus binaries in the assets. Before running your script, make it available to the container by mounting a volume (a directory) or passing it via stdin.

docker run --rm -i mostafamoradian/xk6-kafka:latest run - <scripts/test_json.js

The Official Binaries

Since v0.8.0, the build process creates the binary versions of xk6-kafka and publishes them on the releases page. It currently creates the binaries for GNU/Linux, macOS, and Windows on amd64 (x86_64) machines. If you want to see an official build for your machine, please build and test xk6-kafka from source and then create an issue with details. I'll add the specific binary to the build pipeline and publish them on the next release.

Build from Source

You can build the k6 binary on various platforms, each with its requirements. The following shows how to build k6 binary with this extension on GNU/Linux distributions.

Prerequisites

You must have the latest Go version installed to build the k6 binary. The latest version should match k6 and xk6. I recommend gvm because it eases version management.

gvm for easier installation and management of Go versions on your machine
Git for cloning the project
xk6 for building k6 binary with extensions

Install and build the latest tagged version

Feel free to skip the first two steps if you already have Go installed.

Install gvm by following its installation guide.
Install the latest version of Go using gvm. You need Go 1.4 installed for bootstrapping into higher Go versions, as explained here.
Install xk6:
```
go install go.k6.io/xk6/cmd/xk6@latest
```

Build the binary:

xk6 build --with github.com/mostafa/xk6-kafka@latest

Note You can always use the latest version of k6 to build the extension, but the earliest version of k6 that supports extensions via xk6 is v0.32.0. The xk6 is constantly evolving, so some APIs may not be backward compatible.

Build for development

If you want to add a feature or make a fix, clone the project and build it using the following commands. The xk6 will force the build to use the local clone instead of fetching the latest version from the repository. This process enables you to update the code and test it locally.

git clone git@github.com:mostafa/xk6-kafka.git && cd xk6-kafka
xk6 build --with github.com/mostafa/xk6-kafka@latest=.

Examples

There are many examples in the script directory that show how to use various features of the extension.

Run and Test

You can start testing your environment immediately, but it takes some time to develop the script, so it would be better to test your script against a development environment and then start testing your environment.

Development environment

I recommend the fast-data-dev Docker image by Lenses.io, a Kafka setup for development that includes Kafka, Zookeeper, Schema Registry, Kafka-Connect, Landoop Tools, 20+ connectors. It is relatively easy to set up if you have Docker installed. Just monitor Docker logs to have a working setup before attempting to test because the initial setup, leader election, and test data ingestion take time.

Run the Kafka environment and expose the container ports:

sudo docker run \
    --detach --rm \
    --name lensesio \
    -p 2181:2181 \
    -p 3030:3030 \
    -p 8081-8083:8081-8083 \
    -p 9581-9585:9581-9585 \
    -p 9092:9092 \
    -e ADV_HOST=127.0.0.1 \
    lensesio/fast-data-dev

After running the command, visit localhost:3030 to get into the fast-data-dev environment.
You can run the command to see the container logs:
```
sudo docker logs -f -t lensesio
```

If you have errors running the Kafka development environment, refer to the fast-data-dev documentation.

The xk6-kafka API

All the exported functions are available by importing them from k6/x/kafka. They are subject to change in future versions unless a new major version is released. The exported functions are available in the index.d.ts file, and they always reflect the latest changes on the main branch. You can access the generated documentation at docs/README.md.

k6 Test Script

The example scripts are available as test_<format/feature>.js with more code and commented sections in the scripts directory. The scripts usually have four parts:

The imports at the top show the exported functions from the Go extension and k6.
The Avro schema defines a key and a value schema that both producer and consumer use, according to the Avro schema specification. These are defined in the test_avro.js script.
The message producer:
1. The writer function opens a connection to the bootstrap servers. The first argument is an array of strings that signifies the bootstrap server addresses, and the second is the topic you want to write to. You can reuse this writer object to produce as many messages as possible. This object is created in the init code and is reused in the exported default function.
2. The produce function sends a list of messages to Kafka. The first argument is the producer object, and the second is the list of messages (with key and value). The third and the fourth arguments are the key schema and value schema in Avro format if the Avro format is used. The values are treated as normal strings if the schema are not passed to the function for either the key or the value. Use an empty string, "" if either the schema is Avro and the other will be a string. You can use the produceWithConfiguration function to pass separate serializer, deserializer, and schema registry settings, as shown in the test_avro_with_schema_registry.js script. The produce function returns an error if it fails. The check is optional, but error being undefined means that produce function successfully sent the message.
3. The producer.close() function closes the producer object (in tearDown).
The message consumer:
1. The reader function opens a connection to the bootstrap servers. The first argument is an array of strings that signifies the bootstrap server addresses, and the second is the topic you want to read from. This object is created in init code and is reused in the exported default function.
2. The consume function reads a list of Kafka's messages. The first argument is the consumer object, and the second is the number of messages to read in one go. The third and the fourth arguments are the key schema and value schema in Avro format if the Avro format is used. The values are treated as normal strings if the schema are not passed to the function for either the key or the value. Use an empty string, "" if either the schema is Avro and the other will be a string. You can use the consumeWithConfiguration function to pass separate serializer, deserializer, and schema registry settings, as shown in the test_avro_with_schema_registry js script. The consume function returns an empty array if it fails. The check is optional, but it checks to see if the length of the message array is exactly 10.
3. The consumer.close() function closes the consumer object (in tearDown).

You can run k6 with the Kafka extension using the following command:

./k6 run --vus 50 --duration 60s scripts/test_json.js

And here's the test result output:

          /\      |‾‾| /‾‾/   /‾‾/
     /\  /  \     |  |/  /   /  /
    /  \/    \    |     (   /   ‾‾\
   /          \   |  |\  \ |  (‾)  |
  / __________ \  |__| \__\ \_____/ .io

  execution: local
     script: scripts/test_json.js
     output: -

  scenarios: (100.00%) 1 scenario, 50 max VUs, 1m30s max duration (incl. graceful stop):
           * default: 50 looping VUs for 1m0s (gracefulStop: 30s)


running (1m00.1s), 00/50 VUs, 12064 complete and 0 interrupted iterations
default ✓ [======================================] 50 VUs  1m0s

     ✓ Messages are sent
     ✓ 10 messages are received
     ✓ Topic equals to xk6_kafka_json_topic
     ✗ Key is correct
      ↳  2% — ✓ 300 / ✗ 11764
     ✗ Value is correct
      ↳  4% — ✓ 500 / ✗ 11564
     ✓ Header equals {mykey: 'myvalue'}
     ✓ Time is past
     ✓ Partition is zero
     ✓ Offset is gte zero
     ✓ High watermark is gte zero

     █ teardown

     checks.........................: 98.22%  ✓ 1291648      ✗ 23328
     data_received..................: 0 B     0 B/s
     data_sent......................: 0 B     0 B/s
     iteration_duration.............: avg=248.98ms min=20.92µs med=246.77ms max=542.53ms p(90)=279.71ms p(95)=291.04ms
     iterations.....................: 12064   200.622726/s
     kafka.reader.dial.count........: 50      0.831493/s
     kafka.reader.dial.seconds......: avg=57.38µs  min=0s      med=0s       max=77.09ms  p(90)=0s       p(95)=0s
   ✓ kafka.reader.error.count.......: 0       0/s
     kafka.reader.fetch_bytes.max...: 1000000 min=1000000    max=1000000
     kafka.reader.fetch_bytes.min...: 1       min=1          max=1
     kafka.reader.fetch_wait.max....: 200ms   min=200ms      max=200ms
     kafka.reader.fetch.bytes.......: 0 B     0 B/s
     kafka.reader.fetch.size........: 0       0/s
     kafka.reader.fetches.count.....: 50      0.831493/s
     kafka.reader.lag...............: 7787    min=6515       max=11267
     kafka.reader.message.bytes.....: 24 MB   394 kB/s
     kafka.reader.message.count.....: 120690  2007.058751/s
     kafka.reader.offset............: 2440    min=11         max=2460
     kafka.reader.queue.capacity....: 1       min=1          max=1
     kafka.reader.queue.length......: 1       min=0          max=1
     kafka.reader.read.seconds......: avg=0s       min=0s      med=0s       max=0s       p(90)=0s       p(95)=0s
     kafka.reader.rebalance.count...: 0       0/s
     kafka.reader.timeouts.count....: 0       0/s
     kafka.reader.wait.seconds......: avg=24.61µs  min=0s      med=0s       max=62.83ms  p(90)=0s       p(95)=0s
     kafka.writer.acks.required.....: -1      min=-1         max=0
     kafka.writer.async.............: 0.00%   ✓ 0            ✗ 1206400
     kafka.writer.attempts.max......: 0       min=0          max=0
     kafka.writer.batch.bytes.......: 264 MB  4.4 MB/s
     kafka.writer.batch.max.........: 1       min=1          max=1
     kafka.writer.batch.size........: 1206400 20062.272574/s
     kafka.writer.batch.timeout.....: 0s      min=0s         max=0s
   ✓ kafka.writer.error.count.......: 0       0/s
     kafka.writer.message.bytes.....: 528 MB  8.8 MB/s
     kafka.writer.message.count.....: 2412800 40124.545147/s
     kafka.writer.read.timeout......: 0s      min=0s         max=0s
     kafka.writer.retries.count.....: 0       0/s
     kafka.writer.wait.seconds......: avg=0s       min=0s      med=0s       max=0s       p(90)=0s       p(95)=0s
     kafka.writer.write.count.......: 2412800 40124.545147/s
     kafka.writer.write.seconds.....: avg=1.18ms   min=94.91µs med=1.01ms   max=43.7ms   p(90)=1.46ms   p(95)=1.92ms
     kafka.writer.write.timeout.....: 0s      min=0s         max=0s
     vus............................: 50      min=50         max=50
     vus_max........................: 50      min=50         max=50

Troubleshooting

To avoid getting the following error while running the test:

Failed to write message: [5] Leader Not Available: the cluster is in the middle of a leadership election and there is currently no leader for this partition and hence it is unavailable for writes

You can now use createTopic function to create topics in Kafka. The scripts/test_topics.js script shows how to list topics on all Kafka partitions and create a topic.

You always have the option to create it using kafka-topics command:

$ docker exec -it lensesio bash
(inside container)$ kafka-topics --create --topic xk6_kafka_avro_topic --bootstrap-server localhost:9092
(inside container)$ kafka-topics --create --topic xk6_kafka_json_topic --bootstrap-server localhost:9092

If you want to test SASL authentication, look at this commit message, where I describe how to run a test environment.

Contributions, Issues and Feedback

I'd be thrilled to receive contributions and feedback on this project. You're always welcome to create an issue if you find one (or many). I'd do my best to address the issues. Also, feel free to contribute by opening a PR with changes, and I'll do my best to review and merge it as soon as I can.

Disclaimer

This project was a proof of concept but seems to be used by some companies nowadays. However, it isn't supported by the k6 team, but rather by me personally, and the APIs may change in the future. USE AT YOUR OWN RISK!

This project is licensed under the Apache License 2.0.

enamrik / xk6-kafka