Tutorials
This GitHub repo has the source code for Kafka Tutorials. Read about it in our blog post.
Setup
If you want to hack on this site to add a new tutorial or make a change, follow these instructions.
Prerequisites
The following prerequisites are only required if you are going to run the microsite locally. If you are interested in testing tutorials locally see the Testing Locally section of the README.
- ruby 2.3 or later
- bundler
- npm
- python3 / pip3
- gradle
- Docker Compose
On a Mac, you can get the dependencies like this:
brew install ruby node
gem install bundler
You'll now have an executable called harness-runner on your path. (Note that if you use Python, you likely already have the pyyaml
package installed.)
Installing
1. Clone this repository
git clone [email protected]:confluentinc/kafka-tutorials.git
Then cd
into the directory.
2. Install the node packages
npm install
This will bring in some external JavaScript and CSS packages that we're using.
3. Install the gems
bundle install
This will install Jekyll itself and any other gems that we use.
4. Run the development server
bundle exec jekyll serve --livereload --baseurl /tutorials
This will launch a web server so that you can work on the site locally. Check it out on http://localhost:4000/tutorials/
.
5. Install the Pip package
This repository uses a Python package to facilitate testing the tutorials. To keep things simple, we bundled it into this repository. You can get everything you need by running the following:
pip3 install pyyaml
cd harness_runner
pip3 install -e .
6. Running the tests locally
You can run any of the automated tests locally using a command like:
cd ..
make -C _includes/tutorials/filtering/ksql/code tutorial
Substituting in the appropriate tutorial path.
Note: if you are testing unreleased ksqlDB Docker images, you will need to be logged in to AWS ECR.
Add code for a new tutorial
A tutorial is a short procedure, targeted at developers, for getting a certain thing done using Confluent Platform.
In many cases, you can get that thing done using one of several stacks. For example, you might be able to perform data filtering by writing a KSQL query, by writing a Kafka Streams application, or by directly using the Kafka Consumer API. These comprise the three stacks this site supports: ksql
, kstreams
, and kafka
.
These Tutorials are a bit unique in that each tutorial is self-testing. That is, we have built a light-weight harness system that's able to instrument the code that belongs to each tutorial to make sure that it actually works. This is really useful as we expect to have a lot of tutorials.
With in each stack, these tutorials contain a few pieces. These are described below.
Using tutorial author tools
There are several pieces that you will put together for a tutorial. Aside from the original content you need to provide (tutorial description, actual tutorial content, code, etc.), all of the steps described below can be automated. You accomplish tutorial automation via one of two scripts in the tools
directory
gen_project.sh
clone_tutorial.sh
Let's describe each script.
gen_project.sh
script
The As the name implies, the gen_project.sh
script generates the minimal structure for a viable tutorial. The code and text contained in the tutorial are place holders, and you'll update those with your code and writing to complete the tutorial.
The script expects you to supply a properties file for setting the name and other parts of the tutorial. Here's an example properties file you can use.
#!/bin/sh
# space-separated list of types could be one of ksql or kstreams
CARDS="kstreams ksql"
# all lower-case with no spaces
TUTORIAL_SHORT_NAME=my-tutorial-name
# the MAIN_CLASS variable will generate a test named MAIN_CLASSTest
MAIN_CLASS=FilteringCode
AK_VERSION=3.1.0
CP_VERSION=7.3.0
KSQLDB_VERSION=0.28.2
SEMAPHORE_TEST_NAME="Test name for Semaphore run"
PERMALINK="seo-friendly-link-to-my-tutorial"
To run this script:
- Create a branch
- Make sure you are in the
kafka-tutorials
base directory - Execute
./tools/gen_project.sh my_tutorial_props.sh
You'll see a lot of information scroll across the screen, describing each step of the tutorial generation process. The last part of the information presented is a checklist of what you'll need to do to complete your tutorial, aside from adding your code and tutorial text.
Your tutorial, my-tutorial-name, has been generated successfully!
The script adds a copy of this checklist to the my-tutorial-name directory.
There are some additional steps you'll need to take to complete the tutorial:
- Update the following entries in _data/tutorials.yaml file a. title b. meta-description c. canonical (optional: preferred version of a page) d. question e. introduction
You can find these fields by searching for my-tutorial-name in the _data/tutorials.yaml file.
-
Add the new tutorial to the tutorials/recipes landing page in Contentful.
-
For completeness, update the link text then add the following link(s) to the index.html file in the appropriate section:
<li><a href="seo-friendly-link-to-my-tutorial/kstreams.html">MEANINGFUL LINK TEXT HERE</a></li>
<li><a href="seo-friendly-link-to-my-tutorial/ksql.html">MEANINGFUL LINK TEXT HERE</a></li>
If you only specified one tutorial type (ksql
or kstreams
) then you'd only have one link in the output. Also, a copy of this output is copied in your tutorial directory /Tutorials base dir/_includes/tutorials/you_tutorial_short_name
clone-tutorial.sh
script
The As the name implies, this script creates a clone of an existing tutorial. The clone script changes the name of the tutorial throughout the content. To clone a tutorial, you also need to provide a properties file
#!/bin/sh
#SAMPLE-PROPERTIES-FILE-CONTENT
# By using the basename of a tutorial everything is cloned possibly ksql, kstreams, and kafka
ORIG_TUTORIAL=connect-add-key-to-source
# to only clone a kafka tutorial
ORIG_TUTORIAL=console-consumer-producer-basic/kafka
# to clone just the ksql part
ORIG_TUTORIAL=connect-add-key-to-source/ksql
# to clone just the kstreams portion
ORIG_TUTORIAL=connect-add-key-to-source/kstreams
!!!! IMPORTANT YOU MUST ONLY HAVE ONE ORIG_TUTORIAL VARIABLE !!!!
# Add a new tutorial name
NEW_TUTORIAL=junkA
# Add a new sempahore test name
SEMAPHORE_TEST_NAME="My New Junk Tutorial"
# Add a new PERMALINK
PERMALINK=a-junk-tutorial
To clone a tutorial:
- Create a branch
- Make sure you are in the
kafka-tutorials
base directory - Execute
./tools/clone_tutorial.sh my-clone-tutorial-props.sh
You'll see a similar output scroll across the screen, including the checklist for items you'll need to do for a completed tutorial.
Which script to use?
How do you decide which script to run? If you are creating a new tutorial that does not resemble an existing tutorial, then the gen_project
script is probably the better way to go. If you are creating a tutorial that is closely related to a current tutorial, a hopping-windows tutorial, when there is already a tumbling-windows tutorial, for example, then the clone approach is probably better.
It's still valuable to read through the next section to learn how all the tutorial pieces fit together.
Description of tutorial parts
If you used the clone script then many of these will already exist and will just need customising for your particular tutorial.
1. Describe the question your tutorial answers
The first thing to do is articulate what question your tutorial is meant to answer. Every tutorial contains a question and an example scenario. Edit _data/tutorials.yml
and add your entry. The top item in this file represents the short name for your tutorial. For example, the tutorial for transforming events of a stream is transforming. You'll also notice a status
attribute. You can enable
as many stacks as you'd like to author for this tutorial, but we recommend starting with just one.
2. Make the directory structure
Next, make a few directories to set up for the project:
mkdir _includes/tutorials/<your tutorial short name>/<stack>/code
mkdir _includes/tutorials/<your tutorial short name>/<stack>/markup
3. Write the code for the tutorial
Add your code for the tutorial under the code/
directory you created. This should be entirely self-contained and executable with a docker-compose.yml
file and a platform-appropriate build. Follow the conventions of existing tutorials as closely as possible.
At this point, you should feel free to submit a PR! A member of Confluent will take care of writing the markup and test files to integrate your code into the site. You can, of course, proceed to the next section and do it yourself, if you'd like.
Add a narrative and test for the tutorial
This section is generally for those who work at Confluent and will be integrating new tutorials into the site. We need to do a little more work than just authoring the code. We also need to write the markup to describe the tutorial in narrative form, and also write the tests that we described to make sure it all works. This section describes how to do that.
1. Create a harness for the tutorial
The harness is the main data structure that allows us to both test and render a tutorial from one form. Make a new directory under _data/harnesses/
for your tutorial slug name and stack, like _data/harnesses/<your tutorial short name>/ksql.yml
. Follow the existing harnesses to get a feel for what this looks like. The main thing to notice is that each step has a render
attribute that points to a file. Create the markup for this in the next section.
2. Create markup for the tutorial
Under the markup/
directory that was created earlier, create 3 subdirectories: dev
, test
, and prod
. Write the tutorial prose content here, following the conventions of existing tutorials. These files should be authored in Asciidoc.
3. Tie it all together
Make a file named /tutorials/<your tutorial short name>/<stack>.html
, specifying all the variables of interest. Note: the directory structure for these files is distinct from /_includes/tutorials
.
For example, to display the tutorial with the ksqlDB stack:
# /tutorials/filter-a-stream-of-events/ksql.html
---
layout: tutorial
permalink: /tutorials/filter-a-stream-of-events/ksql
stack: ksql
static_data: filtering
---
You can do the same for Kafka Streams and Kafka, by using the kstreams
and kafka
stacks, respectively.
4. Add your tutorial into build system
Lastly, create a Makefile in the code
directory to invoke the harness runner and check any outputs that it produces. Then modify the .semaphore/semaphore.yml
file to invoke that Makefile. This will make sure your tutorial gets checked by the CI system.
Testing Locally
Each tutorial shows how to manually execute each tutorial step-by-step. However, there are some scenarios when a user may want to run and test a tutorial in a more automated fashion:
- End-to-end: user makes a small change to the code and wants to validate that the tutorial still works end-to-end
- Run-and-play: user runs a tutorial and wants to leave it running to play with the environment
This section describes how you can do either of these scenarios using the harness-runner
to programmatically run a single tutorial.
Prerequisites
The following prerequisites are required if you are going to run a tutorial programmatically.
- python3 / pip3
- gradle
- Docker Compose
Environment Setup
- Check out the kafka-tutorials GitHub repo:
git clone https://github.com/confluentinc/kafka-tutorials.git
cd kafka-tutorials
- Install the packages for the harness runner.
If you have pip3
installed locally:
(cd /harness_runner/ && pip3 install -e .)
If you don't have pip3
installed locally, create a Dockerfile
with the following content:
FROM python:3.7-slim
RUN pip3 install pyyaml
and then run the following command to build and execute the Docker image:
docker build -t runner . ; docker run -v ${PWD}/harness_runner:/harness_runner/ -it --rm runner bash -c 'cd /harness_runner/ && pip3 install -e .'
-
Install gradle for tutorials that compile any code.
-
Install Docker Compose
Run a tutorial
- (optional) If you want to augment or override a tutorial's Docker environment, set the Docker Compose CLI environment variable
COMPOSE_FILE
to includedocker-compose.yml
and the absolute path to adocker-compose.override.yml
file. For example, to use Confluent Control Center with any tutorial, setCOMPOSE_FILE
todocker-compose.yml
and the absolute path to this docker-compose.override.yml.
export COMPOSE_FILE=docker-compose.yml:<path to tutorials>/tools/docker-compose.override.yml
- End-to-end: execute the harness runner for a single tutorial by calling
make
, across alldev
,test
, andprod
stages, to validate it works end-to-end. Identify the tutorial you want and then runmake
. Note that this destroys all the resources and Docker containers it created, so it cleans up after itself. Format:(cd _includes/tutorials/<tutorial name>/<type>/code && make)
where type is one ofksql | kstreams | kafka
. Example:
(cd _includes/tutorials/transforming/kstreams/code/ && make)
- Run-and-play: execute the harness runner for a single tutorial by calling
make SEQUENCE='"dev, test"'
, just acrossdev
andtest
stages, which leaves all resources and Docker containers running so you can then play with it. Format:(cd _includes/tutorials/<tutorial name>/<type>/code && make SEQUENCE='"dev, test"')
where type is one ofksql | kstreams | kafka
. Example:
(cd _includes/tutorials/transforming/kstreams/code/ && make SEQUENCE='"dev, test"')
Now you can play with the environment, some sample commands shown below.
docker exec -t broker kafka-topics --list --bootstrap-server localhost:9092
docker exec -it ksqldb-cli ksql http://ksqldb-server:8088
Because the Docker containers are left running, don't forget to clean up when you are done.
docker container ls
docker container rm -f <container id>
Makefile Details
The Makefile
will delete and re-create the outputs
directory used to contain files with output from various steps used to verify the tutorial steps.
Here is the contents of an actual Makefile
:
STEPS_DIR := tutorial-steps
DEV_OUTPUTS_DIR := $(STEPS_DIR)/dev/outputs
TEMP_DIR := $(shell mktemp -d)
tutorial:
rm -r $(DEV_OUTPUTS_DIR) || true
mkdir $(DEV_OUTPUTS_DIR)
harness-runner ../../../../../_data/harnesses/fk-joins/kstreams.yml $(TEMP_DIR)
diff --strip-trailing-cr $(STEPS_DIR)/dev/expected-output-events.json $(DEV_OUTPUTS_DIR)/music-interest.json
The last line uses the diff
command to validate expected output against the tutorial steps' actual output. The Makefile
may have more than one validation action to have separate diff
commands for each verification.
For example, here's the Makefile
from the dynamic output topics tutorial
STEPS_DIR := tutorial-steps
DEV_OUTPUTS_DIR := $(STEPS_DIR)/dev/outputs
TEMP_DIR := $(shell mktemp -d)
tutorial:
rm -r $(DEV_OUTPUTS_DIR) || true
mkdir $(DEV_OUTPUTS_DIR)
harness-runner ../../../../../_data/harnesses/dynamic-output-topic/kstreams.yml $(TEMP_DIR)
diff --strip-trailing-cr $(STEPS_DIR)/dev/expected-output.json $(DEV_OUTPUTS_DIR)/actual-output.json
diff --strip-trailing-cr $(STEPS_DIR)/dev/expected-special-output.json $(DEV_OUTPUTS_DIR)/actual-special-order-output.json
Harness Details
Given that the test harness is the heart
of a tutorial, it will be helpful to describe in detail how to work with a kafka|ksql|kstreams.yml
file. You should note the harness file is in the YAML file format, so formatting properly is essential. The harness files generate the rendered tutorial structure and validate any output of tutorial steps against expected values.
New tutorial authors should not need to create a harness file from scratch, using either the tools/gen_project.sh
or tools/clone.sh
script will provide a usable harness file. This section should provide enough guidance to add, update, or remove parts as needed.
1. Structure
Three top-level sections make up the harness file:
- dev - the setup and teaching portion of the tutorial (required)
- test - test setup and execution of tests, if any (optional)
- prod - steps to build and deploy a docker image of the tutorial code (optional)
In some cases, having a test and/or prod section doesn't make sense, so you can omit those portions of the harness file. The Apache Kafka console producer and consumer basic operations and the Apache Kafka console consumer with primitive keys and values tutorials are an excellent example of tutorials that don't need a test or prod section.
The dev
, test
, and prod
sections contain a top-level element steps
. The steps
contains any number of well, steps for the user to walk through. Additionally, the harness_runner
script follows the same steps for executing the tutorial automatically during builds. All sections contain the same step structure, so we'll only discuss the make-up of a single section.
For reference here is an example section of the harness file from the console consumer primitive keys and values tutorial
- title: Get Confluent Platform
content:
- action: make_file
file: docker-compose.yml
render:
file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/make-docker-compose.adoc
- action: execute_async
file: tutorial-steps/dev/docker-compose-up.sh
render:
file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/start-compose.adoc
- action: execute
file: tutorial-steps/dev/wait-for-containers.sh
render:
skip: true
- name: wait for ksqldb-server and connectors
action: sleep
ms: 30000
render:
skip: true
-
Title - each section starts with a
title
element, and as the label suggests, the text provided here is the text used the label the step for the tutorial user and the output to the console by the harness runner. Thetitle
section contains one element -content
-
content - the
content
section (a YAMLdictionary
) contains an arbitrary sized list of YAML dictionaries namedaction
. Anaction
key creates an anonymous step, i.e., not specified in the test runner's output. For output in the test runner, you can provide a-name
key, followed by some text for console output. -
action -
action
keys drive the behavior of the harness. An action key can be one of these valuesaction: make_file
- Prompts the user to create a file for the tutorial.action: execute
- a synchronous action stepaction: execute_async
- an asynchronous step, this indicates a step the user will keep running for some portion of the tutorial.action: sleep
- pause the test runner for an amount of time specified by thems
key. You usesleep
key to allow some async action to completems: NNN
- the time in milliseconds you want the test harness to pause execution. You only usems
after anaction: sleep
entry.
docker_ksql_cli_session
- an action starting a ksqlDB CLI session for working through a tutorial
In the next sections, you'll see how to use action
keys to organize your harness files.
2. Action type descriptions and examples
-
make_file
Themake_file
instructs the user to create a file an existing file required to run the tutorial. Some examples are thedocker-compose.yml
file, astatements.sql
(ksqlDB), and Java files.A
make_file
with a file to render look like this:- action: make_file file: docker-compose.yml render: file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/make-docker-compose.adoc
file:
the path and name to the file. The path is relative to<tutorial-name>/<type>/code>
.The harness runner will use the file during the automated tutorial execution.render:
the file to render. Therender
key has one of the two possible keys:file:
the path and name of the file to render to the user.
-
execute
Theexecute
step is a synchronous execution step during the tutorial for the user and the harness runner- action: execute file: tutorial-steps/dev/init.sh render: file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/init.adoc
Sometimes the
execute
step is an internal step only for the harness runner. Internal steps ignore therender:
using askip: true
entry- name: wait for ksqldb-server and connectors action: sleep ms: 30000 render: skip: true
The
execute
steps may also capture output from stdout for tests executed by the harness runner- title: Invoke the tests content: - action: execute file: tutorial-steps/test/run-tests.sh stdout: tutorial-steps/test/outputs/test-results.log render: file: tutorials/aggregating-sum/ksql/markup/test/run-tests.adoc
Here you can see the
stdout:
key specifying the file used to capture the output of anexecute
step. -
execute_async
Theexecute_async
step is for steps needing to execute in the background while the user continues going through the tutorialHere's an example of running
docker compose
to start docker containers to run the duration of the tutorial- action: execute_async file: tutorial-steps/dev/docker-compose-up.sh render: file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/start-compose.adoc
Here's another example of using a console consumer. Note the use of
stdout:
to capture the output from the consumer for testing.- title: Start an initial console consumer content: - action: execute_async file: tutorial-steps/dev/harness-console-consumer-keys.sh stdout: tutorial-steps/dev/outputs/actual-output-step-one.txt render: file: tutorials/console-consumer-primitive-keys-values/kafka/markup/dev/consume-topic-no-deserializers.adoc
-
docker_ksql_cli_session
Thedocker_ksql_cli_session
sets up ksqlDB tutorial users to start a ksqlDB CLI session so the user can execute variousSQL
files to complete the tutorial.- action: docker_ksql_cli_session container: ksqldb-cli docker_bootup_file: tutorial-steps/dev/start-cli.sh column_width: 20 render: file: tutorials/aggregating-sum/ksql/markup/dev/start-cli.adoc
The
docker_ksql_cli_session
contains the following keys:container:
- The name of the ksqldb-cli docker image in the docker-compose.yml file.docker_bootup_file:
- Tutorial users and the harness runner execute this file to start the dockerized CLI session.column_width:
- Formats the ksqlDB query outputrender:
- The harness renders the file corresponding to thefile:
key to tutorial users with the command to start the CLI session.stdin:
- stdin key contains one or morefile
keys specifying the differentSQL
file to execute for the tutorial.
stdin: - file: tutorial-steps/dev/create-movie-ticket-sales.sql render: file: tutorials/aggregating-sum/ksql/markup/dev/create-movie-ticket-sales.adoc - file: tutorial-steps/dev/populate-movie-ticket-sales.sql render: file: tutorials/aggregating-sum/ksql/markup/dev/populate-movie-ticket-sales.adoc
stdout:
- Containsdirectory:
specifying the directory to capture all query output.
Updating dependency versions
The following regular expressions may be useful to group-update all dependencies within the repo:
confluentinc\/cp-([^:]*):\d+.\d+.\d+
will match all Confluent Platform components, except ksqlDB. Capture group 1 can be used to build the component name.confluentinc\/ksqldb-([^:]*):\d+.\d+.\d+
will match all ksqlDB components. Capture group 1 can be used to build the component name.
Updating Tutorials
Confluent manages the release process and the process described here must be done by a Confluent employee.
The release
branch tracks the content and code comprising the live site.
The ksqldb-latest
branch builds against the latest master
branch of ksqlDB, and should be used for updates that are only in the master branch of ksqlDB.
Create a release PR
- Open a pull request from
master
torelease
. A pull request into therelease
branch denotes a request to update the live site.
- Title the PR “KT release [DD-MM-YYYY]”
- In the description add links to PRs that resulted in new tutorials, content changes, or any other noteworthy addition, e.g.:
This release contains:
New Tutorial! A fun new tutorial #1287
New recipe group for financial services use cases #1264
plus many other small fixes
- Add a link to the staging site with the updates (snag the staging site name from Semaphore's "Deploy to staging site" step)
- Tag reviewers
- Create PR
- The semaphore tests for the PR will automatically create the staging site. You can manually click to deploy to staging site if you trust that failing tests work (ksqlDB tests can be flaky sometimes).
-
Look at the staging site from different browsers. Ensure that you get approval from required reviewers. Submit PRs with fixes, if needed.
-
Once the PR is approved, merge the PR via
Merge commit
.
Deploy to live site
To deploy artifacts from the release
branch to the live site, it should be done from the release
branch, not the above PR. So do not deploy to live site
from the PR, because that would deploy from master
. Instead, go to the release
branch, let the tests pass, and then deploy
Landing page
The landing page is at https://developer.confluent.io/tutorials/ (it is not index.html), and the source for it is in Contentful. Any changes to the landing page should be worked through Confluent.