This document shows how to deploy a "Hello World" application with Draft. If you haven't done so already, be sure you have Draft installed properly. This Quickstart Guide is the perfect resource if you still need to install Draft.
There are multiple example applications included within the examples directory. For this walkthrough, we'll be using the python example application which uses Flask to provide a very simple Hello World webserver.
$ cd examples/example-python
$ draft create --> Draft detected Python (96.739130%) --> Ready to sail $ ls -a .dockerignore .draftignore app.py draft.toml .draft-tasks.toml Dockerfile charts/ requirements.txt
Dockerfile assets created by Draft default to a basic Python configuration. This
Dockerfile harnesses the python:onbuild image, which will install the dependencies in
requirements.txt and copy the current directory into
/usr/src/app. To align with the
internalPort service value in
Dockerfile exposes port 8080 from the container.
draft.toml file contains basic configuration details about the application like the name, the repository, which namespace it will be deployed to, and whether to deploy the application automatically when local files change.
$ cat draft.toml [environments] [environments.development] name = "example-python" namespace = "default" wait = true watch = false watch-delay = 2 auto-connect = false dockerfile = "" chart = ""
See dep-006.md for more information and available configuration on the
.draftignore file is created for elements we want to exclude tracking on
draft up when watching for changes. The syntax is identical to helm's .helmignore file.
$ cat .draftignore *.swp *.tmp *.temp .git*
.dockerignore file is created to ensure the docker context ignores files and directories that are not necessary.
$ cat .dockerignore Dockerfile draft.toml charts/
.draft-tasks.toml file is also created. This file allows you to configure tasks to be run before
draft up (
pre-up tasks), after
draft up (
post-up tasks), or after
draft delete (
post-delete tasks). This file is empty by default. See dep-008.md for more information and available configuration on the
Now we're ready to deploy this application to a Kubernetes cluster. Draft handles these tasks with one
draft up command:
- reads configuration from
- compresses the
charts/directory and the application directory as two separate tarballs
- builds the image using
dockerto push the image to the registry specified in
draft config get registry, if set)
helmto install the chart, referencing the image just built
$ draft up Draft Up Started: 'example-python': 01BSY5R8J45QHG9D3B17PAXMGN example-python: Building Docker Image: SUCCESS ⚓ (52.1337s) example-python: Releasing Application: SUCCESS ⚓ (0.5309s) Inspect the logs with `draft logs 01BSY5R8J45QHG9D3B17PAXMGN`
NOTE: You might see a
WARNING: no registry has been setmessage if no container registry has been configured in draft. You can set a container registry using the
draft config set registry docker.io/myusernamecommand. If you'd prefer to silence this warning instead, you can run
draft config set disable-push-warning 1.
To ensure your application deployed as expected, run
kubectl get pods and take a look at the output.
$ kubectl get pods NAME READY STATUS RESTARTS AGE example-python-python-6755c4944d-zbgvj 1/1 Running 0 5s
NOTE: If you're using Minikube and your
STATUSshows an error such as
ImagePullBackOff, make sure you've configured Draft to build images directly using Minikube's Docker daemon. You can do so by running
eval $(minikube docker-env).
INFO: For more information on installing and configuring Minikube for use with Draft, check out the Minikube installation guide here.
Interact with the Deployed Application
Now that the application has been deployed, we can connect to it using
draft connect command is used to interact with the application deployed on your cluster. It works by creating proxy connections to the ports exposed by the containers in your pod. It also streams the logs from all containers.
$ draft connect Connect to python:8080 on localhost:54794 [python]: * Environment: production [python]: WARNING: Do not use the development server in a production environment. [python]: Use a production WSGI server instead. [python]: * Debug mode: off [python]: * Running on http://0.0.0.0:8080/ (Press CTRL+C to quit)
WARNING: Do not use the development server in a production environmentmessage is coming from Flask. The message is in regard to Flask's built-in web server and can safely be ignored for our test purposes here.
In this example, you can see that
draft connect has proxied port 8080 from our container to port 54794 on localhost. We can now open a browser window or another terminal window and connect to our application using the address and port displayed from
draft connect's output.
$ curl localhost:54794 Hello, World!
IMPORTANT: Your local port will likely be different than the one seen here.
localhostdoes not resolve on your system, try
Once you're done checking the application out, you can cancel out of the
draft connect session using
NOTE: You can use the flag
draft up --auto-connectin order to have the application automatically connect once the deployment is done.
INFO: You can also customize the local ports for the
draft connectcommand by using the
-pflag or through the
draft.toml. More information on this can be found in dep-007.md.
Update the Application
Now, let's change the output in
app.py to output "Hello, Draft!" instead:
$ cat <<EOF > app.py from flask import Flask app = Flask(__name__) @app.route("/") def hello(): return "Hello, Draft!\n" if __name__ == "__main__": app.run(host='0.0.0.0', port=8080) EOF
When we call
draft up again, Draft determines that the Helm release already exists and will perform a
helm upgrade rather than attempting another
$ draft up Draft Up Started: 'example-python': 01CEQ5H21BWSR5M8HTJ5BVXPYW example-python: Building Docker Image: SUCCESS ⚓ (1.0010s) example-python: Releasing Application: SUCCESS ⚓ (2.1236s) Inspect the logs with `draft logs 01CEQ5H21BWSR5M8HTJ5BVXPYW`
We should notice a significantly faster build time here. This is because Docker is caching unchanged layers and only compiling layers that need to be rebuilt in the background.
We can run
draft connect again to set up a proxy to our application:
$ draft connect Connect to python:8080 on localhost:54961 [python]: * Environment: production [python]: WARNING: Do not use the development server in a production environment. [python]: Use a production WSGI server instead. [python]: * Debug mode: off [python]: * Running on http://0.0.0.0:8080/ (Press CTRL+C to quit)
Once we have the address and port, we can connect again using
curl in a new terminal window or by browsing to the host and port in a browser window:
$ curl localhost:54961 Hello, Draft!
We can see the application updated successfully!
If you're done testing this application, you can terminate and remove it from your Kubernetes cluster. To do so, run
$ draft delete app 'example-python' deleted
If you run
kubectl get pods shortly after, you should see your application
$ kubectl get pods NAME READY STATUS RESTARTS AGE example-python-python-688fcf849f-8ddh7 1/1 Terminating 0 5m
Once the termination completes, a
kubectl get pods will show that the application no longer exists in your Kubernetes cluster:
$ kubectl get pods No resources found.
IMPORTANT NOTE: The
draft deletecommand should be run with extreme care and caution as it performs a termination and removal of the application from your Kubernetes cluster.
draft deletecommand does not any image(s) created for the deployment within your Docker registry.