Building a Continuous Deployment Pipeline Using LKE (Part 2): Sample Application

Slide deck: Cloud Native Continuous Deployment with GitLab, Helm, and Linode Kubernetes Engine: Our Sample Application (Slide #24)

The sample application that we’ll be running on Kubernetes is called DockerCoins (a demo app just for this presentation). This part of the guide will take a look at DockerCoins and examine how it works and how the app can be run locally.

• Main guide: Building a Continuous Deployment Pipeline Using LKE
• Previous section: Part 1: Get Ready
• Next section: Part 3: Deploying the LKE Cluster

Here’s a copy of the text contained within this section of the presentation. A link to the source file can be found within each slide of the presentation. Some formatting may have been changed.

• I’m going to run our demo app locally, with Docker (you don’t have to do that; do it if you like!)
• Clone the repository: git clone https://github.com/jpetazzo/container.training. You can also fork the repository on GitHub and clone your fork if you prefer that.

Let’s start this before we look around, as downloading will take a little time…

• Go to the dockercoins directory, in the cloned repo: cd container.training/dockercoins
• Use Compose to build and run all containers: docker-compose up

Compose tells Docker to build all container images (pulling the corresponding base images), then starts all containers, and displays aggregated logs.

• It is a DockerCoin miner! .emoji[💰🐳📦🚢]
• No, you can’t buy coffee with DockerCoins
• How DockerCoins works:
  • generate a few random bytes
  • hash these bytes
  • increment a counter (to keep track of speed)
  • repeat forever!
• DockerCoins is not a crypto-currency (the only common points are “randomness,” “hashing,” and “coins” in the name)

• DockerCoins is made of 5 services:
  • rng = web service generating random bytes
  • hasher = web service computing hash of POSTed data
  • worker = background process calling rng and hasher
  • webui = web interface to watch progress
  • redis = data store (holds a counter updated by worker)
• These 5 services are visible in the application’s Compose file, docker-compose.yml

• worker invokes web service rng to generate random bytes
• worker invokes web service hasher to hash these bytes
• worker does this in an infinite loop
• every second, worker updates redis to indicate how many loops were done
• webui queries redis, and computes and exposes “hashing speed” in our browser

(See diagram on next slide!)

How does each service find out the address of the other ones?

• We do not hard-code IP addresses in the code
• We do not hard-code FQDNs in the code, either
• We just connect to a service name, and container-magic does the rest (And by container-magic, we mean “a crafty, dynamic, embedded DNS server”)

redis = Redis("`redis`")

def get_random_bytes():
    r = requests.get("http://`rng`/32")
    return r.content

 def hash_bytes(data):
    r = requests.post("http://`hasher`/",
                       data=data,
                       headers={"Content-Type": "application/octet-stream"})

(Full source code available here)

• Containers can have network aliases (resolvable through DNS)
• Compose file version 2+ makes each container reachable through its service name
• Compose file version 1 required “links” sections to accomplish this
• Network aliases are automatically namespaced
  • you can have multiple apps declaring and using a service named database
  • containers in the blue app will resolve database to the IP of the blue database
  • containers in the green app will resolve database to the IP of the green database

• You can check the GitHub repository with all the materials of this workshop: https://github.com/jpetazzo/container.training
• The application is in the dockercoins subdirectory
• The Compose file ( docker-compose.yml) lists all 5 services
• redis is using an official image from the Docker Hub
• hasher, rng, worker, webui are each built from a Dockerfile
• Each service’s Dockerfile and source code is in its own directory (hasher is in the hasher directory, rng is in the rng directory, etc.)

This is relevant only if you have used Compose before 2016…

• Compose 1.6 introduced support for a new Compose file format (aka “v2”)
• Services are no longer at the top level, but under a services section
• There has to be a version key at the top level, with value "2" (as a string, not an integer)
• Containers are placed on a dedicated network, making links unnecessary
• There are other minor differences, but upgrade is easy and straightforward

• On the left-hand side, the “rainbow strip” shows the container names
• On the right-hand side, we see the output of our containers
• We can see the worker service making requests to rng and hasher
• For rng and hasher, we see HTTP access logs

• “Logs are exciting and fun!” (No-one, ever)
• The webui container exposes a web dashboard; let’s view it
• With a web browser, connect to node1 on port 8000
• Remember: the nodeX aliases are valid only on the nodes themselves
• In your browser, you need to enter the IP address of your node

A drawing area should show up, and after a few seconds, a blue graph will appear.

If you just see a Page not found error, it might be because your Docker Engine is running on a different machine. This can be the case if:

• you are using the Docker Toolbox
• you are using a VM (local or remote) created with Docker Machine
• you are controlling a remote Docker Engine

When you run DockerCoins in development mode, the web UI static files are mapped to the container using a volume. Alas, volumes can only work on a local environment, or when using Docker Desktop for Mac or Windows.

How to fix this?

Stop the app with ^C, edit dockercoins.yml, comment out the volumes section, and try again.

• It looks like the speed is approximately 4 hashes/second
• Or more precisely: 4 hashes/second, with regular dips down to zero
• Why?
• The app actually has a constant, steady speed: 3.33 hashes/second (which corresponds to 1 hash every 0.3 seconds, for reasons)
• Yes, and?

• The worker doesn’t update the counter after every loop, but up to once per second
• The speed is computed by the browser, checking the counter about once per second
• Between two consecutive updates, the counter will increase either by 4, or by 0
• The perceived speed will therefore be 4 - 4 - 4 - 0 - 4 - 4 - 0 etc.
• What can we conclude from this?
• “I’m clearly incapable of writing good frontend code!” 😀 — Jérôme

• If we interrupt Compose (with ^C), it will politely ask the Docker Engine to stop the app
• The Docker Engine will send a TERM signal to the containers
• If the containers do not exit in a timely manner, the Engine sends a KILL signal
• Stop the application by hitting ^C

Some containers exit immediately, others take longer.

The containers that do not handle SIGTERM end up being killed after a 10s timeout. If we are very impatient, we can hit ^C a second time!