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cloud engineer

container

Jekyll on Docker Container

Here’s how to run Jekyll in a Docker container.

mkdir blog
cd blog
docker run -v $(pwd):/site bretfisher/jekyll new .
docker run -p 4000:4000 -v $(pwd):/site bretfisher/jekyll-serve

Another option is to use docker compose. Create a docker-compose.yml file.

version: 3.5
services:
  jekyll:
    image: bretfisher/jekyll-serve
    volumes:
      - .:/site
    ports:
      - '4000:4000'

Run Jekyll.

cd blog
docker-compose up -d

Stop Jekyll.

cd blog
docker-compose down

Docker container logs

How to check Docker container logs. Look for the container ID.

$ docker ps -a
3e2c1193915f

To view the logs for the container.

docker logs 3e2c1193915f
# or
docker container logs 3e2c1193915f

Rocky Linux in a Container

Here’s how to run Rocky Linux in a Docker container.

Download the image.

docker pull rockylinux/rockylinux

Create a Rocky Linux container called bullwinkle.

docker run -it --name bullwinkle -d rockylinux/rockylinux

Login to the container using bash.

docker exec -it --user root bullwinkle /bin/bash

When done, stop and delete the container.

docker ps -a
docker stop container_ID
docker rm container_ID

Terraform in a Docker Container

Run Terraform in a Docker container.

docker run --rm -it --name terraform -v ~/.aws:/root/.aws -v $(pwd):/workspace -w /workspace hashicorp/terraform:latest

Create an alias.

alias terraform='docker run --rm -it --name terraform -v ~/.aws:/root/.aws -v $(pwd):/workspace -w /workspace hashicorp/terraform:latest'

Run the command

terraform --version
Terraform v1.0.2
on linux_amd64

GCloud in a Docker Container

You can run a gcloud commands in a Docker container.

docker run -ti --name gcloud-config google/cloud-sdk gcloud auth login

Create an alias.

alias gcloud='docker run --rm -ti --volumes-from gcloud-config google/cloud-sdk:latest gcloud'

Run the command.

gcloud --version
Google Cloud SDK 348.0.0
alpha 2021.07.09
app-engine-go 1.9.71
app-engine-java 1.9.90
app-engine-python 1.9.93
app-engine-python-extras 1.9.93
beta 2021.07.09
bigtable 
bq 2.0.70
cbt 0.10.0
cloud-datastore-emulator 2.1.0
cloud-firestore-emulator 1.13.0
cloud-spanner-emulator 1.2.0
core 2021.07.09
datalab 20190610
gsutil 4.65
kpt 0.39.3
local-extract 1.2.0
pubsub-emulator 0.4.1

Create one for gsutil.

alias gsutil='docker run --rm -ti --volumes-from gcloud-config google/cloud-sdk:latest gsutil'

AWSCLI in Docker Container

This will download the latest awscli and run it in a container.

A new container will be built every time the command is run.

Your current credentials in ~/.aws will be used.

docker run --rm -it -v ~/.aws:/root/.aws amazon/aws-cli:latest

Create an alias for convenience.

alias aws='docker run --rm -ti -v ~/.aws:/root/.aws -v $(pwd):/aws amazon/aws-cli'

You can now run any aws cli after.

aws --version
aws-cli/2.2.20 Python/3.8.8 Linux/5.4.0-66-generic docker/x86_64.amzn.2 prompt/off

Docker Exec

If you want to SSH to a Docker container, use the Docker exec command.

docker exec -it container_name bash

I’m using a Git Bash terminal, so I have to prefix the docker command with winpty.

winpty docker exec -it container_name bash

Result

root@681bbe3f65f1:/var/www/html#

Ctrl-D to exit.

Static Website on GKE

Here’s how to run your web application on Google Kubernetes Engine.

Create a Dockerfile. Place your web pages in the public-html directory.

FROM httpd:2.4
COPY ./public-html/ /usr/local/apache2/htdocs/

Build a container image for Google Container Registry (GCR).

# set your project
export PROJECT_ID=[project_id]
# build a container image
docker build -t gcr.io/${PROJECT_ID}/your-app:v1 .
# verify docker images
docker images

Upload the container image to GCR.

# authenticate
gcloud auth configure-docker
# upload image
docker push gcr.io/${PROJECT_ID}/your-app:v1

Create a container GKE cluster.

# create cluster
gcloud container clusters create your-app-cluster \
--num-nodes=2
# check clusters
gcloud compute instances list

Deploy your web application.

# create deployment
kubectl create deployment your-app \
--image=gcr.io/${PROJECT_ID}/your-app:v1
# see the pods
kubectl get pods

Expose your application to the Internet.

# expose your application
kubectl expose deployment your-app \
--type=LoadBalancer \
--port 80 \
--target-port 80
# get the external ip address
kubectl get service

Scale your application.

# scale to 3 replicas
kubectl scale deployment your-app --replicas=3
# display the replicas
kubectl get deployment your-app

Cleanup.

kubectl delete service your-app
gcloud container clusters delete your-app-cluster