Dgoss: A Fast YAML Based tool for Validating Docker Containers

dgoss

dgoss is a convenience wrapper around goss that aims to bring the simplicity of goss to docker containers.

Installation

Linux:

Follow the goss installation instructions

Mac OSX

Since goss runs on the target container, dgoss can be used on a Mac OSX system by doing the following:

# Install dgoss
curl -L https://raw.githubusercontent.com/aelsabbahy/goss/master/extras/dgoss/dgoss -o /usr/local/bin/dgoss
chmod +rx /usr/local/bin/dgoss

# Download desired goss version to your preferred location (e.g. v0.3.6)
curl -L https://github.com/aelsabbahy/goss/releases/download/v0.3.6/goss-linux-amd64 -o ~/Downloads/goss-linux-amd64

# Set your GOSS_PATH to the above location
export GOSS_PATH=~/Downloads/goss-linux-amd64

# Use dgoss
dgoss edit ...
dgoss run ...

Usage

dgoss [run|edit] <docker_run_params>

Run

Run is used to validate a docker container. It expects a ./goss.yaml file to exist in the directory it was invoked from. In most cases one can just substitute the docker command for the dgoss command, for example:

run:

docker run -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

test:

dgoss run -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

dgoss run will do the following:

• Run the container with the flags you specified.
• Stream the containers log output into the container as /goss/docker_output.log
  • This allows writing tests or waits against the docker output
• (optional) Run goss with $GOSS_WAIT_OPTS if ./goss_wait.yaml file exists in the current dir
• Run goss with $GOSS_OPTS using ./goss.yaml

Edit

Edit will launch a docker container, install goss, and drop the user into an interactive shell. Once the user quits the interactive shell, any goss.yaml or goss_wait.yaml are copied out into the current directory. This allows the user to leverage the goss add|autoadd commands to write tests as they would on a regular machine.

Example:

dgoss edit -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

Environment vars and defaults

The following environment variables can be set to change the behavior of dgoss.

GOSS_PATH

Location of the goss binary to use. (Default: $(which goss))

GOSS_FILE

Name of the goss file to use. (Default: goss.yaml)

GOSS_OPTS

Options to use for the goss test run. (Default: --color --format documentation)

GOSS_WAIT_OPTS

Options to use for the goss wait run, when ./goss_wait.yaml exists. (Default: -r 30s -s 1s > /dev/null)

GOSS_SLEEP

Time to sleep after running container (and optionally goss_wait.yaml) and before running tests. (Default: 0.2)

GOSS_FILES_PATH

Location of the goss yaml files. (Default: .)

GOSS_VARS

The name of the variables file relative to GOSS_FILES_PATH to copy into the docker container and use for valiation (i.e. dgoss run) and copy out of the docker container when writing tests (i.e. dgoss edit). If set, the --vars flag is passed to goss validate commands inside the container. If unset (or empty), the --vars flag is omitted, which is the normal behavior. (Default: '').

GOSS_FILES_STRATEGY

Strategy used for copying goss files into the docker container. If set to 'mount' a volume with goss files is mounted and log output is streamed into the container as /goss/docker_output.log file. Other strategy is 'cp' which uses 'docker cp' command to copy goss files into docker container. With the 'cp' strategy you lose the ability to write tests or waits against the docker output. The 'cp' strategy is required especially when docker daemon is not on the local machine. (Default 'mount')

CONTAINER_LOG_OUTPUT

Location of the file that contains tested container logs. Logs are retained only if the variable is set to a non-empty string. (Default '')

CONTAINER_RUNTIME

Container runtime to use - docker or podman. Defaults to docker. Note that podman requires a run command to keep the container running. This defaults to sleep infinity in case only an image is passed to dgoss commands.

Examples and Tutorials

• video tutorial - Introduction to dgoss tutorial
• blog tutorial - Same as above, but in written format
• dgoss-examples - Repo containing examples of using dgoss to validate docker images

---

Download Details:

Author: aelsabbahy
Source code: https://github.com/aelsabbahy/goss/

#docker 

What is GEEK

Buddha Community

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Ever Wondered Why We Use Containers In DevOps?

At some point we’ve all said the words, “But it works on my machine.” It usually happens during testing or when you’re trying to get a new project set up. Sometimes it happens when you pull down changes from an updated branch.

Every machine has different underlying states depending on the operating system, other installed programs, and permissions. Getting a project to run locally could take hours or even days because of weird system issues.

The worst part is that this can also happen in production. If the server is configured differently than what you’re running locally, your changes might not work as you expect and cause problems for users. There’s a way around all of these common issues using containers.

What is a container

A container is a piece of software that packages code and its dependencies so that the application can run in any computing environment. They basically create a little unit that you can put on any operating system and reliably and consistently run the application. You don’t have to worry about any of those underlying system issues creeping in later.

Although containers were already used in Linux for years, they became more popular in recent years. Most of the time when people are talking about containers, they’re referring to Docker containers. These containers are built from images that include all of the dependencies needed to run an application.

When you think of containers, virtual machines might also come to mind. They are very similar, but the big difference is that containers virtualize the operating system instead of the hardware. That’s what makes them so easy to run on all of the operating systems consistently.

What containers have to do with DevOps

Since we know how odd happenings occur when you move code from one computing environment to another, this is also a common issue with moving code to the different environments in our DevOps process. You don’t want to have to deal with system differences between staging and production. That would require more work than it should.

Once you have an artifact built, you should be able to use it in any environment from local to production. That’s the reason we use containers in DevOps. It’s also invaluable when you’re working with microservices. Docker containers used with something like Kubernetes will make it easier for you to handle larger systems with more moving pieces.

#devops #containers #containers-devops #devops-containers #devops-tools #devops-docker #docker #docker-image

Dgoss: A Fast YAML Based tool for Validating Docker Containers

dgoss

dgoss is a convenience wrapper around goss that aims to bring the simplicity of goss to docker containers.

Installation

Linux:

Follow the goss installation instructions

Mac OSX

Since goss runs on the target container, dgoss can be used on a Mac OSX system by doing the following:

# Install dgoss
curl -L https://raw.githubusercontent.com/aelsabbahy/goss/master/extras/dgoss/dgoss -o /usr/local/bin/dgoss
chmod +rx /usr/local/bin/dgoss

# Download desired goss version to your preferred location (e.g. v0.3.6)
curl -L https://github.com/aelsabbahy/goss/releases/download/v0.3.6/goss-linux-amd64 -o ~/Downloads/goss-linux-amd64

# Set your GOSS_PATH to the above location
export GOSS_PATH=~/Downloads/goss-linux-amd64

# Use dgoss
dgoss edit ...
dgoss run ...

Usage

dgoss [run|edit] <docker_run_params>

Run

Run is used to validate a docker container. It expects a ./goss.yaml file to exist in the directory it was invoked from. In most cases one can just substitute the docker command for the dgoss command, for example:

run:

docker run -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

test:

dgoss run -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

dgoss run will do the following:

• Run the container with the flags you specified.
• Stream the containers log output into the container as /goss/docker_output.log
  • This allows writing tests or waits against the docker output
• (optional) Run goss with $GOSS_WAIT_OPTS if ./goss_wait.yaml file exists in the current dir
• Run goss with $GOSS_OPTS using ./goss.yaml

Edit

Edit will launch a docker container, install goss, and drop the user into an interactive shell. Once the user quits the interactive shell, any goss.yaml or goss_wait.yaml are copied out into the current directory. This allows the user to leverage the goss add|autoadd commands to write tests as they would on a regular machine.

Example:

dgoss edit -e JENKINS_OPTS="--httpPort=8080 --httpsPort=-1" -e JAVA_OPTS="-Xmx1048m" jenkins:alpine

Environment vars and defaults

The following environment variables can be set to change the behavior of dgoss.

GOSS_PATH

Location of the goss binary to use. (Default: $(which goss))

GOSS_FILE

Name of the goss file to use. (Default: goss.yaml)

GOSS_OPTS

Options to use for the goss test run. (Default: --color --format documentation)

GOSS_WAIT_OPTS

Options to use for the goss wait run, when ./goss_wait.yaml exists. (Default: -r 30s -s 1s > /dev/null)

GOSS_SLEEP

Time to sleep after running container (and optionally goss_wait.yaml) and before running tests. (Default: 0.2)

GOSS_FILES_PATH

Location of the goss yaml files. (Default: .)

GOSS_VARS

The name of the variables file relative to GOSS_FILES_PATH to copy into the docker container and use for valiation (i.e. dgoss run) and copy out of the docker container when writing tests (i.e. dgoss edit). If set, the --vars flag is passed to goss validate commands inside the container. If unset (or empty), the --vars flag is omitted, which is the normal behavior. (Default: '').

GOSS_FILES_STRATEGY

Strategy used for copying goss files into the docker container. If set to 'mount' a volume with goss files is mounted and log output is streamed into the container as /goss/docker_output.log file. Other strategy is 'cp' which uses 'docker cp' command to copy goss files into docker container. With the 'cp' strategy you lose the ability to write tests or waits against the docker output. The 'cp' strategy is required especially when docker daemon is not on the local machine. (Default 'mount')

CONTAINER_LOG_OUTPUT

Location of the file that contains tested container logs. Logs are retained only if the variable is set to a non-empty string. (Default '')

CONTAINER_RUNTIME

Container runtime to use - docker or podman. Defaults to docker. Note that podman requires a run command to keep the container running. This defaults to sleep infinity in case only an image is passed to dgoss commands.

Examples and Tutorials

• video tutorial - Introduction to dgoss tutorial
• blog tutorial - Same as above, but in written format
• dgoss-examples - Repo containing examples of using dgoss to validate docker images

---

Download Details:

Author: aelsabbahy
Source code: https://github.com/aelsabbahy/goss/

#docker 

Docker Tutorial for Beginners 8 - Build and Run C++ Applications in a Docker Container

Docker is an open platform that allows use package, develop, run, and ship software applications in different environments using containers.
In this course We will learn How to Write Dockerfiles, Working with the Docker Toolbox, How to Work with the Docker Machine, How to Use Docker Compose to fire up multiple containers, How to Work with Docker Kinematic, Push images to Docker Hub, Pull images from a Docker Registery, Push stacks of servers to Docker Hub.
How to install Docker on Mac.

#docker tutorial #c++ #docker container #docker #docker hub #devopstools

Docker Explained: Docker Architecture | Docker Registries

Following the second video about Docker basics, in this video, I explain Docker architecture and explain the different building blocks of the docker engine; docker client, API, Docker Daemon. I also explain what a docker registry is and I finish the video with a demo explaining and illustrating how to use Docker hub

In this video lesson you will learn:

• What is Docker Host
• What is Docker Engine
• Learn about Docker Architecture
• Learn about Docker client and Docker Daemon
• Docker Hub and Registries
• Simple demo to understand using images from registries

#docker #docker hub #docker host #docker engine #docker architecture #api