Docker Enterprise was sold to Mirantis in 2019; that product is now sold as Mirantis Kubernetes Engine. But Docker now offers a 2-product suite that includes Docker Desktop, which they present as a fast way to containerize applications on a desktop; and, Docker Hub, a service for finding and sharing container images with a team and the Docker community, a repository of container images with an array of…
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HashiCorp Packer
Score 10.0 out of 10
N/A
HashiCorp Packer automates the creation of machine images, coming out of the box with support to build images for Amazon EC2, CloudStack, DigitalOcean, Docker, Google Compute Engine, Microsoft Azure, QEMU, VirtualBox, and VMware.
You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.
We use packer to generate new machine images for multiple platforms on every change to our Configuration Management tools like Chef/Puppet/Ansible It's act single tool for Image building for Multi-provider like AWS/Azure/GCP Helps to achieve Dev/Prod Parity Packer itself doesn't have a state like Terraform. You can't do packer output AMI ID. If you have a scenario where you want to maintain the state for images it would be tough to manage via Packer.
I have been using Docker for more than 3 years and it really simplifies the modern application development and deployment. I like the ability of Docker to improve efficiency, portability and scalability for developers and operations teams. Another reason for giving this rating is because Docker integrates CI/CD pipelines very well
We need a solution where initially we can use an OS to trigger our pipeline to be used by terraform and then later in ansible. After doing all work it automatically get exited and we can reclaim the space of our VM. So we created a gitlab pipeline and at the initial stage we defined a docker file which will be our base image and we performed all our activities inside that image to build infrastructure using terraform. Integration we have done in our gitlab pipeline and finally we remove the docker image so that the space can be reclaimed immediately.
There are lot of tools in market which does the job for Image creation but all of them are not complete Machine/Image as a code. All other alternatives can create Image partially. Main reason for selecting Packer are Packer is lightweight, portable, and command-line driven Packer helps keep development, staging, and production as similar as possible. Packer automates the creation of any type of machine image Multi-provider portability is the feature to die for
It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.