Container workflow has reduced deployment effort but still faces cost and pricing challenges
What is our primary use case?
What is most valuable?
I use Docker a lot, especially during production deliveries. I deliver development that runs in a Docker container. Docker is very convenient because it abstracts away all the problems by containerizing everything. It contains all of the requirements into one container for ease of use and easy deployment.
Docker streamlines things and makes it easier for testing and development. With full automation, it cuts my deployment and testing time at least in half. I have been using Docker for a long time and continue to use it. Docker is the heart of many AI tools that are used, and I have an AI workstation that uses Docker to package up certain capabilities for AI engineering.
What needs improvement?
Docker has already integrated AI models into their platform and has covered most of the necessary features. They continuously release new versions of Docker. While Docker itself has no cost, the Docker repository and Docker Hub could improve their pricing, especially for startup companies.
For how long have I used the solution?
I have been using Docker for a long time.
What do I think about the stability of the solution?
I have not experienced any stability issues. I run and build Docker containers and then deploy them.
How are customer service and support?
I have not had any reason to contact support. The documentation is good, especially when using AI tools that utilize Docker's information for support.
How would you rate customer service and support?
Neutral
What other advice do I have?
I work with Linux, but not that particular module, mainly in EC2 instances. I use Ubuntu Linux out of the box and do not use Red Hat, especially at the enterprise level. It is convenient and easy since Linux is well supported. Everything is containerized, which is why I use the ECR pieces up in AWS to build containers and put them in the repository.
I work with APIs and consider the best ways to implement them, including JWTs and third-party Okta integration. The A in LAMP stands for Angular, and I do a lot of coding and projects with Angular. Mongo is the heart of our database system. LAMP stack means Linux, Angular, and Mongo. I use AWS Marketplace for different things, including MongoDB connections inside AWS. This review has a rating of 2 out of 10.