DevOps Using Docker Training Course – Achieving a DevOps Culture
DevOps Using Docker training course is a three-day workshop, especially relevant to both developer and sysops professionals concerned with fast delivery and deployment of new software by taking an agile approach. Therefore, delegates are taken from the fundamentals of DevOps through to continuous deployment, horizontal scalability and zero downtime.
DevOps Using Docker – Course Overview
Delegates understand the principles underpinning DevOps before building and monitoring their own continuous delivery pipeline using Docker. There is expert tuition and guidance at every step so that delegates understand the fundamentals of collaboration to eliminate silos. It is helpful, but not essential, to have some experience with a Unix shell.
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DevOps Using Docker – Course Content
- An introduction to DevOps and the fundamentals of the DevOps movement.
- How DevOps culture and behaviour, therefore, have an impact on progress.
- Silos and how to break them consequently improving collaboration.
- Agile and Lean working.
- Reducing waste and bottlenecks as a result of value stream mapping.
- Continuous integration (CI) & continuous delivery (CD).
- Cloud computing and AWS.
- What is containerisation.
- Introduction to Docker.
- Using Jenkins to set off Docker containerisation.
- Finally, deploying Docker containers.
DevOps Using Docker – Prerequisites
- Bring their own laptops therefore be able to log in to machines created in AWS.
- Install Git beforehand (because they’ll be cloning sample code from our GitHub repository).
- Also be proficient with their text editor of choice.
What is Docker?
In summary, Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. A developer packages in a container all the parts an application needs, such as libraries and other dependencies, and ships it all out as one package. By doing so, thanks to the container, the developer can be assured that the application will run on any other machine regardless of customised settings that machine might have that differ from the machine used for writing and testing code.