Intro
In today's software development landscape, DevOps has become an essential practice. It is used in many organizations and is commonly accepted as a good practice for software engineering. Applying DevOps can boost the productivity of organizations, cost managment and improve their software.
WhatOps?
There are several Ops and DevOps is the one that started it all.
- DevOps: Software Development (Dev) + IT Operations (Ops)
- Focuses on software development and deployment
- ModelOps: Model Operations
- Primarily focuses on the machine learning model
- DataOps: Data Operations
- Focuses on best practices in data quality and analytics for data engineering
- AlOps: Artificial Intelligence for IT Operations
- Focuses on using analytics, big data, and machine learning to solve IT issues without human assistance or intervention
How all the Ops work together?
Why is DevOps necessary?
Good Code → Good Data → Good ML → Good Application
- Release Cycle 1: Minimum Viable Product
- Release Cycle 2: Product improvements
- Release Cycle 3: End Product
What is DevOps after all?
DevOps is a combination of:
- Tools
- Technologies
- Cultural elements