DevOps is the combination of operations and software development which reduces or almost eliminates the disconnect between systems administrators who run the infrastructure and software developers who develop applications.
During software development, when the Agile methodology is utilized properly, a bottleneck often occurs during the frequent operations and deployment phases. New fixes and updates are produced so rapidly in every sprint that the infrastructure teams can be swamped with deployments. To eliminate few of these issues, the operations personnel and application developers are asked to work closely to automate the code delivery to production from deployment.
As DevOps is an approach for handling change and agility, engineers must master multiple languages. The Python programming language is one of the most crucial components of the DevOps toolchain. Many DevOps teams utilize it for building web applications for visualizing custom data, building custom utilities and more.
Ansible and other tools are written in Python, which means you can build custom scripts or modules to automate your tasks, for example, or do other things.
Reasons for Using Python for DevOps
The accessibility and flexibility of Python are reasons why it is a preferred language for the DevOps toolset. If you are working in the role of DevOps, you must require an adaptable skillset; you must know how to work with multiple languages. For anyone looking to explore new tools and languages, and are curious about technology, the language can form a solid foundation, as it doesn’t require the commitment levels that a specialist language requires.
In addition, it is a great scripting language, and scripting refers to automation. A few major configuration management tools, including SaltStack and Ansible, are written in Python underscores. This shows how useful the language is when it comes to orchestration and infrastructure automation.
Python and Ruby are compared often, and with good reason: Both are highly accessible and utilized in applications developed by many organizations. They also feature in the DevOps toolset. We can do almost all the things with Ruby that we do with Python. But, when it comes to syntax, Python gains the upper hand, as it is much more direct than the syntax of Ruby.
In the realm of learning to debug problems and code, Python has the advantage over Ruby, as it takes a much more direct approach to programming. Its directness and simplicity are invaluable if you are working in DevOps environment and agility is highly important.
Conclusion
As a growing number of engineers and developers take on decision-making responsibilities, Python can be the stabilizing language. And not only for DevOps—the language also can be used for developing blockchain, which is the underlying technology for various cryptocurrencies such as bitcoin wallet. As it can be utilized in various ways, it enables you to be open to broad range of technical possibilities. Python is the go-to programming language for the DevOps landscape.
