The traditional ways of operating and developing have faced many challenges such as an increasing number of updates and fixes from the development team. In that way, the operations team and development team are disconnected in their work and the approach makes their work cumbersome, monotonous, and tedious to work with.
The functional and the infrastructural changes are very difficult to manage and thus they run independently resulting in a lot of downtimes, unnecessary hurdles, and a lot of bugs and errors due to human intervention. The application development may run their function in a compatible platform and the testing team may test in their platforms and finally when it comes to deployment in production the platforms are different and this is a nightmare for the development and test and production teams.
The operations team which manages their infrastructure has a different outlook and they have their own set of challenges in maintaining the platform which is not suitable for the application hosting.
Then came the DevOps which unifies the development and operations teams in a common platform and eliminates the disconnect that was there between the teams. DevOps in principle is a culture that is also called the DevOps life cycle that makes the automation of the plan, code, build, test, release, deploy, operate and monitor easily so that everyone is working for the common goal. The main culture of DevOps is enhancing the continuous development, testing, management, integration, deployment, operations automation, and continuous monitoring. The DevOps life cycle changes consist of many tools that make the CI/CD pipeline easy to do and automate all the processes in the DevOps SDLC. DevOps life cycle management also needs DevOps engineer to do some coding and scripting so that with simple and easy to use programming he can automate all the processes.
Python with its programming friendly and vast libraries makes automation very easy. That is why it is used in DevOps and has become the de facto language for the automation of the DevOps.
- It is a great scripting language used for automation. Many tools such as Saltstack and Ansible are written in Python.
- It is also used for complete infrastructure automation and orchestration. To debug and code it is far ahead than Ruby.
- It is a very agile programming language and it takes a direct approach to program and simplicity is invaluable to DevOps.
- Its vast libraries for DevOps toolsets are preferred when compared to others because of its ease of access and flexibility.
- Not only in DevOps, but it is also used in various applications such as Machine Learning, AI, IoT, and Data Science.
Learn DevOps online that covers the principles of DevOps, tools used in DevOps, and Python Programming
Best way to use python for DevOps
You can do anything in DevOps using python. The main areas are the automation of the DevOps life cycle management using Python. The CI/CD pipeline can be automated using Python. The best ways to use Python for DevOps are as follows,
- Automate the DevOps life cycle management
- Automate the infrastructure deployment and configuration management
- Use Python to modify, configure and automate the tools used in DevOps
- Use Python for the CI/CD pipeline automation
- Python as a script can be used for automating the small day to day checking and monitoring tasks
- Deploy applications automatically from Dev to QA to Prod environment
- Ensure that DevOps applications are platform-independent by smart and simple programming using Python.
- Automate the operational tasks of the sysadmin which is repetitive and periodic.
- Manage and control the infrastructures using Python programming and using tools
Few python DevOps examples explained
The main purpose why this coding language is used in DevOps is to make the automation scripts. If you want to deploy the code in containers or VM's or deploy apps in development/production machines you can run the automation script to deploy the apps.
Some of the examples of Python scripting and coding are as follows,
- Make automation tools to check on servers
- Make the automation tools to gather application statistics.
- Tools to check on the network devices, disk drives, and also to build failure models.
- Make the GUI to make communication easier.
Benefits of Python in DevOps
Next-Gen solutions - Python and DevOps (combo) combined can be used in synergy for building next-generation solutions. You can build any type of application, get work done by diverse and cross-functional teams, use multiple platforms, and have a great user experience.
Efficiency – This combo goes hand in hand when it is the topic of efficiency. The code is written with best practices, process and patterns bring in the remarkable efficiency in the code. Efficiency is certain when it comes to Python as a coding language and DevOps as a practice. Efficiency must be improved over time to increase quality and customer satisfaction. Efficiency is not a result but the continuous practice.
Agile Programming for DevOps - Python has easy to remember and direct syntax helps the developer work with this combo. It is also used for deployment automation and web development as it is used for scripting in DevOps. DevOps stands for automation and agility and the python with its vast array of packages and libraries offers accessibility and flexibility.
Adapt to Changes -DevOps develops the attitude of the Organization to adapt quickly to the changes. The change in everything such as customer demands, changes in the market changes in the business, and changes in technology is the key things organization must be prepared to adopt and adapt. The change handling and execution must be the motto of any company in the world. Python in DevOps culture helps to make scalable, adaptable, and flexible applications with efficient and effective processes.
Makes things simpler - Python in the DevOps field helps to make simple and easy scripting, automation, and programming with its great syntax and vast libraries. It helps organizations embrace changes, automates deployment and development, and handles complex challenges with a secure, streamlined, and simpler manner. It is a language that can be used by both novice and experienced developers. It is compatible with various technologies and platforms and supports third-party packages as well. To learn more about DevOps with Python language enroll at StarAgile’s DevOps online training.
A great combination -DevOps and Python is not at the end of the road but has many more years of great future in building the applications, automate the tasks increase productivity, improve efficiency, quality, and meet ever-changing customer expectations.
Learn more about the Python language skills and DevOps by taking the DevOps certification course at StarAgile.
Relates Article:Benefits of DevOps
We have seen how Python programming and scripting can be used successfully in the DevOps. Once you are convinced with why is python required for DevOps you must get into more details about programming in Python in DevOps with live real-time projects register for DevOps training online with a reputed institute such as StarAgile.
StarAgile conducts DevOps Certification training online that covers lab and theory sessions. What are you waiting for? Register now and enquire about the fees for the interactive DevOps online training.
Keep Coding and Scripting in DevOps with Python!!!