Upgrading Ansible: Python 2.7 to 3.8 and the Impact on Playbook Speeds
Ansible is a powerful automation and configuration management tool that allows administrators and developers to automate tasks and manage infrastructure. With the recent upgrade of RHEL (Red Hat Enterprise Linux) from version 7 to 8, many users have also upgraded their Python version from 2.7 to 3.8. This article will explore the impact of this upgrade on Ansible playbook speeds, specifically for those running Ansible 2.9.27 on RHEL 7 with Python 2.7 and then upgrading to Ansible 5.4 on RHEL 8 with Python 3.8.
Ansible and Python: A Brief Overview
Ansible is written in Python and relies heavily on the Python interpreter to execute tasks and manage infrastructure. With the release of Python 3, the Python community deprecated Python 2, and many tools, including Ansible, have followed suit and upgraded their dependencies to Python 3. This article will explore the impact of this upgrade on Ansible playbook speeds.
The Upgrade Process
The process of upgrading Ansible and Python involves several steps, including:
- Uninstalling the old version of Ansible and Python
- Installing the new version of Python
- Installing the new version of Ansible
- Testing the new setup
Impact on Playbook Speeds
When upgrading from Python 2.7 to 3.8, users may notice a decrease in playbook speeds. This is because Python 3 introduced several changes that impact the way Ansible executes tasks. For example, Python 3 introduced a new garbage collection algorithm that can slow down the execution of long-running processes. Additionally, Python 3 introduced several changes to the way strings are handled, which can also impact playbook speeds.
Mitigating the Impact on Playbook Speeds
To mitigate the impact on playbook speeds, users can consider several options, including:
- Using a Python virtual environment to run Ansible with Python 2.7
- Using a tool like Mitogen to speed up Ansible playbook execution
- Optimizing playbooks for Python 3
Upgrading from Python 2.7 to 3.8 can have a significant impact on Ansible playbook speeds. However, by taking the appropriate steps and optimizing playbooks for Python 3, users can mitigate this impact and continue to use Ansible for automation and configuration management tasks.
References
# Example Ansible playbook using Python 2.7
- hosts: all
tasks:
- name: Example task
command: /bin/echo "Hello, World!"
# Example Ansible playbook using Mitogen and Python 3.8
- hosts: all
tasks:
- name: Example task
command: /bin/echo "Hello, World!"
mitogen: true