Over the last decade, network engineering has gone from logging into devices and typing commands to a world of software-defined, API-driven, and fully automated infrastructure. Whether you're a network engineer in the trenches configuring devices every day or a tech leader pushing for digital transformation, the challenge is the same: how do you make network changes reliable, repeatable, and completely risk-free?
This is where solid Network Configuration and Change Management (NCCM) practices - powered by network automation, CI/CD pipelines, and dedicated lab testing environments - become absolutely critical for modern network operations.
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For years, network engineers logged into routers, switches, and firewalls via SSH, copy-pasted some CLI commands from a text file, and just hoped for the best. That manual approach might have worked in small, static networks, but it just doesn't scale for modern companies or data centers where:
Network automation addresses three critical pain points in traditional configuration management:
Instead of manually typing CLI commands on each switch, this Ansible playbook ensures all target switches have VLAN 20 configured consistently, eliminating configuration drift.
- name: Configure VLANs on switches
hosts: campus_switches
gather_facts: no
tasks:
- name: Create VLAN
ios_vlan:
vlan_id: 20
name: HR_VLAN
state: present
A Python script using libraries like Netmiko or NAPALM can automatically back up a device's running config before it applies any changes. If the change fails validation, the same script can automatically restore the last-known-good config, preventing network downtime.
from netmiko import ConnectHandler
import datetime
device = {
"device_type": "cisco_ios",
"ip": "10.1.1.1",
"username": "admin",
"password": "password"
}
conn = ConnectHandler(**device)
# Backup running config
config = conn.send_command("show running-config")
filename = f"backup_{device['ip']}_{datetime.date.today()}.txt"
with open(filename, "w") as f:
f.write(config)
# Rollback example
conn.send_config_from_file("last_known_good_config.txt")
Managing complex BGP peerings and route policies manually is a recipe for disaster. An Ansible playbook can enforce consistent BGP configs, peerings, and route-maps across all your routers, ensuring predictable and stable routing.
- name: Configure BGP
hosts: routers
tasks:
- name: Set BGP neighbors
ios_config:
lines:
- router bgp 65001
- neighbor 10.10.10.2 remote-as 65002
Just having network automation isn't enough. Without proper testing and governance, you risk deploying bad configurations at machine speed. That's where CI/CD pipelines for network configuration management come in. Borrowed from DevOps practices, they bring discipline to network automation:
This GitOps workflow makes sure that only thoroughly tested, validated, and peer-reviewed changes ever touch your production network.
Here's the question where most companies get stuck: Where can you safely test these network automation workflows and complex device configurations before deploying them to production?
This is where CloudMyLab's EVE-NG and GNS3-powered network simulation labs change the game for network configuration management:
I often call CloudMyLab the "flight simulator" for network engineers. Before you fly a real aircraft (your production network), you train, test, and validate every move in a high-fidelity simulator (your CloudMyLab environment).
A practical, enterprise-grade workflow for your existing (brownfield) network should look something like this:
No matter how fancy your network automation is, things can still go wrong. A comprehensive, well-tested rollback strategy is absolutely essential for keeping the network up and ensuring business continuity.
Implement a three-tier rollback approach that provides multiple safety nets:
Automated scripts tested extensively in lab environments provide the fastest recovery path. Lets see a Python example.
import os
def rollback_config(device, backup_file):
print(f"Rolling back {device} using {backup_file}")
os.system(f"scp {backup_file} {device}:/config/startup.cfg")
os.system(f"ssh {device} reload")
Before this rollback script is linked to production, it can be tested multiple times in CloudMyLab’s labs, ensuring engineers know it works flawlessly.
Always take comprehensive backups before any change:
Maintain golden configurations stored in Git repositories:
Never push changes globally at once. Use a phased approach:
Picking the right automation tools is critical for a successful NCCM implementation. Here’s a TLDR guide to the most effective frameworks for network engineers:
Ansible's declarative approach and extensive network modules make it the go-to choice for most organizations. Its agentless architecture and YAML-based playbooks provide consistency across multi-vendor environments.
Python offers unmatched flexibility for complex automation scenarios. NAPALM provides vendor-agnostic APIs, while Netmiko excels at device-specific operations.
Cisco's pyATS framework provides comprehensive network testing capabilities, from device health checks to complex validation workflows.
Modern network operations require the same discipline as software development. Git-based workflows ensure every change is tracked, reviewed, and deployed safely.
NCCM works excellently with multi-vendor environments (Cisco, Juniper, Arista), but requires vendor-agnostic tools:
All these tools can be tested and validated in CloudMyLab's EVE-NG and GNS3-powered simulation labs before production deployment, ensuring your automation workflows perform exactly as expected across different vendor platforms.
For technology leaders, it is all about business resilience, operational efficiency, and quantifiable ROI.
Network automation and CI/CD pipelines are incredibly powerful, but without a comprehensive lab testing strategy, they can leave your company exposed to config drift, security vulnerabilities, and unexpected, costly downtime. By integrating CloudMyLab's EVE-NG and GNS3 network simulation labs into your NCCM workflow, both your engineers and your leadership team gain confidence. Your engineers can test, refine, and validate their automation scripts in a safe, realistic environment. Your leaders know that every change is safe, scalable, and aligned with your security and compliance needs.
The move from manual network operations to CI/CD-driven automation requires the right mix of tools, processes, and safe testing environments where your network teams can validate every single change before it impacts your business.
Want to explore how CloudMyLab can support next-gen network testing and automation? Check out our hosted platforms and start building with confidence.
The main challenge is configuration drift across your existing devices. Legacy networks often have inconsistent configs that have evolved over years of manual, one-off changes. The best approach is to start with a comprehensive audit using tools like NAPALM to get a baseline. Then, you can gradually standardize your configs through automated templates while keeping detailed, well-tested rollback procedures for every step.
You must use dedicated network simulation labs, like those powered by EVE-NG or GNS3, to replicate your production topology. CloudMyLab provides pre-built, on-demand enterprise topologies where you can safely test your Ansible playbooks, Python scripts, and config changes in a risk-free environment. Always run your automation workflows from end to end in the lab before they ever touch your production devices.
Configuration management is about maintaining a consistent, desired state for your device settings and preventing unauthorized or inconsistent config drift over time.
Change management is the formal process of planning, approving, testing, and deploying any modifications to your network.
A single, dedicated network engineer can start with basic automation using tools like Ansible and leverage a platform like CloudMyLab for all their testing needs. For larger enterprise setups, a good starting point is a small team with one dedicated network automation engineer, one lab environment manager (if self-hosted), and one or two senior engineers to lead the change approval process.