Network Automation Challenges: 5 Mistakes Engineers Make (And How to Avoid Them)

How does network automation reduce operational costs?

Today's networks are a different beast. They're more dynamic and complex than ever. With demands for cloud integration, tight security, and agile app delivery, banging away on the CLI just doesn't cut it anymore. Your business wants speed, rock-solid reliability, and consistency. And you, as an engineer, want to stop doing the same boring tasks over and over and avoid the stress of those late-night outage calls. Network automation, when you do it right, wipes out human error, makes deployments way faster, and frees up your valuable time to focus on smart design and innovation instead of just typing commands. But for a lot of engineers and companies just starting out, these automation projects often fall flat because of a few common, yet critical, missteps.

• How does network automation reduce operational costs?
• 1. Treating Automation like "fancy CLI scripting" and the skills gap problem
• 2. Skipping Version Control and Collaboration
• 3. Not testing before production
• 4. Ignoring error handling and logging
• 5. Treating Automation as a one-off project
• Actionable recommendations

1. Treating Automation like "fancy CLI scripting" and the skills gap problem

The mistake

You might think network automation is just copying and pasting familiar CLI commands into a script. While that might work for a simple, one-off task, it breaks down spectacularly at scale and often creates more problems than it solves.

An Ansible playbook that pushes BGP configs line by line using raw commands works the first time, but running it again creates duplicate neighbor statements, leading to broken routing sessions.

A Python script that adds VLANs to a switch without first checking what's already there ends up creating conflicting configs or just failing unexpectedly.

CLI-style scripts that you wrote and tested on Cisco IOS devices totally fail when you try to apply them to Juniper Junos or Arista EOS gear because of subtle syntax differences.

The underlying skills gap

"CLI thinking" and "automation thinking" are fundamentally different, and this creates a huge skills gap for network engineers.

Take state management, for example. On the CLI, commands are usually additive. Real automation should be declarative – you define the desired end state, not just the step-by-step commands to get there. If you don't get this difference, you'll write scripts that work once but create configuration drift over time.

Idempotency is another core concept you absolutely need for reliable automation. Your automation scripts should be built to produce the same, predictable result every single time they run, no matter what state the device was in to begin with. Error handling is just as important—your automation needs to gracefully handle failures, network timeouts, and weird device states, not just crash and burn, leaving you to guess what went wrong.

Impact

Your network's configuration starts to drift as devices end up in inconsistent states. Scripts that worked perfectly in your small test lab produce unpredictable and often disastrous results in production. Your automation becomes so brittle that minor infrastructure changes or OS upgrades break everything, and you end up spending more time fixing scripts than you would have just doing things manually.

The business impact is even worse. Your team loses confidence in automation when scripts fail during a critical maintenance window. Engineers go back to manual processes because they don't trust the automation to work reliably. All that investment in automation tools and training feels wasted.

How to avoid it: Learn Automation-First thinking

Instead of this (CLI mindset):

# Add VLAN 100 - will fail if it exists
vlan 100
name PRODUCTION

Think like this (desired state):

# Ansible - idempotent and safe
- name: Configure VLAN 100
  ios_vlans:
    config:
      - vlan_id: 100
        name: PRODUCTION
    state: merged

What are the essential Automation concepts every Network Engineer needs?

Idempotency: Use idempotent modules in Ansible (ios_bgp, nxos_vlan) instead of just sending raw CLI text. These Ansible modules are smart enough to check the current state and only make changes if needed.

State Checking: In Python, always programmatically check a device's current state before you make changes. Think in terms of achieving a "desired state," not just blindly sending a list of commands.

# Check existing VLANs before adding new ones
existing_vlans = device.get_vlans()
if vlan_100 not in existing_vlans:
    device.add_vlan(100, "PRODUCTION")

Robust Error Handling: Plan for things to fail from the start. Networks are unpredictable, and your automation has to handle unexpected edge cases without falling apart.

2. Skipping Version Control and Collaboration

The mistake

You need to fix something fast, so you whip up a script on your laptop, test it on a couple of devices, and run it in production. There's no version control, no one else looks at it, just a focus on getting it done. This "lone wolf" approach feels efficient at the moment but creates absolute chaos that stops your team from scaling automation and introduces a ton of risk.

Examples

Engineer A fixes a critical NTP issue with a script, but a week later, Engineer B, who didn't know about the fix, runs an older version of a similar script and breaks the config all over again. A critical playbook for setting up new branch offices exists only on one engineer's laptop. When they leave, that crucial knowledge is gone.

Multiple engineers on the same team independently create similar automation for the same task, leading to conflicting ways of doing things and wasted effort.

Production changes are made via automation without anyone else looking at the code, causing widespread outages that a second set of eyes could have easily prevented.

Lack of professional development practices

You probably don't have standardized workflows for developing, testing, and deploying automation, everyone just does their own thing.

Without peer review, simple mistakes slip right into production. You're probably missing change tracking, so when something breaks, you have no way to figure out what changed, when, or why. When your automation fails, you don't have a formal rollback plan because there's no record of the previous "good" state.

Impact

Conflicting changes constantly overwrite each other, creating subtle and dangerous configuration inconsistencies. With no audit trail, troubleshooting failures becomes a painful, time-consuming detective game. When problems happen, it's often impossible to roll back the bad changes cleanly, forcing you into frantic manual fixes.

Knowledge silos prevent your team from working together effectively. The business risks are just as bad. Automation projects frequently stall because of a lack of coordination.

Compliance violations are inevitable when network changes aren't properly tracked and reviewed. The departure of key engineers creates single points of failure. Your team wastes countless hours doing the same work over and over.

How to avoid it: Manage your Automation code like professional software

Store all your scripts and playbooks in Git. The foundation of professional automation development starts with proper version control. All your automation code must live in a version control system like Git, with no exceptions for "quick scripts" or "temporary fixes."

Use branches and pull requests to collaborate. Branching strategies (like GitFlow or trunk-based development) let you safely develop new features and have controlled releases, while tagged releases give you easy rollback points. Writing clear, descriptive commit messages documents why each change was made.

Leaders must enforce reviews before code goes to production. Pull request workflows make sure peer reviews catch problems before they hit production. Integrating automated linting and syntax checking into your pull request process enforces consistent coding standards.

Using issue tracking systems (like Jira or GitHub Issues) helps you manage automation requests and bug reports systematically.

Adopting standardized directory structures makes it easy for any team member to understand and contribute.

3. Not testing before production

The mistake

You need to get a new VLAN configured across 50 switches, and your Ansible playbook worked perfectly in your small, isolated test lab. So, you run it directly in production. This approach, which skips comprehensive and realistic testing (including security validation), is a recipe for easily avoidable disasters.

Examples

A script to configure NTP on your routers accidentally wipes out all SNMP settings, leaving your network monitoring blind.

An Ansible playbook with hardcoded credentials and API keys gets accidentally committed to a public GitHub repository, exposing your production network.

Your automation processes bypass standard compliance and change control checks, creating months of potential GDPR or HIPAA violations that are only discovered during a painful audit.

A Python script grants excessive admin-level privileges to automation service accounts, creating massive security holes.

Impact

Your phone rings at 2 AM because the automation you pushed broke something critical, and you're now doing emergency, high-stress rollbacks. Your team starts to avoid automation because they've been burned by it too many times.

You spend more time firefighting problems caused by bad automation than you would have just doing things manually.

The security risks are often invisible until it's too late. Compliance violations can lead to massive regulatory fines. If your automation accounts have too many privileges, you've built a superhighway for attackers who compromise them.

What are some common security concerns related to network automation?

Credential management failures

A DevOps engineer commits an Ansible playbook to a public GitHub repository containing production SSH keys. Within hours, the repository is scraped by automated bots, and the network is compromised.

Excessive automation privileges

Many automation accounts are configured with full admin privileges "just in case." If compromised, attackers gain complete control.

Compliance bypass

Automation, if not properly integrated with change management, can modify firewall rules, VLANs, and access controls without necessary approval, directly violating corporate policies and external regulations.

How should network engineers test Automation before Production?

• Always test in a secure lab environment.
• Use EVE-NG, GNS3, or Cisco Modeling Labs to create a realistic simulation of your production network, including the same device types and software versions
• Build a CI/CD pipeline (using tools like GitHub Actions, GitLab CI, or Jenkins) to automatically run a series of tests on every change: linting for basic syntax and style; dry-run/check mode to validate logic without applying changes; unit tests for individual Python functions; and integration tests to validate automation in the simulated network.

4. Ignoring error handling and logging

The mistake

Building automation that assumes perfect network conditions and a single-vendor environment. Real-world networks are complex, multi-vendor ecosystems where failures are inevitable. Poor error handling amplifies these problems, leading to scripts that fail halfway through a run, leaving devices in a broken state with no record of what went wrong.

Examples

A Python script is designed to configure VLANs on 200 switches. On switch #87, it hits a network timeout. The script crashes immediately, leaving you with no idea which of the first 86 devices were updated and which of the remaining 113 were untouched.

Your Ansible playbooks work perfectly on your Cisco gear but fail with cryptic errors on your Arista switches, creating inconsistent configurations.

Your API calls to your network monitoring system fail, but your automation continues on without updating your IPAM or documentation, leading to documentation that no longer reflects reality.

Integration complexity

Modern network automation integrates with a whole array of other systems, and each one is a potential failure point: multi-vendor devices, management systems (IPAM, DNS, monitoring, ticketing), cloud platforms (AWS, Azure, GCP), security tools, and documentation systems.

Impact

Inconsistent device configurations all over your network. Silent failures that can create hidden security gaps. Partial deployments that leave your network in a weird, undefined state. Extremely time-consuming troubleshooting because you have no proper logging. A significant loss of trust in your automation's reliability. An increase in manual verification work, which totally negates the benefits of automation. Compliance violations from undocumented configuration drift. Extended outages because of poor failure recovery and rollback procedures.

How to avoid it: Design for failure from day one

Expect and plan for failures

In Ansible, use block, rescue, and always sections in your playbooks for graceful error handling and recovery. In Python, use try/except blocks around any network operation or API call, with clear logging in the except block.
Implement proper state racking

• Always automatically back up a device's configuration before you modify it.
• Your automation should log exactly what changed on each device during its run.
• Have automated rollback playbooks or functions ready to revert a device to its previous known-good state if a change fails.
• Store logs centrally (e.g., in Splunk, an ELK stack, or a dedicated Git repository). Don't let valuable logs die on the console.

CloudMyLab's Integration testing scenarios

Our hosted labs are perfect for testing these complex failure scenarios: multi-vendor deployments, partial failure recovery, external system integration, network partition scenarios, and API rate limiting.

5. Treating Automation as a one-off project

The mistake

Writing automation scripts, getting them to work once, and then just forgetting about them. Many engineers build something that solves an immediate problem but never maintain it as networks evolve, compliance requirements change, and underlying software platforms get updated.

Example

A team builds an Ansible playbook for VLAN provisioning in 2021. It works great on their Cisco 2960X switches running IOS 15.2. Today, the company upgrades to Catalyst 9300 switches running IOS-XE, and the old playbook fails catastrophically because the underlying API calls, module syntax, and command outputs have all changed.

Your automation was built when your company only worried about SOX compliance. Now, you also need to adhere to GDPR, but the automation still creates logs and handles data using the old standards.

An audit reveals your automated processes have been creating compliance violations for months. The service account your automation uses was created with temporary elevated privileges "just to get it working." Two years later, that account still has full admin access across your entire network because no one ever remembered to audit and reduce its permissions.

The engineer who built your BGP deployment automation left the company. The script still runs every month, but when it starts failing on your newer Juniper devices, no one on the team understands how it works or how to fix it.

Impact

You accumulate significant "technical debt" in the form of outdated, unreliable automation. Your automation becomes increasingly fragile, breaking with minor network changes. Your teams eventually just go back to manual CLI work because they no longer trust the automation.

How to avoid it: Treat your Automation like enterprise software

Treat your automation code not as a collection of throwaway scripts, but as a valuable software product. This means you need to implement proper lifecycle management and continuous validation. Maintain and refactor your scripts to keep them current.

Leaders must assign clear ownership for every piece of automation. You need proper documentation explaining what the automation does, why it exists, what systems it touches, and how to modify it safely.

Use pipelines to automatically test changes by integrating your automation code with your CI/CD pipeline to automatically test it against lab environments whenever a change is made.

With CloudMyLab, you can continually validate your automation against lab topologies that mirror your production environment, ensuring your automation stays current and reliable, not stale and dangerous.

Actionable recommendations

For Engineers starting in automation

• Learn idempotency, focus on defining desired outcomes, not just sending a series of commands.
• Put all automation code in Git.
• Test every change in a lab first (EVE-NG, GNS3, or CML).
• Write automation with error handling, logging, and rollback plan in mind.
• Maintain and update your codebase regularly.

For Leaders

• Invest in network labs and CI/CD infrastructure for automation testing.
• Encourage peer reviews and shared repos.
• Make automation a team practice, not a side project.
• Partner with platforms like CloudMyLab to provide engineers with ready-to-use labs for POCs and training.

Final Thoughts

Network automation is the foundation of modern, agile, and reliable infrastructure. Getting it right takes more than just writing a few scripts. It demands discipline, a collaborative culture, and access to safe, realistic testing environments.

Avoiding these five common mistakes will help you and your engineers build automation that is both powerful and trusted. And with platforms like CloudMyLab’s on-demand labs, you don’t have to risk your production network while learning, testing, and scaling your automation capabilities.

Contact us to discuss your lab requirements or start a free trial .

FAQ

What are the key challenges in implementing network automation?

The biggest challenges are skills gaps (engineers thinking in CLI instead of automation terms), lack of proper testing environments, poor version control practices, inadequate error handling, and treating automation as one-time projects instead of ongoing software development.

What are some common security concerns related to network automation?

Major security risks include hardcoded credentials in scripts, automation accounts with excessive privileges, bypassing compliance checks, and credential exposure in code repositories. Use secure credential management systems (like Ansible Vault or HashiCorp Vault) and test all automation in isolated lab environments.

How does network automation reduce operational costs?

Automation reduces costs by eliminating manual repetitive tasks, reducing human errors that cause outages, enabling faster deployments, and freeing engineers to focus on high-value design work instead of routine configuration changes.

What are the skills needed to become a successful network automation engineer?

Key skills include understanding idempotency, state management, error handling, version control (Git), at least one programming language (Python), infrastructure-as-code concepts, and multi-vendor API integration. Practice in safe lab environments is essential.

How should leaders enforce network automation best practices?

Leaders should require all automation code in version control, mandate peer reviews for production changes, invest in proper testing infrastructure, assign clear ownership of automation projects, and provide training through network labs from platforms like CloudMyLab.