Question 1
Difficulty: medium
Can you walk me through how you would design a network automation workflow for a repetitive change, such as VLAN provisioning across multiple switches?
Sample answer
I’d start by defining the exact business requirement and validating the source of truth before I write any automation. For VLAN provisioning, I’d want to confirm the approved VLAN ID, naming standard, switch list, and whether the change applies to access, distribution, or both. Then I’d build the workflow in stages: data validation, pre-checks, configuration push, post-checks, and rollback if needed. I prefer using templates or structured data models so the process stays consistent and easy to review. I’d also include idempotency so rerunning the job doesn’t create duplicate changes. Before production use, I’d test against a lab or a small set of noncritical devices and compare the intended state with the actual state after deployment. Finally, I’d log every action and make the results easy for operations teams to audit. My goal is to make the process safe, repeatable, and simple for other engineers to trust.
Question 2
Difficulty: medium
Tell me about a time you automated a network task that used to be done manually. What was the outcome?
Sample answer
In my last role, the team was spending a lot of time manually updating access control lists across several data center firewalls after application changes. It was slow, error-prone, and hard to audit. I worked with the network and security teams to understand the approval process and built a Python-based workflow that pulled change details from a ticketing system, validated them against policy rules, and generated the configuration changes automatically. I also added a review step so an engineer could approve the final output before deployment. The result was a big reduction in turnaround time, from hours down to minutes, and we cut down on configuration mistakes significantly. Just as important, the team became more comfortable with automation because they could see exactly what the script was doing. That project changed how the group approached repetitive work, and it gave us a foundation for automating other standard changes later.
Question 3
Difficulty: medium
How do you ensure your automation is safe and reliable before running it in production?
Sample answer
I treat production automation like any other critical change: it needs testing, visibility, and a rollback plan. First, I validate the input data so the automation only accepts known-good values and doesn’t rely on assumptions. Then I test in a lab or staging environment that closely mirrors production, because network behavior can vary a lot between vendors and versions. I also like to build in dry-run or preview mode so I can inspect the exact commands or API calls before anything is pushed. Logging is important too; I want clear records of what was changed, when, and by which job. For reliability, I add retries only where they make sense, and I avoid hiding failures. If something goes wrong, the automation should stop cleanly and provide enough detail to fix the issue quickly. In production, I prefer small rollout batches at first, with post-change validation after every run.
Question 4
Difficulty: easy
What experience do you have with Python, APIs, or configuration management tools in network automation?
Sample answer
My strongest experience is with Python and API-driven automation, especially for tasks where consistency and speed matter. I’ve used Python to integrate with network devices, ticketing systems, and inventory sources, mostly through REST APIs and structured data formats like JSON and YAML. I’m comfortable writing scripts that pull device state, compare it to an expected configuration, and generate reports or changes. I’ve also worked with configuration management and orchestration tools to standardize repetitive tasks, although I don’t believe any one tool is the answer for everything. My approach is to choose the tool that best fits the problem: Python for custom logic, APIs for clean system integration, and templating or orchestration when the workflow is broader and needs repeatability. I’m also careful about code quality, so I use version control, peer review, and testing wherever possible. That discipline makes the automation easier to maintain as the network evolves.
Question 5
Difficulty: hard
How would you handle a situation where your automation script works in the lab but fails in production on certain devices?
Sample answer
I’d treat that as a troubleshooting and data-quality problem, not just a code problem. First, I’d compare the lab devices and the production devices to identify what’s different: software version, vendor, API behavior, permissions, command syntax, or even timing issues. I’d check logs from the script and from the devices to pinpoint where the failure happens. If the issue is device-specific, I’d isolate the failing models or versions and adjust the logic to handle those differences cleanly instead of forcing one generic path. I’d also confirm whether the production environment has stricter access controls, rate limits, or network latency that the lab doesn’t reflect. Once I understood the root cause, I’d fix the script, retest against a production-like subset, and add a regression test so the same issue doesn’t return. I’d also document the exception clearly so the team knows what to expect with those devices.
Question 6
Difficulty: medium
How do you balance automation speed with the need for change control and compliance in a network environment?
Sample answer
I think speed and control can work together if the process is designed well. The key is to automate the repetitive work without bypassing the approval and audit steps that keep the environment safe. In practice, that means pulling approved change requests from a system of record, validating them against policy, and only then allowing the automation to execute. I also like to make the workflow transparent so reviewers can see the intended impact before it runs. For compliance, I’d ensure the automation keeps detailed logs, stores versioned code in source control, and produces evidence of pre-checks and post-checks. If the organization requires segregation of duties, I’d design the process so one person can request the change, another can approve it, and the automation handles execution. That way, the network team gets the benefits of faster delivery, while auditability and governance stay intact.
Question 7
Difficulty: easy
Describe a time you had to convince network engineers who were skeptical of automation. How did you approach it?
Sample answer
I’ve found that skepticism usually comes from concern about losing control or introducing risk, and I respect that. In one case, the team was hesitant about automating device backups and configuration validation because they were used to doing it manually. Instead of pushing automation as a replacement, I started with a small, low-risk use case that solved a real pain point. I showed how the automation saved time, reduced missed backups, and gave everyone a cleaner audit trail. I also involved one of the senior engineers early so they could review the logic and suggest improvements. That changed the conversation from “Should we trust automation?” to “How can we make this useful?” I think that’s the right way to build confidence: start small, be transparent, and show measurable results. Once people see that automation supports their work instead of replacing their judgment, adoption usually grows naturally.
Question 8
Difficulty: hard
What would you do if an automation run pushed an incorrect configuration to a large set of switches?
Sample answer
My first priority would be containment. I’d stop the automation immediately if it was still running and identify the blast radius: which devices were affected, what changed, and whether traffic is impacted. Then I’d compare the deployed state against the intended state and determine the safest rollback path. If a rollback is possible and low-risk, I’d restore the previous known-good configuration in batches, not all at once, so I can monitor for side effects. At the same time, I’d communicate clearly with the network, operations, and incident response teams so everyone understands the impact and the next steps. After stability is restored, I’d do a root-cause review to understand why the wrong configuration was allowed through. That might mean better input validation, stricter approval gates, stronger testing, or a safer rollout design. I’d also update the runbook and add safeguards so the same failure mode is less likely in the future.
Question 9
Difficulty: medium
How do you decide whether to use scripting, orchestration, or a full automation platform for a network task?
Sample answer
I decide based on scope, complexity, and who needs to operate the solution long term. If the task is small, highly specific, and owned by a technical team, a well-tested script may be the fastest and most maintainable option. If the process spans multiple systems, requires approval steps, or needs repeatable workflows across a team, orchestration starts to make more sense. A full automation platform is useful when you need centralized control, role-based access, reporting, and integration with a larger operational model. I don’t choose a tool because it’s popular; I choose it because it fits the operational reality. I also think about lifecycle support. If only one engineer understands the tool, that becomes a risk. So I look for solutions that are easy to document, test, and hand off. In many cases, the best answer is a combination: scripts for device-level logic and orchestration for the broader process.
Question 10
Difficulty: easy
What metrics would you use to measure the success of a network automation program?
Sample answer
I’d look at both operational and quality metrics. On the operational side, I’d measure time saved on repetitive tasks, change turnaround time, and the percentage of changes executed through automation versus manually. On the quality side, I’d track error rates, failed change attempts, rollback frequency, and the number of incidents caused by configuration mistakes. I’d also want adoption metrics, because automation that nobody uses isn’t delivering value. For example, if engineers are still bypassing the workflow, that tells me the process may be too complex or doesn’t fit their needs. I’d also pay attention to auditability and compliance outcomes, such as whether change records are complete and whether backups or validation steps are consistently captured. Over time, I’d expect automation to reduce repetitive workload, improve consistency, and free engineers to focus on higher-value design and troubleshooting work. The best metric, though, is whether the team trusts the automation enough to rely on it.
