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What is Network Automation?
What you'll learn
- What network automation actually means, in plain terms
- Why network engineers reach for automation instead of doing everything by hand
- The practical difference between a manual workflow and an automated one
- The kinds of network tasks automation is good at
- The basic shape of an automation workflow, from input to report
- Why automation gets more valuable — not less necessary — as a network grows
Listen to a guided explanation of this lesson.
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What is network automation?
Start with the simplest version: network automation is getting a computer to do network tasks that a person would otherwise type by hand.
That's it. If you've ever SSH'd into a switch, run show commands, and copied the output into a spreadsheet — that's a manual network task. If a script does the SSH login, runs the same commands, and writes the output to a file for you, that's the same task, automated.
The technical term for this is network automation: using code to configure, manage, monitor, or verify network infrastructure, instead of doing it interactively through a CLI session one device at a time.
A useful way to think about it
Automation doesn't do anything a network engineer couldn't do manually. It does the same things — just faster, more consistently, and across more devices at once.
Manual networking vs. automation
Picture a task you've probably done before: checking that NTP is configured and synced correctly on a handful of switches.
Done manually, that looks like: log into switch one, run the command, read the output, note the result. Log out. Log into switch two. Run the same command. Read the output. Note the result. Log out. Repeat for every switch.
Every switch gets the same treatment, one at a time, entirely driven by you sitting at the keyboard.
Automated, the shape of the task doesn't change — you still connect to each switch and run the same check — but who does the repeating changes. A script holds the list of switches, connects to each one, runs the command, and collects the results. You review the summary at the end instead of the raw session, switch by switch.
Manual vs. automated, side by side
- Engineer
- SSH to switch
- Switch 1check NTP, note result
- Repeat
- Switch 2check NTP, note result
- Repeat
- Switch 3check NTP, note result
- Engineer
- Automation script
- Multiple switcheschecked in one run
A real scenario: checking NTP across your switches
Say you're responsible for 40 switches across three buildings, and part of your weekly routine is confirming every switch has synced NTP — because a switch with the wrong clock makes log correlation and troubleshooting painful later.
Manually, that's 40 SSH sessions, 40 runs of show ntp status, and 40 results you have to read and remember. It's not hard. It's just repetitive, it eats an hour of your week, and it's exactly the kind of task where it's easy to lose count of which switch you already checked.
Automated, the same check becomes: a script reads your list of 40 switches, connects to each one, runs show ntp status, and hands you back a short report — something like "38 synced, 2 out of sync: SW-14, SW-27." Same task. Same command. A fraction of the time, and nothing to lose track of.
What can network automation actually do?
Once you see the pattern — connect, run something, look at the result — a lot of everyday network engineering work fits it. Common examples:
- Configuration — pushing consistent config changes across many devices
- Configuration backup — pulling and storing running configs on a schedule
- Compliance checking — comparing a device's config against a baseline
- Device inventory — keeping an accurate, current list of what's on the network
- Monitoring — regularly checking device or interface state
- Reporting — turning raw command output into something readable
- Validation — confirming a change did what it was supposed to do
- Provisioning — bringing a new device into service with standard config
- Troubleshooting assistance — gathering diagnostic output from many devices at once, fast
Not every one of these needs to be automated on day one — but every one of them is repetitive, well-defined, and done on more than one device. That combination is the signal that a task is a good automation candidate.
The basic automation workflow
Almost every automation task — from a simple NTP check to a full configuration push — follows the same basic shape:
- Inputwhat do you want to check or change?
- Inventorywhich devices?
- Connectopen an SSH or API session
- Executerun the command, or push the change
- Collect outputcapture what came back
- Validatedoes it match what you expected?
- Reportsummarize the result
You don't need Python to follow that — it's the same shape whether a person or a script is doing it. Automation just means a program executes those steps instead of you typing them.
Here's what that workflow looks like written down as code — you're not expected to read this as a Python lesson, just to see that it maps directly onto the diagram above:
devices = load_inventory("switches.csv") # Inventory
for switch in devices: # loop = "repeat for every device"
session = connect(switch) # Connect
output = session.send_command(
"show ntp status" # Execute
)
check_ntp_synced(output) # Collect output + Validate
send_report(devices) # ReportYou don't need to understand the syntax yet. Notice that every line maps to a step in the diagram above — automation is that workflow, written as steps a computer can repeat.
Why automation matters
None of this is about automation being able to do something a network engineer can't. It's about what changes as the number of devices grows:
- Scale — checking 3 devices by hand is fine; checking 300 by hand is a full day gone
- Consistency — a script runs the exact same command, the exact same way, on every device
- Repeatability — the same check can run every day, every week, or on demand, with no extra effort
- Reduced repetitive work — engineers spend less time on typing the same commands and more time on the problems that actually need judgment
- Reduced human error — no skipped devices, no typos from doing the 30th SSH session of the afternoon
- Faster operations — a 40-switch check that took an hour can take minutes
What automation doesn't do
Automation doesn't eliminate human error — it changes what kind of errors are possible. It removes the mistakes that come from repeating a manual step dozens of times (a typo on switch 23, a skipped device on switch 31). But a script is still code someone wrote, and code can have bugs of its own. That's exactly why testing changes in a safe lab environment before running them against production matters just as much once you're automating — you'll see this called out throughout the Labs section.
What you'll build on this platform
From here, this platform follows the same order most network engineers actually learn automation in: enough Python to be dangerous in a useful way, how network data (JSON, YAML, CLI output) actually looks, your first end-to-end automation script, and then connecting to real devices with Netmiko. Each lesson keeps following the same pattern you saw here — a simple explanation first, then a visual, then a real network example, then code, with quick checks along the way so you know it's landing before moving on.
Key takeaways
- Network automation is using code to do network tasks a person would otherwise do by hand over a CLI session.
- The manual and automated versions of a task are the same task — automation changes who repeats the work, not what the work is.
- Good automation candidates are repetitive, well-defined, and done across more than one device.
- Almost every automation task follows the same shape: input, inventory, connect, execute, collect output, validate, report.
- Automation becomes more valuable — not just faster — as the number of devices grows.
- Automation reduces repetitive mistakes, but scripts are still code and still need to be tested safely.
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Why Network Engineers Automate