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<v Speaker 1>Welcome to the deep dive. We're here to cut through

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<v Speaker 1>the noise and get straight to what matters. And today, Wow,

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<v Speaker 1>we're jumping into a really big shift happening right now

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<v Speaker 1>in it specifically network engineering. The old roles, the way

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<v Speaker 1>things were always done, it's all changing and changing really fast.

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<v Speaker 1>So our mission today is basically to give you a

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<v Speaker 1>shortcut a way to understand this whole transformation. We're looking

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<v Speaker 1>at how Python Linux are becoming well essential tools for

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<v Speaker 1>automating networks. We're drawing on insights from introduction to Python

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<v Speaker 1>network automation and you know, other solid sources. Think of

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<v Speaker 1>this as your guide to the skills, the mindset, and yeah,

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<v Speaker 1>the practical stuff you need to become what people are

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<v Speaker 1>calling a hybrid engineer. Okay, so let's unpack this. Think

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<v Speaker 1>back maybe ten years, maybe a bit more, the traditional

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<v Speaker 1>network engineer role. What did that look like. You were

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<v Speaker 1>probably you know, knee deep in installing kit, configuring lands wands,

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<v Speaker 1>a real master of OSPF, e I, g RP, BGP,

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<v Speaker 1>all that good stuff. Your world was pretty much OSI

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<v Speaker 1>layers one through four, right happy in that specific bubble.

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<v Speaker 2>Yeah, definitely. And Cisco Systems, I mean they were the

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<v Speaker 2>name the one stop shop for pretty much everything network

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<v Speaker 2>related for a long long time. Absolutely, but it's it's

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<v Speaker 2>fascinating how quickly things started to shift. You had these

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<v Speaker 2>disruptive forces appearing. Virtualization started getting big software to define

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<v Speaker 2>networking SDN, those concepts started bubbling up, and then for

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<v Speaker 2>some open source tools really took off. Now automation itself,

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<v Speaker 2>I mean that's not new, right, goes way back to

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<v Speaker 2>the Industrial Revolution, nineteen hundred stuff. But today, yeah, it's

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<v Speaker 2>the hot topic, not just networking, but security, data center, cloud,

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<v Speaker 2>you name it. It's fundamental now.

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<v Speaker 1>Yeah, it really is. And here's something our sources really

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<v Speaker 1>drive home. Kind of a stark reality. If you're just

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<v Speaker 1>relying on let's say, passive learning in this market, the

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<v Speaker 1>future looks a bit grim. It feels like history repeating itself.

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<v Speaker 1>You know, adapt or well or get left behind. Yeah, exactly.

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<v Speaker 1>And the core change is that network devices themselves are

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<v Speaker 1>moving from physical boxes to virtual things. And here's the kicker.

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<v Speaker 1>They're increasingly controlled by AP application programming interfaces. Think about

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<v Speaker 1>VMware's NSX or Cisco's ACI. These aren't just products. They

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<v Speaker 1>show this massive shift in.

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<v Speaker 2>Architecture precisely and That's exactly why this idea of a

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<v Speaker 2>hybrid engineer isn't just like a nice to have anymore.

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<v Speaker 2>It's becoming essential. We're talking about people who, yes, have

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<v Speaker 2>their deep knowledge in their main areas a networking, but

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<v Speaker 2>then they stretch, they build skills in other vital areas

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<v Speaker 2>like Linux and coding, Python, maybe go. It creates the

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<v Speaker 2>sort of T shaped knowledge profile, deep expertise but broad

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<v Speaker 2>adaptability T shaped.

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<v Speaker 1>I like that. It paints a good picture. Okay, so

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<v Speaker 1>let's focus on the tool that seems to be at

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<v Speaker 1>the absolute center of this. Python. Its popularity has just exploded.

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<v Speaker 1>I mean some reports show at overtaking Java, JavaScript and

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<v Speaker 1>developer preference. From your perspective, what is it about Python

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<v Speaker 1>that makes it the go to language for network automation.

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<v Speaker 2>Well, it's a combination of things. Really. Python hits this

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<v Speaker 2>sweet spot between being simple enough to get started but

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<v Speaker 2>powerful enough to do complex things. It's got that reputation

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<v Speaker 2>for a low barrier to entry, right, anyone can basically

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<v Speaker 2>start learning. But and this is important, there's a misconception

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<v Speaker 2>there easy to start, yes, truly proficient that takes real persistence, passion,

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<v Speaker 2>Even you can't just watch videos passively. You need projects,

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<v Speaker 2>you need real problems you want to solve with code.

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<v Speaker 2>That's what keeps you going because fundamentally automation means writing

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<v Speaker 2>code lines of instructions. AI is amazing, but it's not

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<v Speaker 2>yet at the point where it can just replicate the

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<v Speaker 2>intuition and experience of a seasoned network engineer. You still

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<v Speaker 2>need the logic.

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<v Speaker 1>That's a really critical point. So the human understanding the

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<v Speaker 1>logic crafting that's still key even with AI coming along.

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<v Speaker 1>It's about using code to solve problems intelligently exactly. So

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<v Speaker 1>to do that you need Python's building blocks. What are

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<v Speaker 1>some of those core concepts that really give a network

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<v Speaker 1>engineer automation power.

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<v Speaker 2>Okay, think of it this way. Python is how you

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<v Speaker 2>talk to your network now and when you get data

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<v Speaker 2>back from devices. It comes in different shait papes for

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<v Speaker 2>network tasks. Honestly, two data structures are your absolute work courses,

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<v Speaker 2>lists and dictionaries.

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<v Speaker 1>Lists and dictionaries.

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<v Speaker 2>A list is perfect when you need an ordered sequence,

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<v Speaker 2>like say, all the interface names on a switch, just

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<v Speaker 2>a simple list. A dictionary, though, is perfect for configuration.

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<v Speaker 2>You have a key like host name and a value

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<v Speaker 2>like rooter one or lan ten, name is the key,

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<v Speaker 2>sales is the value.

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<v Speaker 1>Ah key value pairs, got it right.

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<v Speaker 2>If you get comfortable manipulating those two lists and dictionaries,

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<v Speaker 2>you've honestly tackled maybe eighty percent of the data wrangling

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<v Speaker 2>you'll do in network automation.

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<v Speaker 1>That makes immediate sense. Lists for sequences, dictionaries for configs

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<v Speaker 1>very practical. What about making scripts smart? Making decisions?

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<v Speaker 2>Right, that's where your control statements and loops come in

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<v Speaker 2>super important. You've got if, l if and else that

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<v Speaker 2>lets your script decide, okay, if this interface status is down,

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<v Speaker 2>then I need to log it and maybe send an.

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<v Speaker 1>Alert conditional logic exactly.

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<v Speaker 2>And then you have loops like four loops and wild loops.

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<v Speaker 2>These are amazing for repetitive stuff. Imagine configuring the same

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<v Speaker 2>description on say fifty switch ports. A four loop handles

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<v Speaker 2>that beautifully. No more copy pasting fifty times.

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<v Speaker 1>Oh yeah, I can see the appeal there immediately.

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<v Speaker 2>These loops and conditions they make your scripts dynamic, They react,

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<v Speaker 2>they repeat intelligently. They're not just static command centers.

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<v Speaker 1>So building intelligence into the script itself, and as scripts

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<v Speaker 1>get bigger, organization must become pretty important. Right. That's modules

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<v Speaker 1>and packages.

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<v Speaker 2>Absolutely critical, especially if you're working in a team or

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<v Speaker 2>just want to reuse your code later. Think of a

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<v Speaker 2>module as basically just a single Python file, a dot

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<v Speaker 2>piy file. It might contain a few functions you wrote

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<v Speaker 2>for a specific task, like getting neighbor information from a router.

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<v Speaker 1>Okay.

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<v Speaker 2>A package is like a folder full of related modules.

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<v Speaker 2>It helps you structure bigger projects. Maybe you have a

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<v Speaker 2>package for Cisco iOS tasks, another for Juniper Geno's tasks.

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<v Speaker 2>Keeps things neat reusable.

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<v Speaker 1>Like libraries of your own tools.

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<v Speaker 2>Exactly. One more thing here, error handling. It absolutely must

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<v Speaker 2>learn how to use try and accept blocks. Networks are messy,

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<v Speaker 2>devices might not respond, files might be missing. Your script

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<v Speaker 2>needs to handle that gracefully with try accept, not just

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<v Speaker 2>you know, crash and burn makes your automation robust.

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<v Speaker 1>Robustness yeah, key for anything production. Okay, So Python gives

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<v Speaker 1>us the language, the data, structure, is the logic, the organization.

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<v Speaker 1>But where does this code actually live and run? That

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<v Speaker 1>leads us to Linux, doesn't it? And I have to

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<v Speaker 1>admit I really wish I'd taken Linux more seriously much

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<v Speaker 1>earlier in my career. It felt like this niche thing back.

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<v Speaker 2>Then you're definitely not alone there. It's a common regret

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<v Speaker 2>because while Windows, yeah, it dominates desktops, linuxes without a

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<v Speaker 2>doubt the default OS for serious enterprise level automation period.

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<v Speaker 1>Why is that? What makes it the go to?

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<v Speaker 2>It's a flexible, it's usually more performance for server tasks,

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<v Speaker 2>it's often more cost effective and has a really strong

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<v Speaker 2>security posture when configured right. It's just built for running

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<v Speaker 2>these kinds of back end services, automation engines, and yeah,

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<v Speaker 2>your Python scripts.

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<v Speaker 1>So for a network engineer who isn't aiming to become

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<v Speaker 1>a full time Linux ADMN, what are the must know

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<v Speaker 1>fundamentals the essentials?

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<v Speaker 2>Great question. You need to be comfortable on the command line,

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<v Speaker 2>that's number one. Knowing a bit about its U and

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<v Speaker 2>IX roots helps because many commands are the same across

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<v Speaker 2>different versions or distributions like a Buntu or cinos.

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<v Speaker 1>Right, the different flavors exactly.

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<v Speaker 2>You need to navigate the directory structures. Nowhere common config

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<v Speaker 2>files live because on Linux almost everything is a text file,

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<v Speaker 2>which means you need to get good with a command

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<v Speaker 2>line text editor like v or Nano. Essential for making

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<v Speaker 2>quick changes on a server without a GUI.

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<v Speaker 1>Okay, command line directories, text editors, what else.

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<v Speaker 2>Basic system checking and management commands things like l's t

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<v Speaker 2>CE files cat or less to view files, seep A copy,

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<v Speaker 2>MB to move or rename standard stuff. Then networking commands

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<v Speaker 2>are vital ep editors to see interface configs, replacing the

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<v Speaker 2>older if can fig and netstat is super useful for

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<v Speaker 2>seeing what ports are open, what services.

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<v Speaker 1>Are listening, checking connectivity listening ports yea.

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<v Speaker 2>And crucially, you'll likely need to install and manage some

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<v Speaker 2>basic network services on your Linux box to support your automation,

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<v Speaker 2>things like a TFTP server I mean an FTP server

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<v Speaker 2>using vsftpd and definitely an NTP server using Krony to

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<v Speaker 2>keep time synchronized. This lets you build your own little

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<v Speaker 2>all in one lab server, which is often what your

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<v Speaker 2>network devices will interact with for things like image transfers

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<v Speaker 2>or can fig backups.

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<v Speaker 1>So the goal isn't Linux mastery necessarily, not at all.

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<v Speaker 1>It's about having the confidence and the core skills to

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<v Speaker 1>operate that Linux environment where your automation runs right without

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<v Speaker 1>breaking things.

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<v Speaker 2>That's the sweet spot exactly. You need to be competent

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<v Speaker 2>enough to manage your automation platform effectively.

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<v Speaker 1>Okay, makes sense now, you the listener might be thinking

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<v Speaker 1>this sounds powerful, but theory is one thing, and our

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<v Speaker 1>sources really hammer this home. If you do not build

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<v Speaker 1>your lab yourself, then you will not know how everything works.

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<v Speaker 1>Just watching videos that passive learning it's not good enough.

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<v Speaker 1>You absolutely have to get your hands dirty build it yourself.

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<v Speaker 2>Couldn't agree more. And virtualization is your absolute best friend here.

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<v Speaker 2>It's how you build that playground. You need to understand

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<v Speaker 2>the basic types. There are Type one hypervisors, the bare

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<v Speaker 2>metal ones like VMware ESXi you find in data centers,

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<v Speaker 2>and then type two, which run like an application on

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<v Speaker 2>your desktop OS, perfect for labs and experiments. VMware Workstation

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<v Speaker 2>Pro is a really popular powerful Type two option lets

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<v Speaker 2>you build complex labs just on your own PC.

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<v Speaker 1>Okay, so workstation pro for the environment. What about the

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<v Speaker 1>network devices themselves? Can you run routers and switches virtually?

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<v Speaker 2>Absolutely? That's where tools like GNS three come in. Genius

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<v Speaker 2>theory is fantastic. It started with dynamips for emulating older

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<v Speaker 2>Cisco hardware, but now it's a full graphical environment. You

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<v Speaker 2>can load actual Cisco iOS images into it, older ones

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<v Speaker 2>like the twelve on one x train or newer virtual

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<v Speaker 2>images like the ones from Cisco Modeling Labs, the c

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<v Speaker 2>amount pe images for L two L three functionality.

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<v Speaker 1>So you're running real Cisco code.

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<v Speaker 2>Exactly real code, emulated hardware. You can graphically connect virtual routers, switches,

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<v Speaker 2>even little virtual PCs vpcs to test connectivity. You could

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<v Speaker 2>even bridge this virtual network to your actual PCs network

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<v Speaker 2>using things like Microsoft loop back adapters. It creates this

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<v Speaker 2>amazing self contained sandbox.

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<v Speaker 1>Wow. So this integrated lab environment running Linux, running GNS

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<v Speaker 1>three with virtual devices, that really sounds like the key.

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<v Speaker 1>It's the closest you can get to actually practice and

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<v Speaker 1>experience everything that occurs in the real network environment. Right, build, break, fix,

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<v Speaker 1>automate all safely, precisely.

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<v Speaker 2>It's where the Python knowledge, the Linux skills, it all

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<v Speaker 2>comes together in a practical way. It's indispensable for learning

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<v Speaker 2>this stuff properly.

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<v Speaker 1>Okay, let's pivot now to the real world application. How

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<v Speaker 1>does Python actually talk to network devices? Because let's face it,

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<v Speaker 1>even with APIs growing a ton of gear out there

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<v Speaker 1>still relies on the command line via telnet and SSH.

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<v Speaker 2>That's very true, and Python is excellent for automating those

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<v Speaker 2>interactions too. There are standard libraries like telnet live built in,

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<v Speaker 2>but more often you'll use more powerful third party libraries.

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<v Speaker 2>Is a popular one for SSH at a lower level.

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<v Speaker 2>And then there's Netmeko, which builds on paramco and is

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<v Speaker 2>specifically designed for network devices. It'd understand different vendor prompts, handles,

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<v Speaker 2>pagination makes life much.

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<v Speaker 1>Easier netnico Okay, so what can you do with.

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<v Speaker 2>These ah tons of repetitive tasks? Think about configuring the

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<v Speaker 2>same VLAN on say twenty different access switches. Instead of

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<v Speaker 2>logging into each one, you write a simple Python loop

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<v Speaker 2>using netmeico connect configure, disconnect next switch. Done in seconds.

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<v Speaker 1>That alone sounds like a huge time saver it is.

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<v Speaker 2>Or backing up configurations, schedule a Python script to log

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<v Speaker 2>into all your core devices every night and save the

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<v Speaker 2>running config to your Linux server via SEP or TFTP.

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<v Speaker 1>Nice. And what about security? You mentioned telnet earlier.

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<v Speaker 2>Yeah, this is a big one. Telnet is insecure, sends

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<v Speaker 2>passwords in clear text. You can write a Python script

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<v Speaker 2>to scan your network ranges, check if telnet is enabled

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<v Speaker 2>on devices and if it finds telnet open. Use Python

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<v Speaker 2>with netmeko again to log in via SSH, disable the

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<v Speaker 2>Telnet service and maybe be ensure SSH is properly configured.

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<v Speaker 2>It's automating security policy enforcement.

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<v Speaker 1>That's moving beyond convenience into really critical operational security, powerful stuff.

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<v Speaker 1>What about monitoring, keeping an eye on device health?

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<v Speaker 2>For that, SNNP is still king the Simple Network Management Protocol.

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<v Speaker 2>It's been around forever but is still widely used. You

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<v Speaker 2>need to grasp the basics the idea of polling, where

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<v Speaker 2>your management station asks devices for data versus traps, or

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<v Speaker 2>devices send alerts automatically if something bad happens.

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<v Speaker 1>Okay, polling versus traps.

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<v Speaker 2>In the terminology, SMI is the structure of management information,

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<v Speaker 2>how data is organized. The MIIB management information based of

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<v Speaker 2>like the database of things you can monitor on a device,

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<v Speaker 2>and crucially oid's object identifiers. These are like unique addresses

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<v Speaker 2>for specific pieces of data like one point three point

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<v Speaker 2>six two point one, put one to one point one

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<v Speaker 2>put one point one point one. Did is typically system

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<v Speaker 2>uptime or specific Cisco ID like one put through six

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<v Speaker 2>point four point nine and nine put one button on

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<v Speaker 2>one point five might be this five minute CPU load average.

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<v Speaker 1>There's a great Python module called pi sm it lets

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<v Speaker 1>you easily perform sn mp gt request to fetch specific OIDs,

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<v Speaker 1>or even SMMP set request change configuration, though that's less

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<v Speaker 1>common and needs care. You can also use command line

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<v Speaker 1>tools on Linux like simp walk to explore devices m

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<v Speaker 1>ib and find useful OIDs.

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<v Speaker 2>So give us a practical example. How could you use this?

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<v Speaker 1>Okay, imagine this. You write a Python script using pizmpm

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<v Speaker 1>to pull your main router's CPU utilization o ID every

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<v Speaker 1>few minutes using secure sm mpv three. The script checks

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<v Speaker 1>the return value if the CPU load goes above, say ninety.

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<v Speaker 2>Percent right, instead of just logging it. The script could

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<v Speaker 2>then use the twili o API, maybe running inside a

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<v Speaker 2>lightweight dock or container, send an SMS alert straight to

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<v Speaker 2>your phone.

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<v Speaker 1>Proactive alerting via text message that beats a three am

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<v Speaker 1>phone call waking you.

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<v Speaker 2>Up, doesn't it, jest. It's about getting ahead of problems.

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<v Speaker 2>It's efficiency, yes, but it's also about sanity.

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<v Speaker 1>Sanity definitely value and to make that check happen regularly automatically.

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<v Speaker 1>That's Linux's KRON again precisely.

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<v Speaker 2>Pron is the simple, super reliable Linux scheduler. You write

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<v Speaker 2>a kron tab entry that just says, run this Python

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<v Speaker 2>script every five minutes, set it and forget it. Your

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<v Speaker 2>monitoring is now automated and persistent.

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<v Speaker 1>Perfect. Now there are even more advanced tools out there too, right,

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<v Speaker 1>we should probably mention them briefly.

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<v Speaker 2>Yeah, definitely beyond direct scripting with netmko or piesapp, you'll

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<v Speaker 2>quickly run into tools like antsable. Ansable is huge for

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<v Speaker 2>configuration management. It's agentless, mainly uses SSH and you define

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<v Speaker 2>the desired state in simple yamo files called playbooks. Very

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<v Speaker 2>powerful for ensuring consistency across many devices. It has modules

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<v Speaker 2>like iOS facts to gather device info easily email playbooks.

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<v Speaker 1>Right, and Cisco has their own stuff too.

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<v Speaker 2>We do piats often used with its parsing library called Genie.

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<v Speaker 2>It's a Cisco endorsed Python framework really geared cords, network

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<v Speaker 2>testing and validation. You can use gene to parse complex

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<v Speaker 2>show command put like show version into structured Python data,

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<v Speaker 2>dictionaries and lists. Again makes it easy to grab say

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<v Speaker 2>the uptime or serial number. You can even export that

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<v Speaker 2>data to Excel, maybe visualize it with matt.

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<v Speaker 1>Plotlob data extraction and testing. Okay, and Docker you mentioned

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<v Speaker 1>for the SMS alert Right.

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<v Speaker 2>Docker isn't strictly automation, but it's containerization. It lets you

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<v Speaker 2>package your Python script and all its dependencies into a small,

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<v Speaker 2>isolated container. This ensures your script runs the same way everywhere,

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<v Speaker 2>whether it's on your laptop or a server. Great for

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<v Speaker 2>deploying small focused tools like monitoring scripts or alert handlers.

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<v Speaker 1>Okay, so we have scripting, monitoring, configuration, management, testing frameworks.

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<v Speaker 1>If we try to tile this together, where does it

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<v Speaker 1>really culminate. What's a complex, high value task that this

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<v Speaker 1>approach can tackle.

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<v Speaker 2>Well, if we connect this to the bigger picture, I

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<v Speaker 2>think one of the classic high stress tasks is manually

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<v Speaker 2>upgrading Cisco iOS software in a live production network. Think

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<v Speaker 2>about it, two four seven environment tight change windows, the

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<v Speaker 2>immense pressure not to cause an adage. There were distinct phases,

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<v Speaker 2>the pre checks, the actual upgrade, the critical post checks.

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<v Speaker 2>It's incredibly labor intensive and nerve wracking.

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<v Speaker 1>Oh absolutely, I've been there. It's stressful. So how can

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<v Speaker 1>Python help break down that labor intensive workflow?

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<v Speaker 2>This is where all the pieces come together beautifully, that complex,

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<v Speaker 2>stressful process. Python can turn it into manageable, automatable, modular steps.

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<v Speaker 2>You could have a Python script that first connects via

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<v Speaker 2>sash net miko to run pre checks. Is there enough

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<v Speaker 2>flash space for the new image. What's the current boot variable?

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<v Speaker 2>Save the current can.

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<v Speaker 1>Fig okay the verification stage.

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<v Speaker 2>Then another part of the script could securely transfer the

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<v Speaker 2>new iOS image using SEP or maybe TFTP from your

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<v Speaker 2>Linux server. It can even verify the MTFI hash of

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<v Speaker 2>the transferred file to ensure it wasn't.

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<v Speaker 1>Correct integrity checks nice.

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<v Speaker 2>Then configure the boot system variables to point to the

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<v Speaker 2>new image, save the config and then initiate the reload.

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<v Speaker 1>The point of no return.

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<v Speaker 2>Well hopefully not is after the device reboots. Your script

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<v Speaker 2>connects again to run post checks. Did it boot the

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<v Speaker 2>right image? Or the interfaces up? Can it? Pin key neighbors?

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<v Speaker 2>Is routing working all verified automatically?

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<v Speaker 1>Wow? Breaking that massive task down into automated, verifiable steps

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<v Speaker 1>that really highlights the power exactly.

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<v Speaker 2>It takes that high stress, error prone manual process and

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<v Speaker 2>makes it far more reliable, repeatable, and faster. This is

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<v Speaker 2>where all those Python basics, Linux skills, netmko s and

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<v Speaker 2>mp checks maybe they all converge to solve a really

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<v Speaker 2>significant operational.

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<v Speaker 1>Challenge that really crystallizes the goal, doesn't it. It's not

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<v Speaker 1>about kicking engineers out, not at all. It's about deeply

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<v Speaker 1>understanding what engineers do, their decision processes, their checks and balances,

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<v Speaker 1>and then building tools that amplify their effectiveness, tools that.

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<v Speaker 2>Make their work more efficient, way more accurate, and less

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<v Speaker 2>prone to simple human error during repetitive tasks. It fundamentally

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<v Speaker 2>allows engineers to scale their impact to do more work

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<v Speaker 2>using an application programming interface.

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<v Speaker 1>Essentially, they shift from being purely manual operators to being

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<v Speaker 1>the architects and overseers of intelligent automation.

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<v Speaker 2>That's a great way to put it.

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<v Speaker 1>Well, what a journey we've covered today. Seriously. We started

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<v Speaker 1>with this rapidly changing network engineering landscape, the absolute need

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<v Speaker 1>now to become this hybrid engineer. Then we dove into

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<v Speaker 1>Python basics, the core data types and logic needed, navigated

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<v Speaker 1>essential Linux skills for running our automation, talked about building

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<v Speaker 1>those crucial virtual labs with GNS three and VMware to

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<v Speaker 1>get hands on practice, and finally brought it all together

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<v Speaker 1>with real world automation using Python for SSH, SNMP, monitoring,

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<v Speaker 1>scheduling with Kron, and even tackling something as complex as

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<v Speaker 1>iOS upgrades. So what does this all really mean for

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<v Speaker 1>you listening right now?

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<v Speaker 3>I think the key takeaway is that making this transition

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<v Speaker 3>becoming that cross functional engineer with solid networking plus links

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<v Speaker 3>chops plus coding ability. It's not just a nice to

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<v Speaker 3>have for your CV anymore. It really feels like a

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<v Speaker 3>necessity now for staying relevant for career growth in this

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<v Speaker 3>IT world that's just shifting so quickly under our feet.

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<v Speaker 2>Absolutely, and maybe here's a final thought to leave you

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<v Speaker 2>with something to chew on. Take a hard look at

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<v Speaker 2>your own day to day work right now, what specific task,

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<v Speaker 2>even a small one, could you potentially automate using some

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<v Speaker 2>of these ideas, And then flip the question, Even with

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<v Speaker 2>that automation, what unique human insight, what critical thinking or

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<v Speaker 2>complex problem solving skill that you possess would still be

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<v Speaker 2>absolutely essential because the real power here, the future of

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<v Speaker 2>network programmability isn't just the raw automation. It's the intelligent

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<v Speaker 2>application of it, the smart processing and interpretation of the

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<v Speaker 2>data it provides, and that intelligence, that guidance that still

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<v Speaker 2>comes best from experienced engineers like you.

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<v Speaker 1>Powerful thoughts, indeed, focus on where you add unique human value.

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<v Speaker 1>Excellent point to end on. Thanks so much for joining

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<v Speaker 1>us on this deep dive. Until next time, keep learning,

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<v Speaker 1>keep exploring that automation potential and keep diving deep