The Network Automation Skill Gap — And Why It's Your Opportunity
Founder explains the growing demand for network automation skills. Python, Ansible, APIs for network engineers — not replacing manual work, augmenting it. What employers are hiring for in 2026.
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The Skill Gap Is Real
I am going to share an observation that has shaped my thinking about the future of networking careers over the past five years. There is a growing chasm in the networking industry — a gap between what organizations need and what most network engineers can deliver. On one side, you have enterprises with thousands of network devices that need to be configured consistently, monitored continuously, and updated frequently. On the other side, you have a workforce that still does this work device by device, CLI session by CLI session, copy-pasting configurations from Notepad and hoping they did not miss a line. The gap between these two realities is the network automation skill gap, and it represents one of the most significant career opportunities in networking today.
Let me quantify what I am seeing. When I speak with hiring managers at large enterprises, service providers, and vendors — companies that employ the engineers we train — the most common unmet hiring requirement is not "needs CCIE" or "needs 10 years of experience." It is "needs automation skills." They want engineers who can write a Python script to pull interface statistics from 200 switches. They want engineers who can build an Ansible playbook to deploy a VLAN across 50 sites simultaneously. They want engineers who understand REST APIs well enough to integrate their network monitoring with their ticketing system. And they are struggling to find these engineers because the traditional networking career path — CCNA, then CCNP, then maybe CCIE — does not include these skills in any meaningful depth.
The irony is that network automation is not new. Cisco has been talking about programmability since the early DevNet days. Python libraries like Netmiko and NAPALM have been mature for years. Ansible has had a networking module since 2016. The tools exist. The demand exists. What does not exist in sufficient quantity is network engineers who have invested the time to learn these tools alongside their traditional routing and switching expertise. And that scarcity is precisely what makes this an opportunity.
I want to be honest about something. When automation first started gaining traction in networking conversations, there was genuine fear among engineers that it would replace them. "If you can automate VLAN deployment, why do you need me?" The fear was understandable but misplaced. Automation does not replace network engineers — it changes what network engineers do. Instead of spending three hours copy-pasting VLAN configurations into 30 switches, you spend 30 minutes writing a playbook that deploys the VLAN to all 30 switches in two minutes. The three hours you saved? You spend them on design work, troubleshooting complex issues, capacity planning, and security reviews — the high-value work that cannot be automated because it requires judgment, context, and expertise. Automation does not eliminate the network engineer. It eliminates the tedious, error-prone parts of the network engineer's job and frees them for work that is more interesting, more valuable, and harder to outsource.
I have had this conversation with hundreds of engineers who resist learning automation. Their reasons are consistent: "I am not a programmer," "my network is too small to need automation," "I will learn it when I need it." Each of these is understandable but ultimately self-defeating. You are not becoming a programmer — you are adding a tool to your engineering toolkit. No network is too small — even a 20-device network benefits from automated compliance checking and configuration backup. And waiting until you need automation to learn it means learning under pressure, which is the worst possible time to acquire a new skill. The engineers who invested in automation skills before they were urgently needed are the ones who were ready when the demand arrived — and they were rewarded accordingly.
The Window Is Open — But It Will Close
What Network Automation Actually Looks Like
There is a misconception about network automation that I encounter frequently among traditional network engineers. They imagine it means building complex software applications — writing thousands of lines of code, managing databases, deploying web services. That misconception scares them away because they did not sign up to be software developers. So let me describe what network automation actually looks like in practice, because the reality is far more accessible than the myth.
Network automation, in its most common form, is scripting. It is writing a 50-line Python script that connects to every switch in a site, runs "show interface status," parses the output, and generates a CSV report showing which ports are unused. It is writing an Ansible playbook that reads a YAML file describing the desired VLAN configuration, connects to every access switch, compares the current state to the desired state, and makes only the necessary changes. It is using the REST API on your firewall management platform to pull the current rule set, compare it against a compliance template, and flag deviations. These are not software engineering projects. They are automation tasks that take hours to learn and minutes to execute, and they save days of manual work every month.
Configuration Deployment
The most common automation use case. Instead of SSHing into each device individually, you define the desired configuration in a template, specify the target devices in an inventory file, and run a script or playbook that deploys the configuration to all targets simultaneously. Error handling is built in — if a device is unreachable or the configuration fails validation, the automation reports it without affecting the other devices. A configuration change that would take a team of four engineers an entire maintenance window to deploy manually can be completed in minutes with automation. And critically, it is consistent — every device receives exactly the same configuration, eliminating the human errors that plague manual deployment.
Compliance Checking
Every organization has network standards — NTP servers should point to these IPs, SNMP community strings should use this value, SSH should be version 2, Telnet should be disabled. Checking compliance manually means logging into every device and verifying each setting. At scale, this is impractical and therefore rarely done, which means configuration drift accumulates silently. An automated compliance check connects to every device, extracts the running configuration, parses it against a set of rules, and generates a report showing every deviation. Run it weekly and you catch drift early. Run it after every change window and you catch mistakes before they become security vulnerabilities.
Monitoring and Reporting
SNMP and syslog handle basic monitoring, but there is a layer of operational intelligence that traditional monitoring misses. A Python script can connect to every router, pull the BGP neighbor summary, check for sessions that are in a non-established state, and send a Slack notification to the on-call engineer. Another script can pull interface utilization across all WAN links, calculate trends, and flag links that will exceed capacity within 30 days based on current growth rates. These are not complex programs — they are typically 50-100 lines of Python using libraries like Netmiko for device connectivity and Pandas for data analysis. The value they provide in proactive network management is enormous.
Network State Validation
After any change — planned or unplanned — you need to verify that the network is functioning correctly. Manually, this means logging into key devices and running show commands. Automated, this means running a validation playbook that checks OSPF neighbor counts, BGP session states, interface error counters, and application reachability, then compares the results against a known-good baseline. If any check fails, the automation can alert the team or even trigger a rollback. This concept of "automated pre-checks and post-checks" is becoming standard practice in mature network operations teams, and it eliminates the class of incidents caused by unverified changes.
Abhishek, who works at Unisys as a Cloud Security Engineer starting at 8 LPA, operates in an environment where automation is not optional — cloud infrastructure is managed through code by definition. His combination of networking fundamentals and automation familiarity is exactly what made him valuable to an employer that bridges traditional infrastructure and cloud. The engineers who can work across both worlds — CLI and API, manual and automated — are the ones commanding the strongest offers.
I also want to address a concern I hear from experienced engineers: "Automation will make my job easier, which means my employer will need fewer of me." This is a valid concern but historically unfounded. Every time a technology has made network operations more efficient — from CLI replacing manual DIP switch configuration, to SNMP replacing manual device polling, to centralized management platforms replacing per-device administration — the result has not been fewer network engineers. It has been network engineers managing more complex, more capable, more business-critical networks. Automation is the next step in that progression. The engineers who adopt it do not lose their jobs — they move into roles with greater scope, greater responsibility, and greater compensation. The engineers who resist it find themselves increasingly confined to manual operations roles that are shrinking in both number and relative compensation.
Automation Is a Spectrum, Not a Binary
Python for Network Engineers: What You Actually Need to Know
Python is the language of network automation. Not because it is the best programming language — that is a meaningless debate — but because the networking ecosystem has standardized on it. Cisco's DevNet certifications use Python. Ansible is written in Python. The most popular network automation libraries — Netmiko, NAPALM, Nornir, pyATS — are all Python. When a vendor provides API examples, they are usually in Python. When the community shares automation scripts on GitHub, they are overwhelmingly Python. You can argue about whether Go or Rust is technically superior, but the practical reality is that Python is what the networking world uses, and learning it provides immediate utility.
Now, here is the critically important nuance: the Python you need as a network engineer is different from the Python a software developer needs. You do not need to understand object-oriented programming at an advanced level. You do not need to build web applications with Django or Flask. You do not need to understand decorators, metaclasses, or async programming. What you need is practical scripting — and that subset of Python is learnable in weeks, not months.
Core Python Skills for Network Engineers
Variables, strings, lists, dictionaries — these are your data structures. If-else conditions and for loops — these are your control flow. Functions — these let you organize reusable code. File handling — reading from and writing to CSV, JSON, and YAML files. These fundamentals cover 80% of what you need for network automation scripting. A network engineer who understands these concepts thoroughly can write useful automation scripts. The remaining 20% — error handling, regular expressions for parsing CLI output, working with libraries — you learn as you encounter the need. Do not try to learn all of Python before writing your first network script. Learn enough to start, then learn more as your scripts become more ambitious.
Netmiko: Your First Network Automation Library
Netmiko simplifies SSH connections to network devices. In pure Python, establishing an SSH session, handling authentication, detecting the device prompt, sending commands, and parsing the output is dozens of lines of complex code. Netmiko reduces it to four lines: create a connection dictionary (device type, IP, username, password), establish the connection, send a command, receive the output. It supports Cisco IOS, NX-OS, ASA, Juniper Junos, Arista EOS, Palo Alto PAN-OS, and dozens of other platforms. A network engineer who learns Netmiko can write a useful automation script within their first day of Python practice. That immediate payoff is what makes Python accessible to network engineers — you see results fast.
NAPALM: Multi-Vendor Abstraction
NAPALM (Network Automation and Programmability Abstraction Layer with Multivendor support) takes automation a level higher. Instead of sending vendor-specific CLI commands, NAPALM provides a unified interface for common operations: get_facts(), get_interfaces(), get_bgp_neighbors(), load_merge_candidate(), commit_config(). You write your script once, and it works across Cisco IOS, Juniper Junos, Arista EOS, and other supported platforms. This is particularly valuable in multi-vendor environments where writing separate Netmiko scripts for each vendor would be tedious. NAPALM also introduces the concept of configuration management — load a candidate configuration, compare it to the running configuration, review the diff, and commit or discard. This workflow mirrors what software developers call "infrastructure as code" and brings discipline to network changes.
Working with Data: JSON, YAML, and APIs
Modern network devices expose data through APIs in structured formats — primarily JSON. Understanding JSON (and its close relative YAML) is essential for network automation. When you query a REST API on a Cisco DNA Center, Meraki dashboard, or Palo Alto Panorama, the response comes back as JSON — a structured format that Python can parse natively using dictionaries and lists. Similarly, Ansible playbooks and inventory files use YAML. The ability to read, write, and manipulate these data formats is as important for modern network engineering as understanding CLI output was for the previous generation. The learning curve is gentle — JSON and YAML are human-readable by design — but the capability it unlocks is transformative.
Vedant, now a Senior Network Engineer at Ruckus Networks after CCNP with a ~60% salary jump, works in an environment where enterprise wireless infrastructure management increasingly involves API-driven operations. The engineers who can bridge the gap between traditional networking and programmable infrastructure are the ones who advance fastest. His CCNP provided the deep networking knowledge. Adding automation skills to that foundation is what creates the premium combination that employers are actively seeking.
The Python Learning Path for Network Engineers
Ansible and Infrastructure as Code
If Python scripting is the foundation of network automation, Ansible is the framework that makes it enterprise-ready. Ansible provides structure around automation tasks — playbooks define what to do, inventory files define where to do it, roles organize reusable components, and variables allow the same playbook to be customized for different environments. For network engineers who are not comfortable writing Python from scratch, Ansible offers a gentler entry point because its playbooks are written in YAML — a human-readable data format that looks more like a structured document than a program.
Let me describe a practical Ansible use case. You need to deploy a new SNMP configuration across 200 switches — updating the community string, adding a new SNMP server, and enabling specific traps. Manually, an engineer would SSH into each switch, paste the configuration, verify it took effect, and move to the next switch. At three minutes per switch, that is 10 hours of repetitive work with a high probability of at least a few copy-paste errors. With Ansible, you write a playbook that defines the desired SNMP configuration, point it at your inventory of 200 switches, and run it. Ansible connects to all switches (in parallel, configurable batches), applies the configuration, verifies the changes, and reports the results. The entire operation completes in minutes with zero human error because every switch receives exactly the same configuration. The playbook is also self-documenting — anyone can read the YAML and understand what the automation does, which makes it reviewable, auditable, and maintainable.
The concept of "Infrastructure as Code" — treating your network configuration as versioned, reviewable, testable code rather than ad-hoc CLI sessions — is the philosophical shift that automation enables. When your network configuration exists as Ansible playbooks and YAML variable files stored in a Git repository, you gain capabilities that manual operations cannot provide. Version control: every change is tracked with a timestamp, author, and description. Peer review: changes can be reviewed by another engineer before deployment. Rollback: reverting a bad change means reverting to the previous version in Git and re-running the playbook. Consistency: the configuration in Git is the single source of truth — any drift from it can be detected and corrected automatically.
Why Ansible Works for Network Engineers
Ansible is agentless — it connects to devices via SSH (for network devices) or APIs, without requiring software installation on the managed device. This is critical for networking because you cannot install agents on most routers and switches. Ansible's network modules support Cisco IOS/NX-OS/ASA, Juniper Junos, Arista EOS, Palo Alto PAN-OS, F5, and dozens more. The YAML syntax is deliberately simple — indentation and key-value pairs, no programming constructs needed for basic playbooks. And the community support is massive — thousands of pre-built roles and modules are available that you can adapt rather than writing from scratch.
Ansible vs Python: When to Use Which
Use Ansible for structured, repeatable operations: configuration deployment, compliance enforcement, standard change implementation. The playbook format enforces consistency and is easy for other team members to understand and modify. Use Python scripts for ad-hoc tasks, complex logic, custom parsing, and scenarios where Ansible's module support is insufficient. In practice, most network automation teams use both — Ansible for the routine 80% and Python for the custom 20%. Learning both gives you complete coverage, but if you can only start with one, start with Ansible. Its learning curve is gentler and it delivers enterprise-grade value faster.
Kalyan Kumar, now at NTTDATA, who works at Cisco TAC as a Network Consulting Engineer with CCIE and 28 LPA, increasingly encounters customers who are adopting automation tools and need guidance on integrating them with their Cisco infrastructure. Cisco's own platforms — DNA Center, ACI, Meraki — are API-first, meaning automation is the intended interaction model. Engineers who understand both the underlying networking and the automation layer are the ones who can deliver the most value in these engagements. The traditional "CLI-only" engineer is still needed, but the engineer who can do both is needed more — and compensated accordingly.
Start With One Playbook
What Employers Are Actually Hiring For in 2026
Let me share what I see in the job market based on conversations with hiring managers, analysis of job postings, and feedback from our placement partners. The demand pattern has shifted meaningfully over the past three years, and engineers who understand this shift can position themselves ahead of the curve. The short version: pure routing-and-switching roles still exist and still pay well, but the fastest-growing and highest-paying network engineering roles combine traditional networking with at least one additional skill dimension — automation, cloud, or security.
The "Network Automation Engineer" Title
This is an emerging job title that barely existed five years ago and now appears in hundreds of postings. The typical requirement: CCNP or equivalent networking knowledge, Python scripting, Ansible experience, understanding of REST APIs and data formats (JSON/YAML), and familiarity with version control (Git). Notice what is first in the list — networking knowledge. These roles are not for developers who happen to know networking. They are for network engineers who have added automation skills. The compensation typically runs 15-30% above equivalent pure networking roles because the combination is scarce.
Traditional Roles with Automation Requirements
Even roles titled "Network Engineer" or "Senior Network Engineer" increasingly list automation as a desired or preferred skill. The phrasing varies: "Python scripting preferred," "experience with configuration management tools," "familiarity with programmability and APIs." These are not hard requirements yet — you can still get hired without them — but they are tiebreakers. When a hiring manager has two candidates with similar CCNP-level knowledge and one also has automation skills, the choice is obvious. In an increasingly competitive job market, tiebreakers matter.
DevNet and Programmability Certifications
Cisco's DevNet certification track — DevNet Associate and DevNet Professional — formally recognizes network automation skills. While DevNet certifications alone are not as well-established as CCNA/CCNP in the hiring market, the combination of a traditional networking certification plus DevNet is powerful. It signals to employers that you have both the networking depth and the automation breadth. Other vendors have similar programs: Juniper's automation certifications, Arista's automation track. The industry is formally recognizing that automation is a core networking competency, not an optional add-on.
Cloud Networking Roles
AWS, Azure, and GCP networking roles inherently require automation skills because cloud infrastructure is managed through APIs and infrastructure-as-code tools (Terraform, CloudFormation). A network engineer who understands VPCs, Transit Gateways, VPN connections, and load balancers — and can deploy them through code — is exactly what cloud-first organizations need. Abhishek at Unisys, starting at 8 LPA as a Cloud Security Engineer, operates in this space where the line between networking, security, and automation is blurred — and that intersection is where the strongest career trajectories exist.
The message from the market is consistent and clear: networking knowledge is the foundation. Automation skills are the multiplier. Engineers who have both are in the strongest position — not because automation replaces networking expertise, but because it amplifies it. A CCNP engineer who can write a Python script to automate a task is more valuable than a CCNP engineer who cannot. A CCIE engineer who can build an Ansible framework for their organization's network operations is more valuable than a CCIE engineer who manages everything through CLI. The networking knowledge remains essential — you cannot automate what you do not understand. But the ability to automate what you do understand is what separates the most sought-after engineers from the rest.
One more data point worth sharing. When I review job postings for network engineering roles in India's major tech hubs — Bangalore, Hyderabad, Pune, Mumbai — the postings that mention Python, Ansible, or automation consistently list higher salary ranges than equivalent postings without those requirements. The premium is not marginal. For CCNP-level roles, automation-inclusive postings typically offer 15-30% more than equivalent non-automation postings. For senior roles, the premium can be even larger because automation skills at the senior level imply the ability to build and lead automation initiatives, not just execute individual scripts. This salary data reinforces what the hiring managers tell me directly: automation skills are a compensation multiplier, not just a hiring tiebreaker.
The Compound Effect
The Practical Automation Learning Path
Let me be prescriptive about how to learn network automation as a working network engineer. I have watched hundreds of engineers attempt this transition, and the ones who succeed follow a pattern: they build networking knowledge first (or in parallel), they start with practical automation tasks rather than theoretical programming courses, and they learn by solving real problems from their own environment. The ones who fail typically try to learn Python from a generic programming course aimed at software developers, find it disconnected from their work, get frustrated, and quit. The learning path matters as much as the learning itself.
Phase 1: Build the Networking Foundation (Ongoing)
Automation skills without networking knowledge are useless for network automation. You cannot write a meaningful script to troubleshoot OSPF if you do not understand OSPF. You cannot build an Ansible playbook for BGP policy deployment if you do not understand BGP policies. The networking foundation — CCNA at minimum, CCNP ideally — must be solid before or alongside your automation learning. This is non-negotiable. The engineers who try to skip the networking fundamentals and go straight to automation end up writing scripts that deploy incorrect configurations at scale, which is worse than deploying them manually.
Phase 2: Linux and Git Basics (2-3 Weeks)
Before Python, get comfortable with Linux command line basics and Git version control. Network automation tools run on Linux. Your scripts will be stored in Git. These are prerequisites that many network engineers skip, only to struggle later when they cannot navigate a Linux file system or manage their code versions. You do not need to become a Linux administrator — you need to be comfortable running commands, navigating directories, editing files, and understanding permissions. For Git, you need to understand clone, add, commit, push, pull, and branch. These fundamentals take two to three weeks of daily practice and pay dividends throughout your automation journey.
Phase 3: Python Scripting for Networks (4-6 Weeks)
Learn Python through networking-specific exercises. Do not work through a generic "learn Python" tutorial building web scrapers and games. Instead, write a script that pings a list of devices and reports which are reachable. Write a script that SSHs into a router using Netmiko and pulls the routing table. Write a script that reads a CSV of switch IP addresses and generates a report of interface utilization. Every exercise should involve network devices and network data. This approach keeps the learning relevant and motivating, and it builds a portfolio of useful scripts that you can apply at work immediately.
Phase 4: Ansible for Network Operations (4-6 Weeks)
With Python basics established, learn Ansible with a focus on its network modules. Build playbooks that deploy configurations, validate network state, and generate reports. Practice with Ansible's ios_config, nxos_config, and junos_config modules. Learn to use Jinja2 templates for configuration generation — this is where Ansible becomes particularly powerful, because you can define a configuration template once and render it with different variables for different sites, roles, or environments. By the end of this phase, you should be able to build a playbook that deploys a standard configuration change across a multi-device, multi-site environment with error handling and validation.
Phase 5: APIs and Platform Integration (Ongoing)
Learn to interact with REST APIs on platforms like Cisco DNA Center, Meraki, Palo Alto Panorama, or your organization's specific tools. This is where automation transcends device-level scripting and becomes infrastructure orchestration. You learn to use APIs to provision new sites, manage security policies across a fleet of firewalls, integrate network data with monitoring and ticketing systems, and build custom dashboards. This phase is ongoing because every platform has its own API, and new platforms emerge regularly. The foundational skill — understanding REST, authentication, JSON payloads, and response handling — transfers across all platforms.
The total investment from Phase 2 through Phase 4 is approximately 10-14 weeks of part-time study alongside your regular work. That is less than one semester. For a skill set that increases your marketability by 15-30%, shortlists you for roles that pure networking candidates cannot access, and positions you for the future of the industry, the return on investment is extraordinary. And unlike a certification that you study for and then forget, automation skills improve with daily use — every script you write and every playbook you build makes you more proficient.
The Most Common Mistake
Watch: Automation-Ready Career Stories & Training
Watch real students who built careers combining networking expertise with modern skills, and explore training content covering the technologies discussed in this article:
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Vedant From Chhattisgarh Got Placed at RUCKUS Networks 10+LPA
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CCNA-CCNP Mock Interview 2026: Real Network Engineer Q&A
Frequently Asked Questions
What is network automation?
Using code and tools (Python, Ansible, REST APIs) to automate repetitive network tasks: configuration deployment, compliance checking, monitoring, and reporting. It doesn't replace network engineers — it makes them faster and more reliable.
Python for network engineers?
Python is the most useful programming language for network automation. Libraries like Netmiko, NAPALM, and Nornir let you interact with network devices programmatically. You don't need to be a developer — basic Python scripting is sufficient.
Network automation engineer salary?
Network automation skills command a significant premium. Engineers who combine CCNP-level networking knowledge with automation skills are among the most sought-after in the industry. The combination is rare, which drives compensation.
Do I need coding for network automation?
Basic Python scripting — not full software development. You need to write scripts, use APIs, and work with data structures (JSON, YAML). Most network automation code is 50-200 lines, not complex applications.
Network Automation Readiness Framework
Solidify Your Networking Foundation
Automation amplifies networking knowledge — it does not replace it. Ensure your CCNA/CCNP fundamentals are strong before or alongside learning automation tools.
Learn Linux and Git Basics
Get comfortable with the Linux command line and Git version control. These are prerequisites for all network automation tooling and will be part of your daily workflow.
Master Python Scripting for Networks
Focus on practical network automation scripting: Netmiko for device connectivity, data parsing, file handling with JSON/YAML/CSV. Skip the generic programming tutorials.
Build Ansible Playbooks for Operations
Learn to write playbooks for configuration deployment, compliance checking, and state validation. Practice with network-specific modules and Jinja2 templates.
Integrate with APIs and Platforms
Learn REST API interaction with your organization's tools: DNA Center, Meraki, Panorama, cloud platforms. This is where device-level automation becomes infrastructure orchestration.
Related Training Programs
Build the networking foundation and automation skills that the industry demands. These programs integrate hands-on automation practice with deep protocol knowledge:
CCIE Automation Course in Bangalore
Expert-level network automation with Python, Ansible, and API-driven infrastructure management. Build production-grade automation frameworks for enterprise networks.
CCNA Automation Course in Bangalore
Networking fundamentals combined with Python scripting and basic automation skills. The ideal starting point for engineers who want both skill sets from day one.
CCIE Enterprise Course in Bangalore
Deep networking expertise that forms the foundation automation skills amplify. SD-WAN, advanced routing, and network design with programmability integration.
The network automation skill gap is real, and it is your opportunity. Not because automation is replacing networking — it is not. But because the combination of deep networking knowledge and practical automation skills is rare, valuable, and increasingly demanded by every organization that operates infrastructure at scale. The engineers who close this gap now position themselves for the strongest career trajectories in the industry.
Consider the career paths we have seen. Vedant at Ruckus Networks with a ~60% jump, Kalyan Kumar, now at NTTDATA at Cisco TAC at 28 LPA, Abhishek at Unisys starting at 8 LPA — each of them built on strong networking foundations and added skills that the market values. The automation skill gap is the same kind of opportunity: a clear demand signal from the industry that most engineers have not yet responded to.
If you want to build both networking depth and automation capability in a structured environment — with real lab equipment, practical exercises, and mentorship from engineers who understand both worlds — explore the CCIE Automation, CCNA Automation, or CCIE Enterprise programs. The skill gap is an opportunity — but only for those who act on it.
— Vikas Swami
