Cisco DevNet in 2026: How the Track Became Automation

The Cisco DevNet certification track is now a legacy name. On February 3, 2026, Cisco rebranded DevNet Associate, Professional, and Expert into CCNA Automation, CCNP Automation, and CCIE Automation. Active holders transitioned into the new naming, and the current certification pages now present automation as a full Cisco career family.

That means a 2025 article about “the DevNet track” needs to be read historically. The skills remain important, but the career map, professional exam structure, and branding have moved forward.

The 2026 Automation track is easier to explain to employers and more closely aligned with modern infrastructure work: APIs, software development, infrastructure as code, CI/CD, observability, security, operations, and AI-assisted automation.

DevNet’s original contribution was making software a networking skill

Before DevNet, many network engineers treated programming as optional or adjacent. DevNet helped normalize Python, REST APIs, JSON, Git, application workflows, and controller-based automation as legitimate infrastructure skills.

That cultural shift was arguably more important than any individual exam. It encouraged network teams to adopt software-engineering practices and gave developers a structured route into Cisco platforms.

The modern Automation certifications inherit that mission. The name changed because the work became mainstream enough to sit beside other Cisco professional domains.

CCNA Automation is the new associate identity

CCNA Automation uses the 200-901 CCNAAUTO exam. It validates software development and design, API use, application deployment and security, infrastructure automation, and platform-related skills.

This is the natural replacement for someone who would previously have pursued DevNet Associate. The certification is valid for three years and sits inside the wider Cisco recertification framework.

Candidates should think of it as an infrastructure-software credential. It is not designed to replace a computer science degree or a networking certification; it proves that you can work where software and infrastructure meet.

CCNP Automation was redesigned rather than merely renamed

The professional level received a deeper change. Cisco rebuilt CCNP Automation around a new core-and-concentration model intended to reflect network automation engineering jobs more directly.

The 350-901 AUTOCOR exam covers automation-system development and design, infrastructure as code, operations, security, and AI in automation. Concentrations such as ENAUTO and DCNAUTO add enterprise or data-center depth.

This is more coherent than treating professional automation as a collection of unrelated product scripts. The emphasis is now on building and maintaining automation as an operational system.

CCIE Automation gives programmability an expert destination

CCIE Automation uses AUTOCOR as the qualifying core and adds a practical exam that tests expert-level automation and programmability. Cisco has announced a v1.2 practical update for 2027 with deeper AI-driven operations, modern DevOps, and cloud-native workflows.

That trajectory matters because it shows where the discipline is going. Advanced network automation increasingly looks like platform engineering: source of truth, APIs, software services, pipelines, security, telemetry, AI integrations, and governance.

The expert role is not defined by the number of devices automated. It is defined by whether the automation system remains safe, observable, maintainable, and useful as complexity increases.

The automation path is multi-domain by design

Cisco automation skills apply across enterprise networking, security, collaboration, computing, and data center systems. That breadth is one reason Cisco stopped treating DevNet as a developer niche.

An engineer may begin with general API and software skills, then specialize in enterprise controllers, data-center fabrics, security platforms, collaboration APIs, or orchestration. The common layer is software-driven infrastructure operations.

The automation and AI infrastructure path helps distinguish automation-system engineering from the infrastructure required to run AI workloads.

AI is becoming part of automation work

Automation certifications now include AI-related topics because engineers are beginning to use language models, agents, and predictive systems inside operations. That creates new opportunities and new failure modes.

An AI assistant can help interpret telemetry, generate code, or propose remediation, but automation teams still need validation, access control, auditability, and human oversight. The more powerful the tool, the more important guardrails become.

Candidates should learn AI as an augmentation layer on top of strong software and infrastructure fundamentals, not as a shortcut around them.

Career value comes from the hybrid skill set

Automation professionals are valuable because they can communicate with both infrastructure and software teams. They understand network behavior well enough to automate safely and software practices well enough to build maintainable systems.

This hybrid profile supports roles such as network automation engineer, NetDevOps engineer, infrastructure platform engineer, automation architect, and operations engineer with strong programmability responsibilities.

The certification becomes stronger career evidence when paired with repositories, pipeline examples, controller integrations, tests, and documentation that show you can apply the skills.

How to migrate a 2025 DevNet study plan

First, keep the durable material: Python, APIs, data formats, Git, testing, authentication, application security, controller integration, and automation logic. Then compare the course against the current CCNA or CCNP Automation blueprint.

Replace obsolete exam names and product examples. Add current infrastructure-as-code, operations, security, and AI-in-automation topics where the new blueprint expects them. If you are at professional level, make sure your plan reflects AUTOCOR plus a current concentration.

The goal is not to start over. It is to preserve useful learning while aligning the certification objective with the current program.

The modern roadmap is clearer than the old DevNet label

The current Cisco certification roadmap places Automation beside other major career domains. That clarity helps candidates explain the credential to employers and makes progression from associate to expert easier to understand.

It also gives traditional network engineers permission to specialize in software-driven operations without treating that move as leaving networking. Automation has become part of the core infrastructure profession.

For candidates entering the field now, there is little reason to plan around the DevNet name. Learn the history, use older resources carefully, but build your career around the current Automation track.

The transition also affects resumes and professional profiles. If you earned DevNet Associate before the rename, you do not need to erase that history. You can list the original credential with the current CCNA Automation recognition where appropriate, making the transition clear to employers who may know either name. The same principle applies at professional and expert levels.

Teams with internal training built around DevNet should update learning paths rather than discard them. Preserve labs that teach software fundamentals, APIs, Git, and testing, then map them to current CCNAAUTO, AUTOCOR, ENAUTO, or DCNAUTO objectives. This reduces wasted training investment while keeping the program aligned with Cisco’s current certification language.

Automation career development should also include adjacent systems knowledge. An engineer who can call an API but does not understand routing, security, cloud, or application behavior can automate the wrong outcome very efficiently. Conversely, a strong infrastructure engineer with no software discipline may create brittle scripts. The value of the track comes from combining both sides.

Over time, build toward platform ownership. Start with scripts, then reusable modules, then pipelines and services with tests, observability, access controls, and documented interfaces. That progression mirrors the move from associate to professional and expert thinking more accurately than simply counting exams.

One reason the new naming matters is career portability inside an organization. A manager who already understands CCNA and CCNP can place “CCNP Automation” more easily in a skills framework than “DevNet Professional.” That does not make the skills better overnight, but clearer signaling can improve hiring, promotion, and training alignment.

The concentration model also gives professional candidates a sharper specialization decision. ENAUTO fits enterprise automation work, while DCNAUTO fits data-center automation. That is more useful than choosing a concentration simply because it is familiar; the exam should reflect the systems you can access and the role you want to grow into.

Organizations adopting AI-assisted operations should use the Automation path to reinforce governance rather than bypass it. Generated code and agentic actions still need tests, permissions, logging, and review. Engineers who understand both AI tools and traditional software-delivery controls will be better positioned than those who treat AI as an excuse to skip engineering discipline.

Finally, the end of the DevNet name is a reminder that certifications are temporary labels around evolving skills. APIs, source control, testing, infrastructure as code, observability, and secure automation will outlast any one branding cycle. Build those foundations deeply enough that the next rename does not require rebuilding your career identity.

A practical 2026 learning sequence is to master Python and API fundamentals, earn or study toward CCNA Automation, contribute to a version-controlled infrastructure project, then decide whether professional depth belongs in enterprise or data-center automation. The sequence creates evidence before the more demanding core exam.

Candidates coming from software rather than networking should make the opposite adjustment: learn addressing, routing, security boundaries, device state, and operational change before automating at scale. Software skill without infrastructure context can produce elegant code that changes the wrong thing very efficiently.

The best proof that the transition worked is operational independence. By the time you move toward CCNP Automation, you should be able to take an unfamiliar API, model the required state, build a tested workflow, secure its credentials, observe its execution, and explain its rollback path to the team that will support it.