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Cisco retired the DevNet Associate name from its live certification framework on February 3, 2026 and moved the credential into the CCNA family as CCNA Automation. The current exam is still number 200-901, now presented as CCNAAUTO and focused on automating networks using Cisco platforms.
Cisco has been explicit that the associate-level content remains closely connected to the DevNet foundation. The certification validates software development and design, APIs, application deployment and security, scripting, workflow automation, infrastructure as code, and automation on Cisco platforms.
A useful preparation mindset is to treat every automation task as a small engineering system. There is an input, an intended state, an interface, an action, a result, and a validation step. If any of those pieces is implicit, the workflow becomes hard to trust. Associate-level candidates do not need advanced software architecture, but they should be able to read code, reason about data, make an API call, handle a failure, and verify that the infrastructure now matches the intended outcome.
CCNA Automation keeps the associate-level bridge between software and infrastructure but places it in a broader automation career track. That matters because candidates no longer need to treat programmability as a niche skill attached to one product family. The objective is to understand how software techniques make network operations safer, more repeatable, and easier to integrate with the rest of an organization's delivery systems.
Automation engineers need to understand both sides of the interface. They must know what the network is supposed to do and enough software development to express that intent safely through code, APIs, and repeatable workflows.
Older DevNet Associate certification material remains useful for understanding that original bridge between developers and infrastructure engineers, but the current certification identity is CCNA Automation.
Intent needs to be precise enough for software to act on it. 'Configure the branch' is vague; 'ensure these interfaces have these addresses, these VLANs exist, these routes are present, and these policies are applied' can be represented as data and validated. This is why automation often begins with models and structured inputs rather than with a long script. The clearer the desired state, the easier it becomes to test whether a workflow succeeded.
Network knowledge remains essential because software can only automate assumptions it has been given. A script that pushes an incorrect route policy to fifty devices is more efficient than a manual mistake, but it is not better engineering. Candidates should practice explaining the protocol or service behavior first, then writing the smallest automation needed to observe or modify it. This keeps the code connected to operational intent.
Modern Cisco platforms expose structured interfaces that allow software to read state and make controlled changes. Candidates need to understand REST concepts, authentication, request methods, status codes, payloads, and how structured data such as JSON is used in an automation workflow.
The goal is not simply to memorize HTTP verbs. A useful lab retrieves device or controller state, validates the response, makes a small change, and then verifies that the resulting state matches the intended outcome.
REST interactions should be understood as conversations with contracts. The endpoint, method, authentication mechanism, headers, request body, and expected response schema define what the client and server agree to exchange. Status codes provide clues but are not sufficient by themselves; a successful response can still contain incomplete data or a business-level error. Good automation checks the payload and confirms that the returned state has the fields and values the workflow expects.
Authentication deserves special attention. Hard-coding passwords or tokens into scripts makes quick labs easy but creates poor habits. Candidates should understand environment variables, secure secret storage, scoped tokens, expiration, and least privilege at a conceptual level. They should also be comfortable handling rate limits, timeouts, pagination, and transient errors. These are the details that separate a one-time API demo from a workflow that can run reliably in operations.
Python remains one of the most practical languages for infrastructure automation because it is readable, has mature libraries, and integrates well with APIs and structured data. Candidates should be comfortable with variables, data structures, loops, functions, error handling, files, and basic testing.
Python automation shows why scripting becomes valuable when repetitive technical work needs to be standardized rather than repeated manually.
The most relevant Python practice is data transformation. Network APIs frequently return lists and dictionaries; configuration sources may be JSON, YAML, CSV, or plain text; and the script often needs to filter, normalize, compare, or aggregate that information. Candidates should be able to iterate over a collection of devices, select the records that meet a condition, construct a request, and capture failures without stopping the entire run.
Functions and modules help separate concerns. One function can authenticate, another retrieve state, another calculate a desired change, and another validate the result. This makes scripts easier to test and reduces the temptation to build one long block that mixes data collection, business logic, and device changes. Even at associate level, small design choices such as meaningful variable names and explicit error messages improve operational safety because someone else may need to understand the script during an incident.
An automation script can become a privileged operator of the network. That means credentials, tokens, secrets, input validation, permissions, and error handling have to be treated seriously. Fast automation with poor security simply scales the mistake.
The same principle appears in DevSecOps, where security is integrated into delivery workflows instead of being checked only after code or infrastructure has already changed.
Automation expands the attack surface because it often has credentials and network reach that ordinary user applications do not. Input validation prevents malformed or malicious data from becoming configuration. Least-privilege permissions limit what a compromised token can change. Logging creates an audit trail, while secret rotation reduces the useful lifetime of stolen credentials. These are not separate security topics; they are requirements for trustworthy automation.
Dependency risk matters too. Scripts and automation platforms rely on libraries, containers, repositories, and pipeline systems. Candidates should understand why version pinning, code review, signed or trusted sources, and basic software-supply-chain hygiene matter even when the final target is a network device. The operational question is always the same: what would an attacker gain if they controlled this workflow, and what controls would detect or limit that misuse?
Infrastructure as code allows teams to represent intended state in files that can be reviewed, versioned, tested, and reapplied. Different tools take different approaches, so candidates benefit from understanding the distinction between configuration-oriented and state-oriented automation. Ansible and Terraform for infrastructure automation provide useful context for that difference.
At associate level, the important idea is not tool loyalty. It is recognizing why repeatability, version control, validation, and rollback make automation safer than undocumented manual change.
Version control gives infrastructure changes a history. A pull request can show exactly what will change, reviewers can discuss intent before deployment, and a prior version can help explain when drift was introduced. This does not make rollback automatic—network state may have dependencies and side effects—but it creates a far better record than an undocumented CLI session. Candidates should understand commits, branches, diffs, and reviews as operational controls, not just developer rituals.
Idempotence is another core idea. A well-designed workflow should be able to enforce the same intended state repeatedly without creating additional changes each time. That makes scheduled compliance checks and recovery more predictable. If a tool reports drift, the engineer should investigate why the live environment differs from the declared state before blindly overwriting it. Infrastructure as code is safest when it improves visibility and governance as well as speed.
The former DevNet Professional credential became CCNP Automation in 2026, but Cisco did more than rename it. The current professional core, 350-901 AUTOCOR, is a major update centered on network automation systems, infrastructure as code, operations, and AI-assisted automation.
DevNet Professional is therefore best read as a transition point into the modern CCNP Automation structure rather than as the next certification name candidates should search for today.
AUTOCOR expects a broader systems view than the associate exam. Professional automation engineers design pipelines, data models, testing strategies, observability, and reusable services that may affect multiple network domains. The associate foundation is therefore valuable when it teaches disciplined interfaces and validation rather than only syntax. Those habits are what scale into larger automation systems.
Candidates considering the professional path should look for opportunities to automate real operational tasks with measurable outcomes: inventory collection, compliance checks, configuration validation, change preparation, or post-change verification. A project that saves five minutes but has clear input validation, logging, testing, and rollback thinking can demonstrate more mature engineering than a much larger script that nobody can safely rerun.
No formal prerequisite is required, but candidates will learn faster if they already understand basic networking and are comfortable with at least one scripting language. Engineers coming from the CCNA side bring networking context; developers bring coding context. The certification exists to close the gap between them.
Automation now sits alongside Enterprise, Security, Data Center, Collaboration, Wireless, and Service Provider within Cisco certifications.
The certification is approachable without being trivial. Cisco does not require a previous certification, but candidates benefit from enough networking knowledge to recognize the state they are reading and changing. Someone coming from software may need more routing, switching, and platform context; someone coming from networking may need more practice with Python, APIs, Git, and data structures. The exam sits deliberately between those backgrounds.
A balanced study plan alternates software and infrastructure tasks. Read an API response, then verify the same state on the device or controller. Make a small configuration change through code, then inspect the resulting network behavior. Store the script in version control, add error handling, and rerun it against a slightly different input. That cycle turns isolated objectives into one repeatable automation workflow.
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