Views from an Insider on the CCNP Automation Observe: DCNAUTO 2.0 Version

We’ve lastly arrived on the third and ultimate installment of this riveting weblog sequence.  Whereas some could also be unhappy on the disappearance of additional sleep they acquired from studying this (my prose is normally an excellent treatment for insomnia), on this weblog, we’ll be masking the shiny new DCNAUTO specialization and applied sciences close to and expensive to my coronary heart.  Similar to the weblog on AUTOCOR and ENAUTO 2.0, I hope that this may assist make clear the rationale and intent for the massive remodeling of the examination matters to help and help you in your research.

A fork within the highway

The unique DCAUTO examination had the “shortest” listing of examination matters (based mostly solely on my unscientific evaluation of the quantity of textual content on a PDF), however that doesn’t imply that the examination was easy.  It coated a broad set of applied sciences with disparate terminology and spanned a number of (usually) separate groups (server/compute groups normally are separate from the datacenter networking groups).

However  even should you have been in a company that had ACI and UCS, more often than not you’re employed with just one expertise or the opposite, not each.  This complication was solely exacerbated by the truth that the Unified Computing System (UCS) Supervisor Platform Emulator (UCSM-PE) couldn’t be linked to Cisco Intersight; solely sure builds which have been accessible solely to particular groups like Cisco DevNet for his or her Sandbox might accomplish that.

This lead to an enormous inside resolution: How do we offer an automation certification that focuses on the datacenter, covers the community expertise accessible at this time, contains platforms and gadgets, and covers the evolving realities within the datacenter (like Kubernetes and containers)?  We had some powerful decisions to make, however the result’s the DCNAUTO 2.0 (be aware the “N” for networking)

Give it to me straight, what has been faraway from DCAUTO?

Based mostly on this picture, you’ll be able to see that a big chunk of the unique blueprint has been eliminated/modified not directly(the highlighted sections).  In some circumstances, the matters have been eliminated for a similar as they have been in ENCOR 2.0; matters like Git, fundamental APIs, or Python digital environments have been eliminated as a result of both (a) they’re assumed data (b) coated within the core examination or (c) might be changed with different applied sciences which will work higher with bigger workflows (e.g. growth within a container with mapped volumes can exchange digital environments inside Python).

Inside area 2.0, we eliminated most of the particular API and SDK duties as they pertain to ACI.  Whereas these two strategies of automation are nonetheless legitimate, a lot of the event and integration effort inside the datacenter has been targeted on Infrastructure as Code (IaC) instruments.  With the ability to automate platforms and applied sciences with instruments which have multi-platform help is vital as a result of these datacenters are more and more heterogeneous.  So understanding how one can use these instruments inside the community infrastructure turns into a vital talent.

Area 3.0 acquired a lightweight contact of adjustments, principally targeted on refining and trimming down superfluous device-centric automation and app-hosting strategies.  Whereas these capabilities are nonetheless built-in to our huge datacenter switching portfolio, we tried to deal with the most typical use-cases and applied sciences.  Keep in mind, the main target of the brand new blueprints is to create practicality and applicability into exams, so we needed to trim away among the esoteric or much less used options and performance.

And also you dropped compute?!

Sure.

I assume you’ll be searching for a cause on this one, too. Consider me, it wasn’t a simple resolution.  We went backwards and forwards on this and there have been sturdy arguments to each side, however finally, as a rule, the compute and server groups are utterly completely different than community infrastructure groups, and the practitioners inside these groups had vastly completely different skillsets, making the crossover to be that rather more tough.

Fairly than weakening the depth of the check (and the sensible purposes gained from it) to help added breadth, we determined to drop the compute automation utterly.  I can already hear the sighs of reduction from community automation of us, however I do know there are just a few of us that may miss the inclusion of Intersight and the UCSM APIs (my former compute Developer Advocate counterpart included).

Sufficient about what was dropped, what do we have to research?

Throughout the datacenter, there are just a few key applied sciences that we selected to deal with.  As with the AUTOCOR and ENAUTO 2.0, reference the highest paragraph of the examination matters listing to get an understanding of the in-scope platforms.  These platforms shouldn’t come as a shock, however it’s useful to set context round your research.

Infrastructure as Code (IaC)

The datacenter have to be:

• Agile
• Multivendor
• Even multicloud

This implies click-ops or particular person automations for various platforms gained’t all the time be accepted.  The unifying issue to all of that is one thing like Ansible or Terraform, whereby the syntax throughout platforms and clouds is similar and the one distinction is the modules/collections or suppliers in use.

The DCNAUTO examination displays this, as 25% of the examination falls inside the IaC area. This  requires you to be acquainted with the instruments and management options in addition to the platforms coated by the blueprint.

On-box automation and programmability

With the dimensions and scale of contemporary datacenter networks, platforms are sometimes used to handle the material.  Nevertheless, there could also be both particular community automation options or day 0 provisioning that dictate a “box-by-box” course of.  Due to this, we’ve included particular examination matters to validate a learner’s data round these “community factor” automation duties in Area 3.

When it comes to particular community factor programmability, we’ve included:

• NETCONF help, as YANG fashions equivalent to OpenConfig are utilized in massive, probably multi-vendor or web-scale datacenters, because it normalizes configuration throughout quite a lot of gadgets
• Familiarity with NETCONF and ncclient, which can be utilized to ship XML-structured payloads to a tool by way of code written in Python
• Understanding the day-0 provisioning of a tool exterior of the usage of a controller, and the on-box programmability strategies accessible inside the Nexus platform
• Data round NXAPI and the stream of making bespoke templates (which might then be utilized as coverage) inside Nexus Dashboard rounds out the area

Operations (together with Linux Networking!)

One of many bigger shifts (throughout all new CCNP-Automation exams) has been the deal with operational points of an automation answer.  In any case, what good is deploying a change with out understanding the impression of that change on the community?  That is no completely different inside the datacenter and a few would argue that it’s extra vital; datacenters are finely tuned devices to maneuver knowledge in a short time from place to position. If it doesn’t work, it’s usually costing massive sums of cash.

On this examination, we’ve not a lot “eliminated” matters, however shifted them in complexity.  The unique DCAUTO examination had components that touched on model-driven telemetry and understanding subscriptions to knowledge., together with next-generation protocols like gNMI and gRPC.  We additionally embody digital twins and pyATS validation, as we’ve in different exams.  To not be forgotten, we additionally cowl the power to retrieve well being data by way of Python towards gadgets as nicely.

Lastly, we additionally added the requirement to troubleshoot packet flows from Linux-based hosts working containers.  Everyone knows that containers are the brand new VMs, however the hosts working these containers don’t use the identical instruments and terminology as a Kind-1 Hypervisor; we should perceive how Linux networking works and the way it’s configured.

This contains how interfaces, subinterfaces, and bonded interfaces are created, in addition to how commonplace bridges are outlined and the connection between digital Ethernet (veth) interfaces on the host degree and interfaces outlined inside the container runtime.  These abilities are not elective and we felt it vital to know them nicely sufficient to repair them after they break.

We needed to toss in some AI, too

Similar to with the remainder of the skilled automation specializations, some AI wanted to be included inside the examination matters listing; it’s being talked about in every single place and our certifications needs to be no completely different.

• Understanding the safety implications of utilizing AI inside the datacenter is vital to guard the huge quantities and worth of that knowledge. Right here there may very well be unintended penalties round knowledge publicity and as a vector for exfiltration.
• As agentic AI turns into mainstream, understanding how these brokers join to varied platforms, gadgets, and controllers is a baseband activity; one thing that everybody ought to perceive.
• With the prevalence of automation and orchestration inside the datacenter, describing and understanding how generative AI can be utilized to speed up prototyping and iteration over community automation options will not be an elective talent. It ought to validated for any automation skilled.

Bringing all of it collectively

By way of this weblog, and the earlier ones on the AUTOCOR and ENAUTO 2.0, I hope you’ve gained a little bit bit extra perception into the certification and the particular exams (each core and focus).  This isn’t simply associated to the exams and matters themselves, but additionally the mindset shift and completely different strategy in creating the examination matters listing, transferring from software program engineers which are studying “community” to community engineers which are studying “automation.”  It sounds delicate, however the final result might be fairly completely different.  By way of this distinction, we hope that you simply discover that the brand new exams align to your automation work in a way more impactful manner.

As all the time, comfortable studying!  If in case you have any questions, please contact me on X (@qsnyder) or by means of the Cisco Studying Community message boards.

Efficient February 3, 2026, the 300-635 DCNAUTO examination might be up to date to v2.0 and renamed, “Automating Cisco Knowledge Heart Networking Options v2.0.”

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