We’ve lastly arrived on the third and last 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 protecting the shiny new DCNAUTO specialization and applied sciences close to and pricey to my coronary heart. Identical to the weblog on AUTOCOR and ENAUTO 2.0, I hope that it will assist make clear the rationale and intent for the massive transforming of the examination matters to help and assist you in your research.
A fork within the highway
The unique DCAUTO examination had the “shortest” checklist of examination matters (primarily based 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 lined a broad set of applied sciences with disparate terminology and spanned a number of (sometimes) separate groups (server/compute groups normally are separate from the datacenter networking groups).
However even if you happen to have been in a company that had ACI and UCS, more often than not you’re employed with just one know-how 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 obtainable solely to particular groups like Cisco DevNet for his or her Sandbox may achieve this.
This lead to an enormous inner choice: How do we offer an automation certification that focuses on the datacenter, covers the community know-how obtainable at present, contains platforms and units, 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 (word the “N” for networking)
Give it to me straight, what has been faraway from DCAUTO?
Primarily based on this picture, you’ll be able to see that a big chunk of the unique blueprint has been eliminated/modified in a roundabout way(the highlighted sections). In some instances, the matters have been eliminated for a similar as they have been in ENCOR 2.0; matters like Git, primary APIs, or Python digital environments have been eliminated as a result of both (a) they’re assumed information (b) lined within the core examination or (c) may be changed with different applied sciences that will work higher with bigger workflows (e.g. growth inside a container with mapped volumes can change digital environments inside Python).
Inside area 2.0, we eliminated lots 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 centered on Infrastructure as Code (IaC) instruments. Having the ability to automate platforms and applied sciences with instruments which have multi-platform assist is essential as a result of these datacenters are more and more heterogeneous. So understanding tips on how to use these instruments inside the community infrastructure turns into a essential talent.
Area 3.0 acquired a light-weight contact of adjustments, largely centered 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 give attention to the most typical use-cases and applied sciences. Bear in mind, the main focus 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 suppose you’ll be in search of a motive on this one, too. Imagine me, it wasn’t a straightforward choice. We went forwards and backwards on this and there have been sturdy arguments to each side, however in the end, most of the time, the compute and server groups are fully totally different than community infrastructure groups, and the practitioners inside these groups had vastly totally different skillsets, making the crossover to be that rather more tough.
Quite than weakening the depth of the check (and the sensible purposes gained from it) to assist added breadth, we determined to drop the compute automation fully. I can already hear the sighs of aid from community automation of us, however I do know there are just a few of us that can 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 give attention to. As with the AUTOCOR and ENAUTO 2.0, reference the highest paragraph of the examination matters checklist 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 at all times be accepted. The unifying issue to all of that is one thing like Ansible or Terraform, whereby the syntax throughout platforms and clouds is identical 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 aware of the instruments and management options in addition to the platforms lined 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. Nonetheless, 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 information round these “community component” automation duties in Area 3.
When it comes to particular community component programmability, we’ve included:
- NETCONF assist, as YANG fashions reminiscent of OpenConfig are utilized in massive, doubtlessly multi-vendor or web-scale datacenters, because it normalizes configuration throughout a wide range of units
- 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 obtainable inside the Nexus platform
- Information round NXAPI and the circulate of making bespoke templates (which may 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 give attention to operational facets of an automation resolution. In any case, what good is deploying a change with out understanding the affect of that change on the community? That is no totally different inside the datacenter and a few would argue that it’s extra essential; datacenters are finely tuned devices to maneuver information 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 information., together with next-generation protocols like gNMI and gRPC. We additionally embody digital twins and pyATS validation, as we’ve got in different exams. To not be forgotten, we additionally cowl the flexibility to retrieve well being data by way of Python in opposition to units as effectively.
Lastly, we additionally added the requirement to troubleshoot packet flows from Linux-based hosts operating containers. Everyone knows that containers are the brand new VMs, however the hosts operating 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 customary bridges are outlined and the connection between digital Ethernet (veth) interfaces on the host stage and interfaces outlined inside the container runtime. These abilities are not non-obligatory and we felt it essential to grasp them effectively sufficient to repair them once they break.
We needed to toss in some AI, too
Identical to with the remainder of the skilled automation specializations, some AI wanted to be included inside the examination matters checklist; it’s being talked about all over the place and our certifications must be no totally different.
- Understanding the safety implications of utilizing AI inside the datacenter is essential to guard the huge quantities and worth of that information. Right here there may very well be unintended penalties round information publicity and as a vector for exfiltration.
- As agentic AI turns into mainstream, understanding how these brokers join to numerous platforms, units, 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 non-obligatory talent. It ought to validated for any automation skilled.
Bringing all of it collectively
By means of this weblog, and the earlier ones on the AUTOCOR and ENAUTO 2.0, I hope you’ve gained somewhat bit extra perception into the certification and the precise exams (each core and focus). This isn’t simply associated to the exams and matters themselves, but in addition the mindset shift and totally different strategy in creating the examination matters checklist, shifting from software program engineers which can be studying “community” to community engineers which can be studying “automation.” It sounds refined, however the end result may be fairly totally different. By means of this distinction, we hope that you just discover that the brand new exams align to your automation work in a way more impactful manner.
As at all times, blissful studying! If in case you have any questions, please contact me on X (@qsnyder) or via the Cisco Studying Community message boards.
Efficient February 3, 2026, the 300-635 DCNAUTO examination shall be up to date to v2.0 and renamed, “Automating Cisco Knowledge Heart Networking Options v2.0.”
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