We’ve lastly arrived on the third and remaining installment of this riveting weblog collection. Whereas some could also be unhappy on the disappearance of additional sleep they obtained from studying this (my prose is normally an important remedy 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. Identical to the weblog on AUTOCOR and ENAUTO 2.0, I hope that this may assist make clear the explanation and intent for the big 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 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 when you had been in a corporation 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 had been out there solely to particular groups like Cisco DevNet for his or her Sandbox might achieve this.
This lead to an enormous inner determination: How do we offer an automation certification that focuses on the datacenter, covers the community expertise out there in the present day, contains platforms and units, and covers the evolving realities within the datacenter (like Kubernetes and containers)? We had some robust selections 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?
Based mostly on this picture, you may see that a big chunk of the unique blueprint has been eliminated/modified not directly(the highlighted sections). In some instances, the matters had been eliminated for a similar as they had been in ENCOR 2.0; matters like Git, fundamental APIs, or Python digital environments had been eliminated as a result of both (a) they’re assumed information (b) coated within the core examination or (c) may be changed with different applied sciences that will work higher with bigger workflows (e.g. improvement within a container with mapped volumes can change 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. Having the ability to automate platforms and applied sciences with instruments which have multi-platform help is necessary as a result of these datacenters are more and more heterogeneous. So understanding easy methods to use these instruments inside the community infrastructure turns into a important talent.
Area 3.0 obtained a lightweight contact of modifications, 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 concentrate on the commonest 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 a number of the esoteric or much less used options and performance.
And also you dropped compute?!
Sure.
I suppose you’ll be on the lookout for a cause on this one, too. Imagine me, it wasn’t a simple determination. We went backwards and forwards on this and there have been sturdy arguments to each side, however finally, most of the time, 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.
Moderately than weakening the depth of the take a look at (and the sensible functions 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 people, however I do know there are a number of people 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 a number of key applied sciences that we selected to concentrate on. 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, but it surely’s useful to set context round your research.
Infrastructure as Code (IaC)
The datacenter should be:
- Agile
- Multivendor
- Even multicloud
This implies click-ops or particular person automations for various platforms received’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 aware of the instruments and management options in addition to the platforms coated by the blueprint.
On-box automation and programmability
With the scale and scale of recent 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 information round these “community factor” automation duties in Area 3.
By way of particular community factor programmability, we’ve included:
- NETCONF help, as YANG fashions akin to OpenConfig are utilized in giant, probably 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 through 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 out there inside the Nexus platform
- Data round NXAPI and the circulation 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 concentrate on operational facets of an automation resolution. In spite of everything, what good is deploying a change with out understanding the influence of that change on the community? That is no completely different inside the datacenter and a few would argue that it’s extra necessary; datacenters are finely tuned devices to maneuver knowledge in a short time from place to position. If it doesn’t work, it’s typically costing giant sums of cash.
On this examination, we’ve not a lot “eliminated” matters, however shifted them in complexity. The unique DCAUTO examination had parts that touched on model-driven telemetry and understanding subscriptions to knowledge., together with next-generation protocols like gNMI and gRPC. We additionally embrace digital twins and pyATS validation, as we’ve in different exams. To not be forgotten, we additionally cowl the flexibility to retrieve well being info through Python in opposition to units as nicely.
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 commonplace bridges are outlined and the connection between digital Ethernet (veth) interfaces on the host degree and interfaces outlined inside the container runtime. These expertise are not non-obligatory and we felt it necessary to know them nicely sufficient to repair them after 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 in all places and our certifications needs to be no completely different.
- Understanding the safety implications of utilizing AI inside the datacenter is necessary to guard the huge quantities and worth of that knowledge. Right here there might be unintended penalties round knowledge 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 job; 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 way of this weblog, and the earlier ones on the AUTOCOR and ENAUTO 2.0, I hope you’ve gained slightly 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 completely different strategy in creating the examination matters checklist, transferring from software program engineers which might be studying “community” to community engineers which might be studying “automation.” It sounds refined, however the consequence may 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 method.
As all the time, completely happy studying! When 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 will likely be up to date to v2.0 and renamed, “Automating Cisco Information Heart Networking Options v2.0.”
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