We’ve lastly arrived on the third and ultimate installment of this riveting weblog collection. Whereas some could also be unhappy on the disappearance of additional sleep they acquired from studying this (my prose is often an ideal treatment for insomnia), on this weblog, we’ll be protecting 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 rationale and intent for the massive transforming of the examination matters to help and assist you in your research.
A fork within the street
The unique DCAUTO examination had the “shortest” record 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 often are separate from the datacenter networking groups).
However even if you happen to had 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 related to Cisco Intersight; solely sure builds which had been obtainable solely to particular groups like Cisco DevNet for his or her Sandbox might achieve this.
This lead to an enormous inside choice: How do we offer an automation certification that focuses on the datacenter, covers the community expertise obtainable at this time, consists of 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 indirectly(the highlighted sections). In some circumstances, the matters had been eliminated for a similar as they had been in ENCOR 2.0; matters like Git, primary APIs, or Python digital environments had been eliminated as a result of both (a) they’re assumed data (b) lined within the core examination or (c) might be changed with different applied sciences that will work higher with bigger workflows (e.g. growth inside a container with mapped volumes can substitute 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 throughout 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 methods to use these instruments throughout the community infrastructure turns into a crucial talent.
Area 3.0 acquired a light-weight contact of adjustments, principally 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 deal with the commonest use-cases and applied sciences. Keep 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 assume you’ll be on the lookout for a cause on this one, too. Consider me, it wasn’t a simple choice. We went forwards and backwards on this and there have been robust arguments to each side, however finally, 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 troublesome.
Reasonably than weakening the depth of the check (and the sensible functions gained from it) to assist added breadth, we determined to drop the compute automation fully. I can already hear the sighs of reduction from community automation people, however I do know there are a number of people 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 examine?
Inside the datacenter, there are a number of 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 record 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 should 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 throughout the IaC area. This requires you to be accustomed to 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 recent 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 data round these “community factor” automation duties in Area 3.
By way of particular community factor programmability, we’ve included:
- NETCONF assist, as YANG fashions similar to OpenConfig are utilized in giant, 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 outdoors of using a controller, and the on-box programmability strategies obtainable throughout the Nexus platform
- Information round NXAPI and the movement 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 deal with operational facets of an automation resolution. In any case, what good is deploying a change with out understanding the impression of that change on the community? That is no totally different throughout 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 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 components that touched on model-driven telemetry and understanding subscriptions to information., together with next-generation protocols like gNMI and gRPC. We additionally embrace digital twins and pyATS validation, as we’ve got in different exams. To not be forgotten, we additionally cowl the power to retrieve well being info by way of Python towards 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 consists of 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 stage and interfaces outlined throughout the container runtime. These abilities are not non-obligatory and we felt it essential to know them effectively 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 throughout the examination matters record; it’s being talked about all over the place and our certifications must be no totally different.
- Understanding the safety implications of utilizing AI throughout the datacenter is essential to guard the huge quantities and worth of that information. Right here there might 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 throughout 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 particular exams (each core and focus). This isn’t simply associated to the exams and matters themselves, but additionally the mindset shift and totally different method in creating the examination matters record, transferring from software program engineers which might be studying “community” to community engineers which might be studying “automation.” It sounds refined, however the final result might be fairly totally 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 means.
As all the time, glad studying! You probably 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.”
Join Cisco U. | Be a part of the Cisco Studying Community at this time without spending a dime.
Be taught with Cisco
X | Threads | Fb | LinkedIn | Instagram | YouTube
Use #CiscoU and #CiscoCert to affix the dialog.
