Since everyone is talking about Intent Based or Data Driven Networks for a while, I spent some time recently going through work done by Cisco, Juniper, Apstra, Veriflow & Forward Networks in the Area of Intent Based Networking AKA Data Driven Network AKA Self Driving Networks.
So far seems like everyone is trying to solve the different sets of problems with some overlap. Also mostly they use ML/AI in some form or shape. But my assumption is Algorithms under ML/AI umbrella are proprietary (Secret Sauce) for most part with little details available publicly.
Also the common buzzword " Automation " would mean totally different set of things in such world IMHO. So In the mean while below are quick questions you can ask to your fav. OEM vendor guys next time you go for a product/training session around same :) to get more clarity.
> What they really mean by Intent Based Networking ? (Everyone has some different definition for this)
> How do they describe the Intent to the system ?
> How do they map Business Intent & Technology intent and describe it to system ?
> Does the system translate the intent into configurations/policies on it's own or they use some sort of policy language for admin to be used to describe Business and Technical intents to system ?
> What sort of checks that system has to verify described intent and returns feedback to admin ?
> Are there any dry run capabilities into the system ?
> How they maintain the consistency for the intent throughout the life-cycle - Plan, Design, Deploy, Verify, Operate & Optimize ?
> How Intent gets documented and updated over time ?
> How do you describe intent for things like Backup path etc. ?
> How do they create visualization for Intent to present to management & Network Architects ?
> How to modify Intent over the period and what would be the touch points ?
> How their Intent Based Networking is different from policy based network (Remember Promise Theory that ACI Works on) ?
> OEMs AI/ML/DL & Algorithm Details (I doubt they would be willing though) ?
> How do they control AI and ML since they can create their own algorithms and break this closed loop over time ? (Remember what happened with Facebook's AI attempt)
> How do they track changes in such networks such as created by AI/ML dynamically ?
> How does AI/ML understand if it's actual pattern change in network during attack or just traffic pattern change driven by an special event such as heavy load on billing systems during financial year end for example ?
> Do they use graph approach (By building Network Graph such as Link State Protocol Does) or they use relation approach (Such as describing links with properties ) across network components to describe intent ?
> Which Data model they follow to describe intent and push/change configurations ? (Also understanding Data Normalization Techniques & Data Model details will be key to understand support across multiple vendors )
> Do they support APIs to describe intent and to work with other systems as part of larger eco-system ?
> How do they deal with scale ? (Everyone has different sets of limitations here)
> How do they deal with mix of legacy networks & Cloud Networks in hybrid environment ?
> How do they handle Leaky abstraction & Grey failures ?
> How do they operate across multi OEM platforms with different HW/SW capabilities ? (Which essentially means they must form a eco system with selective set of partners as it's going to be an ongoing effort)
> Does the intent description part only takes care of configuration side of things or they even go further with Network Design as part of another abstraction layer ?
Let's park Telemetry related stuff of solution for a while which is another area to dig into in order to fit all pieces together. :) (Maybe another follow up post)
HTH...
Deepak Arora
Evil CCIE
