I’m Paul Parker Johnson from ACG research based in Boston and aside from having a long connection with with operator networks and management of them my connection into Omaha nap is especially grounded in NFV considerations and use cases that have to do with the emerging edge computing universe just to share my own vantage point on it you know here.
At the cop here at the Congress there’s no shortage of interest in orchestration.
Automation and such topics so and there’s also great interest in the onap topic as well so I’m sure that this session will be informative to you on all of those dimensions as far as own apps.
Contribution to Progress is concerned a little bit of context on fundamental motivations and goals for why.
Orchestration and automation is is of such high interest much of this you viscerally know from your own work but it’s worthwhile just to tee it up a little bit at the beginning of the the cycle because there will.
Be many details and the upcoming presentations goal.
Number one I have two goals this slide in the next goal number one is around actually creating usable consumable applications efficiently.
And at scale for operators this has many many contexts but applications are becoming more complex they’re becoming more delivered from multiple clouds the management and operation problem is is not as simple as each person running his own portion there is.
In fact orchestration that’s required to do augmented reality to do video analytics and to do real-time monitoring of production processes and so forth goal number two it’s a little bit less visually obvious but just to net it out.
This little graph here represents agility or efficiency.
And it’s it’s the out it’s the kind of output that we do from comparisons of existing methods of operation to new methods of operation and calibrating in what way is automation.
Efficiency going to contribute to positive results and the long and short is that the objective is to achieve an accelerated time to positive results whether you measure that in savings or you measure that.
In revenues but this is a this is a strong motivator for.
How you tell when it’s all said and done have you made progress so that’s goal number two now all those things being so.
Simple to to view this has to be overlaid into a large operator context in many different.
Use cases and use case by use case we’re not sure why so much use case by use case there is a need to understand how this is going to get done and how the solution is going to get realized this particular chart here is a multi cloud reference model.
From the current onap work that shows through the green arrows the way that multiple operators who are operating different infrastructures and domains can relate to each other I kind of wanted to use that for shock value because it’s probably the most complex one that.
Could be envisioned in in the process but the full work of the community and through this initiative is oriented toward reducing the operations of the various lifecycle elements in.
Deployment to being something simpler something extensible something faster to use in creating a collaboration between let’s say and over the top cloud provider and a.
Transport network cloud provider with that as a use case example then the way that this maps into the work of the community is through its various projects which are illustrated in the reference architecture or the framework model that the onap community has developed this one having been yielded and as part of the current casablanca release from the community and the purpose of the circles here is is just to draw attention into what are the elements that fit into the flow how do they how do they actually get focus within the.
Different project teams of the community and you’ll hear more about that so the whole point is that you can reduce this you know sort of compelling set of goals into the work areas that.
Comprise the program for for this set of projects overall and so you know having been around the block a little bit and having been through multiple generations of management and orchestration and and such you know we’ve used models before of one type or another and we’ve had different.
Amounts of progress so what’s different this time why you know why is it likely that that we should be optimistic about producing a result that can be used in practice my opinion is essentially it boils down to the size of the community that’s involved in the engage it’s less everybody should be aware it’s quite large but it’s.
Non-trivial as far as how do how the investments are being made and how fast.
Progress can go the second one is extensive pervasive pervasive adoption.
Of extensible data models not just static data models or ones that take long time to to evolve but ones that have reasonable designed to them and can.
Be expanded as use cases grow you’ll hear more about that and the last one is both the real and a desired embrace of DevOps as time goes on this is not simple it has lots of uses within the within the project mix as you can imagine but all these attributes are different from what’s happened before these these are not the same old method.
That’s been tried in the past and I think give us reason for thinking that progress can be more tangible and faster in this round.