PRPv1 Discussion topics Eli Dart, Network Engineer ESnet Science Engagement Lawrence Berkeley National Laboratory National Research Platform Workshop Bozeman, MT August 7, 2017

Outline PRPv1 as a routed layer3 network Layer2 vs. Layer3 Science DMZs Notes on the theme of Scalability 11/24/2018

PRPv1 Diagram Primary substrate is CENIC HPR Layer3 connectivity between campus DMZs Connectivity to other sites via Layer3 peering Usually with CENIC But, if there is other policy, traffic follows that policy

Layer2 vs. Layer3 Connecting two DTNs to each other at Layer2 is quite different from connecting them at Layer3 Layer2 connection: Determine whether layer2 services exist between DMZs Scientist typically can’t do this, and so needs an engineer to help Determine which IP addresses will be used for the connection Scientist typically can’t do this either – need engineering assistance Then configure the DTNs with the addresses, VLANs, etc. Resolve security policy issues between DTNs, if any Set up the circuit Can be done by the scientist if they have permission – typically done by network engineers Debug the circuit if the DTNs can’t talk Often requires detailed knowledge of the network path and devices Layer2 circuit often must be modified in order to troubleshoot it No way for a scientist to do this 11/24/2018

Layer2 vs. Layer3, Continued Connectivity at Layer3 is straightforward Scientist reasons about their data Scientist uses the data transfer application Scientist involves helpdesk/engineering only in case of problems The difference between the Layer2 and Layer3 case is stark In the Layer2 case, scientist must involve engineering at the beginning In the Layer3 case, engineering is only involved in case of problems The choice of Layer3 for PRPv1 was a wise choice 11/24/2018

Scalability There are many different ways to think about scalability – some are: Technology, architecture, complexity People People scale terribly – primary driver for other scalability needs Technology - hardware DTNs, networks, storage, detectors, simulations, etc. Much of this is governed by the same underlying physics Semiconductors, Moore’s Law, etc. Storage currently appears to be more difficult Technology – software Command-line tools vs. GUI tools vs. API-driven tools More data, more files  error handling, automation 11/24/2018

Scalability, Continued Architecture Science DMZ model makes it easier to get good results more often Less work for people Ability to more easily deploy better tools and systems Complexity Nobody’s friend People are bad at keeping track of complex things Complex processes are hard to get right every time Simplifying and standardizing allows tasks to be automated Remember the larger context Science is changing dramatically Scientists need a way to keep up, and we need a way to help them 11/24/2018

PRPv1 – Good Set Of Choices The PRP collaboration made a good set of decisions Routed Layer3 architecture leverages many advantages Self-service by scientists (just go use the DTNs without reasoning about the network) Standard troubleshooting tools work Etc. etc. etc. Allows the collaboration to focus on the harder stuff Fixing performance problems Science engagement Etc. As we continue to think about scaling in the NRP context, let’s not forget our early successes 11/24/2018

Thanks! Eli Dart Energy Sciences Network (ESnet) Lawrence Berkeley National Laboratory http://fasterdata.es.net/ http://my.es.net/ http://www.es.net/