High-Level Abstractions for Programming Software Defined Networks Joint with Nate Foster, David Walker, Arjun Guha, Rob Harrison, Chris Monsanto, Joshua Reich, Mark Reitblatt, Cole Schlesinger Jennifer Rexford Princeton University

Software Defined Networks 2

decouple control and data planes Software Defined Networks 3

decouple control and data planes by providing open standard API Software Defined Networks 4

(Logically) Centralized Controller Controller Platform 5

Protocols  Applications Controller Platform 6 Controller Application

Payoff Cheaper equipment Faster innovation Easier management 7

But How Should We Program SDNs? 8 Controller Platform Controller Application Network-wide visibility and control Direct control via open interface Today’s controller APIs are tied to the underlying hardware

OpenFlow Networks 9

Data Plane: Packet Handling Simple packet-handling rules –Pattern: match packet header bits –Actions: drop, forward, modify, send to controller –Priority: disambiguate overlapping patterns –Counters: #bytes and #packets 10 1.src=1.2.*.*, dest=3.4.5.*  drop 2.src = *.*.*.*, dest=3.4.*.*  forward(2) 3. src= , dest=*.*.*.*  send to controller 1.src=1.2.*.*, dest=3.4.5.*  drop 2.src = *.*.*.*, dest=3.4.*.*  forward(2) 3. src= , dest=*.*.*.*  send to controller

Control Plane: Programmability 11 Events from switches Topology changes, Traffic statistics, Arriving packets Commands to switches (Un)install rules, Query statistics, Send packets Controller Platform Controller Application

E.g.: Server Load Balancing Pre-install load-balancing policy Split traffic based on source IP src=0* src=1*

Seamless Mobility/Migration See host sending traffic at new location Modify rules to reroute the traffic 13

Programming Abstractions for Software Defined Networks 14

Network Control Loop 15 Read state OpenFlow Switches Write policy Compute Policy

Reading State SQL-Like Query Language 16

Reading State: Multiple Rules Traffic counters –Each rule counts bytes and packets –Controller can poll the counters Multiple rules –E.g., Web server traffic except for source Solution: predicates –E.g., (srcip != ) && (srcport == 80) –Run-time system translates into switch patterns srcip = , srcport = srcport = 80

Reading State: Unfolding Rules Limited number of rules –Switches have limited space for rules –Cannot install all possible patterns Must add new rules as traffic arrives –E.g., histogram of traffic by IP address –… packet arrives from source Solution: dynamic unfolding –Programmer specifies GroupBy(srcip) –Run-time system dynamically adds rules srcip = srcip =

Reading: Extra Unexpected Events Common programming idiom –First packet goes to the controller –Controller application installs rules 19 packets

Reading: Extra Unexpected Events More packets arrive before rules installed? –Multiple packets reach the controller 20 packets

Reading: Extra Unexpected Events Solution: suppress extra events –Programmer specifies “Limit(1)” –Run-time system hides the extra events 21 packets not seen by application

Frenetic SQL-Like Query Language Get what you ask for –Nothing more, nothing less SQL-like query language –Familiar abstraction –Returns a stream –Intuitive cost model Minimize controller overhead –Filter using high-level patterns –Limit the # of values returned –Aggregate by #/size of packets 22 Select(bytes) * Where(in:2 & srcport:80) * GroupBy([dstmac]) * Every(60) Select(packets) * GroupBy([srcmac]) * SplitWhen([inport]) * Limit(1) Learning Host Location Traffic Monitoring

Computing Policy Parallel and Sequential Composition Abstract Topology Views 23

Combining Many Networking Tasks 24 Controller Platform Monitor + Route + FW + LB Monolithic application Hard to program, test, debug, reuse, port, …

Modular Controller Applications 25 Controller Platform LB Route Monitor FW Easier to program, test, and debug Greater reusability and portability A module for each task

Beyond Multi-Tenancy 26 Controller Platform Slice 1 Slice 2 Slice n... Each module controls a different portion of the traffic Relatively easy to partition rule space, link bandwidth, and network events across modules

Modules Affect the Same Traffic 27 Controller Platform LB Route Monitor FW How to combine modules into a complete application? Each module partially specifies the handling of the traffic

Parallel Composition [ICFP’11, POPL’12] 28 Controller Platform Route on dest prefix Monitor on source IP + dstip = 1.2/16  fwd(1) dstip = 3.4.5/24  fwd(2 ) srcip =  count srcip =  count srcip = , dstip = 1.2/16  fwd(1), count srcip = , dstip = 3.4.5/24  fwd(2 ), count srcip = , dstip = 1.2/16  fwd(1), count srcip = , dstip = 3.4.5/24  fwd(2), count

Spread client traffic over server replicas –Public IP address for the service –Split traffic based on client IP –Rewrite the server IP address Then, route to the replica Example: Server Load Balancer clients load balancer server replicas

Sequential Composition [NSDI’13] 30 Controller Platform Routing Load Balancer >> dstip =  fwd(1) dstip =  fwd(2 ) srcip = 0*, dstip=  dstip= srcip = 1*, dstip=  dstip= srcip = 0*, dstip =  dstip = , fwd(1) srcip = 1*, dstip =  dstip = , fwd(2 )

Dividing the Traffic Over Modules Predicates –Specify which traffic traverses which modules –Based on input port and packet-header fields 31 Routing Load Balancer Monitor Routing dstport != 80 dstport = 80 >> +

High-Level Architecture 32 Controller Platform M1 M2 M3 Composition Spec

Partially Specifying Functionality A module should not specify everything –Leave some flexibility to other modules –Avoid tying the module to a specific setting Example: load balancer plus routing –Load balancer spreads traffic over replicas –… without regard to the network paths 33 Load Balancer Routing >> Avoid custom interfaces between the modules

Abstract Topology Views [NSDI’13] Present abstract topology to the module –Implicitly encodes the constraints –Looks just like a normal network –Prevents the module from overstepping 34 Real networkAbstract view

Separation of Concerns Hide irrelevant details –Load balancer doesn’t see the internal topology or any routing changes 35 Routing viewLoad-balancer view

High-Level Architecture 36 Controller Platform View Definitions M1 M2 M3 Composition Spec

Supporting Topology Views Virtual ports –(V, 1): [(P1,2)] –(V, 2): [(P2, 5)] Simple firewall policy –in=1  out=2 Virtual headers –Push virtual ports –Route on these ports –From (P1,2) to (P2,5) 37 V 1 2 firewall routing P1 P

Writing State Consistent Updates 38

Writing Policy: Avoiding Disruption Invariants No forwarding loops No black holes Access control Traffic waypointing

Writing Policy: Path for New Flow Rules along a path installed out of order? –Packets reach a switch before the rules do 40 Must think about all possible packet and event orderings. packets

Writing Policy: Update Semantics Per-packet consistency –Every packet is processed by –… policy P1 or policy P2 –E.g., access control, no loops or blackholes Per-flow consistency –Sets of related packets are processed by –… policy P1 or policy P2, –E.g., server load balancer, in-order delivery, … P1 P2

Writing Policy: Policy Update Simple abstraction –Update entire configuration at once Cheap verification –If P1 and P2 satisfy an invariant –Then the invariant always holds Run-time system handles the rest –Constructing schedule of low-level updates –Using only OpenFlow commands! 42 P1 P2

Writing Policy: Two-Phase Update Version numbers –Stamp packet with a version number (e.g., VLAN tag) Unobservable updates –Add rules for P2 in the interior –… matching on version # P2 One-touch updates –Add rules to stamp packets with version # P2 at the edge Remove old rules –Wait for some time, then remove all version # P1 rules 43

Writing Policy: Optimizations Avoid two-phase update –Naïve version touches every switch –Doubles rule space requirements Limit scope –Portion of the traffic –Portion of the topology Simple policy changes –Strictly adds paths –Strictly removes paths 44

Frenetic Abstractions 45 SQL-like queries OpenFlow Switches Consistent Updates Policy Composition

Related Work Programming languages –FRP: Yampa, FrTime, Flask, Nettle –Streaming: StreamIt, CQL, Esterel, Brooklet, GigaScope –Network protocols: NDLog OpenFlow –Language: FML, SNAC, Resonance –Controllers: ONIX, POX, Floodlight, Nettle, FlowVisor –Testing: NICE, FlowChecker, OF-Rewind, OFLOPS OpenFlow standardization – – 46

Conclusion SDN is exciting –Enables innovation –Simplifies management –Rethinks networking SDN is happening –Practice: useful APIs and good industry traction –Principles: start of higher-level abstractions Great research opportunity –Practical impact on future networks –Placing networking on a strong foundation 47

Frenetic Project Programming languages meets networking –Cornell: Nate Foster, Gun Sirer, Arjun Guha, Robert Soule, Shrutarshi Basu, Mark Reitblatt, Alec Story –Princeton: Dave Walker, Jen Rexford, Josh Reich, Rob Harrison, Chris Monsanto, Cole Schlesinger, Praveen Katta, Nayden Nedev Short overview at