Frenetic : Programming Software Defined Networks

1. Frenetic: Programming Software Defined Networks Jennifer Rexford Princeton University http://www.frenetic-lang.org/ Joint with Nate Foster, David Walker, Rob Harrison, Chris Monsanto, Cole Schlesinger, Mike Freedman, Mark Reitblatt, Joshua Reich

2. Traditional Networks Management Plane Monitors traffic, configures policy Control Plane (software) Tracks topology; computes routes; modifies data plane Data Plane (hardware) Forwards, filters, buffers, tags, rate-limits; collects statistics

3. Software Defined Networking (SDN) Logically-centralized control Smart, slow API to the data plane (e.g., OpenFlow) Dumb, fast Switches

4. Momentum • Everyone has signed on • Google, Facebook, Microsoft, Yahoo, Verizon, Deutsche Telekom • New applications • Host mobility • Server load balancing • Network virtualization • Dynamic access control • Energy-efficiency • Real deployments

5. Programming OpenFlow Networks • The Bad • Low-level programming interface • Functionality tied to hardware • Explicit resource control • The Good • Simple data plane abstraction • Logically-centralized architecture • Direct control over switch policies • The Ugly • Non-modular, non-compositional • Programmer faced with challenging distributed programming problem Images by Billy Perkins

6. Language-Based Abstractions • Benefits • Modularity • Portability • Efficiency • Assurance • Simplicity Simple, high-level abstractions are crucial for achieving the vision of software-defined networking.

7. OpenFlow Networks

8. Data-Plane: Simple 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 • src=1.2.*.*, dest=3.4.5.*  drop • src = *.*.*.*, dest=3.4.*.*  forward(2) • 3. src=10.1.2.3, dest=*.*.*.*  send to controller

9. Controller: Programmability Application Network OS Events from switches Topology changes, Traffic statistics, Arriving packets Commands to switches (Un)install rules, Query statistics, Send packets

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

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

12. Programming Abstractions for Software Defined Networks

13. Three Main Abstractions Composing modules Reading state Writing policies OpenFlow Switches

14. Reading State: Multiple Rules • Traffic counters • Switch counts bytes and packets matching a rule • Controller application polls the counters • Multiple rules • E.g., Web server traffic except for source 1.2.3.4 • Solution: predicates • E.g., (srcip != 1.2.3.4) && (srcport == 80) • Run-time system translates into switch patterns 1. srcip = 1.2.3.4, srcport = 80 2. srcport = 80

15. 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 5.6.7.8 • Solution: dynamic unfolding • Programmer specifies GroupBy(srcip) • Run-time system dynamically adds rules 1. srcip = 1.2.3.4 2. srcip = 5.6.7.8 1. srcip = 1.2.3.4

16. Reading: Extra Unexpected Events • Common programming idiom • First packet goes to the controller • Controller application installs rules packets

17. Reading: Extra Unexpected Events • More packets arrive before rules installed? • Multiple packets reach the controller packets

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

19. 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 Traffic Monitoring Select(bytes) * Where(in:2 & srcport:80) * GroupBy([dstmac]) * Every(60) Learning Host Location Select(packets) * GroupBy([srcmac]) * SplitWhen([inport]) * Limit(1)

20. Composition: Multiple Modules • Networks have multiple policies • Routing • Traffic monitoring • Access control • Challenges • Common set of rules in the switches • Processing the same packets • OpenFlow API is not modular • Programmer must combine the logic

21. Composition: Simple Repeater Simple Repeater def switch_join(switch): # Repeat Port 1 to Port 2 p1 = {in:1} a1 = [out:2] install(switch, p1, DEFAULT, a1) # Repeat Port 2 to Port 1 p2 = {in:2} a2 = [out:1] install(switch, p2, DEFAULT, a2) Controller 1 2 When a switch joins the network, install two forwarding rules.

22. Composition: Web Traffic Monitor Monitor “port 80” traffic def switch_join(switch)): # Web traffic from Internet p = {in:2, srcport:80} install(switch, p, DEFAULT, []) query_stats(switch, p) def stats_in(switch, p, bytes, …) print bytes sleep(30) query_stats(switch, p) 1 2 Web traffic When a switch joins the network, install one monitoring rule.

23. Composition: Repeater + Monitor Repeater + Monitor def switch_join(switch): pat1 = {in:1} pat2 = {in:2} pat2web = {inport:2, srcport:80} install(switch, pat1, DEFAULT, None, [out:2]) install(switch, pat2web, HIGH, None, [out:1]) install(switch, pat2, DEFAULT, None, [out:1]) query_stats(switch, pat2web) def stats_in(switch, xid, pattern, packets, bytes): print bytes sleep(30) query_stats(switch, pattern) Must think about both tasks at the same time.

24. Composition: Frenetic is Modular # Static repeating between ports 1 and 2 def repeater(): rules=[Rule(in:1, [out:2]), Rule(in:2, [out:1])] register(rules) Repeater # Monitoring Web traffic def web_monitor(): q = (Select(bytes) * Where(in:2 & srcport:80) * Every(30)) q >> Print() Monitor # Composition of two separate modules def main(): repeater() web_monitor() Repeater + Monitor

25. Composition: Reactive Run-Time • Microflow-based • Send first packet to the controller • Install rule if possible • Check all policies • Accumulate actions to perform on packet • Check all queries • If no matches: install a rule to handle remaining packets of the flow

26. Composition: Proactive [POPL’12] • Proactive, wildcard rules • Keep packets in the “fast path” • “Cross-product” of predicates • Translate predicates into rules • Convert each predicate to one or more rules • Minimize to produce a smaller set of rules • Reactive specialization • Dynamically expanding the policy as packets arrive in:1 in:2 & srcport=80 in:2 * in:1 in:2 * in:2 & srcport=80 * X =

27. Writing Policy: Avoiding Disruption

28. Writing Policy: Avoiding Disruption • Reasons • Routine maintenance • Unexpected failure • Traffic engineering • Fine-grained security • Invariants • No forwarding loops • No black holes • Access control • Traffic waypointing

29. Writing Policy: Traffic Engineering • Shortest-path routing • Controller computes shortest paths • … based on preconfigured link weights 1 1 1 1 3

30. Writing Policy: Traffic Engineering • Transient loop • Update top switch to forward down • … while bottom switch still forwards up 1  5 1 1 1 3

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

32. Writing Policy: Update Semantics P1 • Per-packet consistency • Every packet is processed by • … policy P1 or policy P2, • … but not a mixture of the two • E.g., access control, no loopsor blackholes during routing change • Per-flow consistency • Sets of related packets are processed by • … policy P1 or policy P2, • … but not a mixture of the two • E.g., server load balancing, in-order delivery, … P2

33. Writing Policy: Policy Update • Simple abstraction • Update the entire configuration at once • E.g., per_packet_update(P2) • 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 • Applying optimizations to limit the number of rules • Using only OpenFlow commands! P1 P2

34. 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, thenremove all version # P1 rules

35. Writing Policy: Optimizations • Avoid two-phase commit • Naïve version touches every switch • Doubles rule space requirements • Limit scope of two-phase commit • Affects only a portion of the traffic • Affects only a portion of the topology • Simple policy changes • Extension: strictly adds paths • Retraction: strictly removes paths • Run-time system applies optimizations

36. Frenetic Abstractions Policy Composition Consistent Updates SQL-likequeries OpenFlow Switches

37. Ongoing Work • Network virtualization • Applications see abstract topology • E.g., one big switch

38. Ongoing Work • Network virtualization • Applications see abstract topology • E.g., one big switch • Joint host-network management • Measurement and control • … through local host agent

39. Ongoing Work • Network virtualization • Applications see abstract topology • E.g., one big switch • Joint host-network management • Measurement and control • … through local host agent • Policy transformation • Spread rules over many switches • E.g., distributed firewall/load-balancer

40. 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, Nettle, FlowVisor, RouteFlow • Testing: MiniNet, NICE, FlowChecker, OF-Rewind, OFLOPS • OpenFlow standardization • http://www.openflow.org/ • https://www.opennetworking.org/

41. 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

44. Thanks to My Frenetic Collaborators Rob Harrison Nate Foster Mike Freedman Mark Reitblatt Dave Walker Alec Story Chris Monsanto Josh Reich