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Softening the Network: Virtualization’s Final Frontier Steve Riley Technical Director, Office of the CTO Riverbed Technology steve.riley@riverbed.com http://blog.riverbed.com
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Abstractions We’ve Seen
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virtual memory
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virtual disk volumes
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virtual machines
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the illusion of a thing
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abstraction
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no re-programming
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sometimes is disruptive
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PM-1PM-2 VM-1 VM-2 VM-3 VM-4 VM-1 VM-2 VM-3
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meets needs
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provisioning
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moving
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snapshotting
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roll back
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New?
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crude 1.A1.B1.C 2.A2.B2.C
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less crude 1.A1.B1.C 2.A2.B2.C
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less crude 1.A1.B1.C 2.A2.B2.C 1.D2.D
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limitations
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n < ∞
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topology
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static
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interesting 10.M 1.A1.B1.C
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interesting + 10.M 1.A1.B1.C 2.A2.B2.C
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interesting +? 10.M 1.A1.B1.C 2.A2.B2.C
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interesting +?? 10.M 1.A1.B1.C 2.A2.B2.C 1.D2.D
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interesting +!!! 10.M 1.A1.B1.C 2.A2.B2.C 1.D2.D 10.N 1.E1.F 2.E2.F2.G 1.G2.H 2.I
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insane ;) 10.M 1.A1.B1.C 2.A2.B2.C 1.D2.D 10.N 1.E1.F 2.E2.F2.G 1.G2.H 2.I
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limitations
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as before
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+ not cloudable
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operational abstractions aren’t useful
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PM-1PM-2 VM-1 VM-2 VM-3 VM-4 VM-1 VM-2 VM-3 MAC? IP? ACL? state?
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control forwardingforwarding
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limitations
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topology mandates/constraints
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no overlapped addresses
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sloooooow to change
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+ not cloudable
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requirements
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decouple V from P
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V looks like P
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V allows units of operation
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Software Defined Networking (*) * One popular, but not necessarily universal, definition
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control forwardingforwarding
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forwardingforwarding
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application network application tier network tier
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application tier control plane forwarding plane OpenFlow control platform
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forwarding plane
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relatively “dumb”
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does what it’s told
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R.I.P., RIP OSPF IS-IS &c.
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control plane
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centralized
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end-t0-end view (not hop-by-hop)
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programmable
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naturally multitenant
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maintains state
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that’s it?
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virtual server ≠ virtual network
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DatapathConsistency Virtual serverCPU memory device I/O nanosecond operation self-contained Virtual networkaddress contextsall-port knowledge N instances of N states consistency on all paths timely distribution
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DatapathConsistency Virtual serverCPU memory device I/O nanosecond operation = complexity at speed self-contained Virtual networkaddress contextsall-port knowledge N instances of N states consistency on all paths timely distribution = complexity at scale
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The Virtual Network
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decoupled from h/w
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independent from others
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delegated control
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ephemeral
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SDN (*) is a useful tool * As defined previously
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control plane forwarding plane OpenFlow API x86 API VXLAN NVGRE NVP OTV STT
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(
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is SDN (*) a requirement? * As defined previously
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control plane forwarding plane API x86 API VXLAN NVGRE OpenFlow multicast
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)
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How does Alice talk to Bob? API x86 vAPI : “I need a virtual L2-L3 network with these properties…” vSWITCHes in x86 boxes determine optimal path OPENFLOW: “Hardware, plumb the following…”
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x86 Alice VM PM-A Bob VM PM-B
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E V I L
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ThroughputRecv CPUSend CPU Linux bridge9.3 Gbps85%75% OVS bridge9.4 Gbps82%70% OVS-STT9.5 Gbps70% OVS-GRE2.3 Gbps75%97% one flow, two VMs, separate hypervisors ThroughputCPU OVS bridge18.4 Gbps150% OVS-STT18.5 Gbps120% OVS-GRE2.3 Gbps150% aggregate, four VMs, two hypervisors http://networkheresy.com/2012/06/08/the-overhead-of-software-tunneling/
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possibilities
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security application
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QoS application
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WAN op application (*) * hard: distributed cache and symbol vocabulary
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on-demand VPN/C
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infrastructure code
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network code
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decoupled and delegated
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physical L2-L3
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logical L2-L3 L4-L7 services x86
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x86, really?
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complex much CPU
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FW/LB use CPU at flow start
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optimized stacks performance
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upgrade certainty
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distinct security forwarding shaping priority …
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outcomes
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working multitenancy
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isolated addressing
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programmable
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independent and ephemeral
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VM “ ”
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virtual IP virtual MAC
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route my packets/frames without collisions
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move v-net without changes
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tear down when finished
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separately alter physical and virtual topologies
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consider: on-demand HA/DR
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consider: on-demand HA DR
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SDN (*) manages state * As defined previously
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VM “ ”
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“ ”
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“ ”
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abstractional consistency
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(mature orchestration?)
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servers = disposable horsepower
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networks = disposable pathways
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DatapathConsistency Virtual serverCPU memory device I/O nanosecond operation = complexity at speed self-contained Virtual networkaddress contextsall-port knowledge N instances of N states consistency on all paths timely distribution = complexity at scale
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DatapathConsistency Virtual serverCPU memory device I/O nanosecond operation = complexity at speed self-contained Virtual networkaddress contextsall-port knowledge N instances of N states consistency on all paths timely distribution = complexity at scale
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easy familiar point solution ideas
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TaggingSegmentation, not isolation Same address in “both” worlds Hardware has to understand No mobility
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TaggingSegmentation, not isolation Same address in “both” worlds Hardware has to understand No mobility Address mapping Like NAT: update address in place Multiplex large space into small: how? Virtual-to-virtual: physical “punch”
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TaggingSegmentation, not isolation Same address in “both” worlds Hardware has to understand No mobility Address mapping Like NAT: update address in place Multiplex large space into small: how? Virtual-to-virtual: physical “punch” EncapsulationOr tunnels, or overlays (sigh) Worlds can be totally distinct Different forwarding for V and P Strong isolation: no V on P w/o bridge PA demux VA payload
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DatapathConsistency Virtual serverCPU memory device I/O nanosecond operation = complexity at speed self-contained Virtual networkaddress contextsall-port knowledge N instances of N states consistency on all paths timely distribution = complexity at scale programmability and cloudability
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hard scary innovative advancements
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Resources
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networkheresy.com packetpushers.net blog.ioshints.con sdncentral.com
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Thanks for coming! Steve Riley Technical Director, Office of the CTO Riverbed Technology steve.riley@riverbed.com http://blog.riverbed.com
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