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Large scale overlay networks with ovn: problems and solutions
Han Zhou presents problems and solutions for scaling Open Virtual Network (OVN) components in large overlay networks. The key challenges addressed are: 1. Scaling the OVN controller by moving from recomputing all flows to incremental processing based on changes. 2. Scaling the southbound OVN database by increasing probe intervals, enabling fast resync on reconnect, and improving performance of the clustered mode. 3. Further work is planned to incrementally install flows, reduce per-host data, and scale out the southbound database with replicas.
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Large scale overlay networks with ovn: problems and solutions
- 1. Large Scale OverlayNetworks with OVN: Problems and Solutions Han Zhou (hzhou8@ebay.com) Open Infrastructure Summit - Denver, 2019
- 2. Agenda ● Background ● Control-planecomponents scaling ○ OVN-Controller ○ South-bound DB ○ OVN-Northd ● Scaling ACL ● Scaling nested workloads (containers on VMs)
- 3. Background of OVN ●SDN solution developed by OVS (Open vSwitch) community ● OpenStack support - neutron ML2 plugin: networking-ovn ● Kubernetes support - CNI plugin: ovn-kubernetes ● Main Features ● Full L2/L3 virtualization with overlay networks (Geneve, STT, VxLAN) ● L2 gateway, L3 gateway (centralized/distributed) & NAT with HA ● L4 ACLs (stateful FW) with address-set, port-group and packet logging ● Distributed Load-Balancer ● L2/L3 Port-security ● ARP responder, static/dynamic ARP ● Flat/Vlan physical networks ● Native DHCP, Metadata ● Parent-child ports for nested workloads ● QoS ● IPSec ● Policy-based routing ● ...
- 4. ● Logical/physical separation ●Distributed local controllers ● Database Approach (ovsdb) Northd North-bound ovsdb South-bound ovsdb Central North-bound ovsdb Northd South-bound ovsdb Distributed Control Plane OVN-Controller OVS HV HV … OVSDB protocol (RFC7047) HV GW CMS (OpenStack/K8S) Virtual Network Abstractions Logical Flows OpenFlows
- 5. Northd North-bound ovsdb South-bound ovsdb Central North-bound ovsdb Northd South-bound ovsdb OVN-Controller Scaling Challenges OVN-Controller OVS HV HV… OVSDB protocol (RFC7047) HV GW CMS (OpenStack/K8S) Virtual Network Abstractions Logical Flows OpenFlows ● Factors ○ Size of data ○ Rate of changes ● Challenges ○ Big size of data to be processed ■ E.g. 10k logical ports generates >40k logical flows and 10k port-bindings ○ Logical flow parsing is CPU intensive ○ Cloud workload changes frequently ○ Lots of inputs for flow computation
- 6. OVS qos Address Sets (converted) MFFOVN Geneve OVS open_vswitch OVS bridge SB logical_flow SB chassis SB encap SB mc_group SB dp_binding SB port_binding SB mac_binding SB dhcp SB dhcpv6 SB dns SB gw_chassis OVS port SB addr_set SB port_group Runtime Data ------------------------------ Local_datapath Local_lports Local_lport_ids Active_tunnels Ct_zone_bitmap Pending_ct_zones Ct_zones Flow Output --------------------------- Desired_flow_table Group_table Meter_table Conj_id_ofs SB OVSDB input Local OVSDB input Dependency Graph of OVN-Controller Port Groups (converted)
- 7. Original Approach -Recomputing ● Compute OVS flows by reprocessing all inputs when ○ Any input changes ○ Or even when there is no change at all (but just unrelated events) ● Benefit ○ Relatively easy to implement and maintain ● Problems ○ 100% CPU of ovn-controller process on all compute nodes ○ High control plane latency
- 8. Solution - IncrementalProcessing Engine ● DAG representing dependencies ● Each node contains ○ Data ○ Links to input nodes ○ Change-handler for each input ○ Full recompute handler ● Engine ○ DFS post-order traverse the DAG from the final output node ○ Invoke change-handlers for inputs that changed ○ Fall back to recompute if for ANY of its inputs: ■ Change-handler is not implemented for that input, or ■ Change-handler cannot handle the particular change (returns false) input intermediate input intermediate output input
- 9. OVS qos Address Sets (converted) MFFOVN Geneve OVS open_vswitch OVS bridge SB logical_flow SB chassis SB encap SB mc_group SB dp_binding SB port_binding SB mac_binding SB dhcp SB dhcpv6 SB dns SB gw_chassis OVS port SB addr_set SB port_group Runtime Data ------------------------------ Local_datapath Local_lports Local_lport_ids Active_tunnels Ct_zone_bitmap Pending_ct_zones Ct_zones Flow Output --------------------------- Desired_flow_table Group_table Meter_table Conj_id_ofs SB OVSDB input Local OVSDB input Input with change handler implemented Change Handler Implemented Port Groups (converted)
- 10. ● Create andbind 10k ports on 1k HVs ○ Simulated 1k HVs on 20 BMs x 40 cores (2.50GHz) ○ 10k ports all under the same logical router ○ Batch size 100 lports ○ Bind port one by one for each batch ○ Wait all ports up before next batch CPU Efficiency Improvement
- 11. ● End toend latency on top of 10k existed logical ports ○ Create one more logical port and bind the port on HV ○ Wait until northd generate lflows and create port-binding in SB ○ Wait until ovn-controller claim the port on HV ○ Wait until northd generate all lflows ○ Wait until OVS flows programmed on all HVs Latency Improvement
- 12. Tests at LargerScale ● Next bottle-necks: ○ OVS flow installation ○ Port-binding handling when the binding happens locally
- 13. What’s next forIncremental-Processing (WIP) ● Incremental flow installation ○ Low hanging fruit - with the help of incremental flow computing ● Implement more change handlers as needed ○ E.g. support incremental processing when port-binding happens locally - further improve end-to-end latency ● New implementation: Differential Datalog (DDlog) ○ Data-flow approach ○ Reuse the effort taken for Northd improvement (will be discussed in Northd scaling) ● Upstream? ○ Not in upstream, because DDlog is the preferred long term solution ○ For those who need this: ■ Rebased on Master: https://github.com/hzhou8/ovs/tree/ovn-controller-inc-proc ■ Rebased on 2.11: https://github.com/hzhou8/ovs/tree/ip12_rebase_on_2.11 ■ Rebased on 2.10: https://github.com/hzhou8/ovs/tree/ip12_rebase_on_2.10
- 14. OVN-Controller Other Improvements(WIP) ● Reduce data size per-HV ○ Problem: External Provider Network connects everything ○ Solution: Don’t cross external network boundary when calculating connected datapaths ● On-demand tunnel port creation ○ Problem: Too many OVS ports when there are a lot of HVs ○ Solution: Create tunnel to a remote host only if there are ports on these hosts logically connected.
- 15. ● Factors ○ Numberof clients (HVs & GWs) ○ Size of data ○ Rate of changes ● Problems ○ Probe handling ○ Data resync during restart/failover ○ Clustered-mode problems Northd North-bound ovsdb South-bound ovsdb Central North-bound ovsdb Northd South-bound ovsdb SB DB Scaling Challenges OVN-Controller OVS HV HV … OVSDB protocol (RFC7047) HV GW CMS (OpenStack/K8S) Virtual Network Abstractions Logical Flows OpenFlows
- 16. SB DB Probe ●Default 5 sec probe interval causing connection flapping ○ Ovsdb-server response can occasionally exceed 5 sec ■ DB log compression ■ Large transaction handling ○ Clients reconnecting adds more load to the server - cascade failure ■ Clients resync data from server (solved - see next slide) ● Solution ○ Increase probe interval ■ Client side (on HVs) ● ovs-vsctl set open . external_ids:ovn-remote-probe-interval=60000 ■ Server side (DON’T FORGET!!) ● ovn-sbctl -- --id=@conn_uuid create Connection target="ptcp:6642:0.0.0.0" inactivity_probe=0 -- set SB_Global . connections=@conn_uuid ○ Rely on external monitorings for HVs connectivity
- 17. Data re-sync duringDB reconnect ● Problem ○ OVSDB client caching => NOT a problem ○ Server restart/failover: re-sync data for all clients. => This is the problem! ● Solution - OVSDB fast re-sync (in master -> v2.12) ○ Track and maintain recent history transactions in disk and memory. ○ New method monitor_cond_since in OVSDB protocol, to request changes since last point before connection lost. ○ Note: now it works for clustered mode only. ● Test Result - 1k HVs, 10k ports ○ Before: SB DB 100% CPU, >30 min to recover. ○ After: No CPU spike, all connections restored in <1 min (probe interval).
- 18. OVSDB Clustered Mode ●Raft based clustering (experimental support since v2.9) ● Problems at scale ○ High CPU load (solved in master) ○ Follower update latency (solved in master) ○ Leader flapping (WIP, workaround ready) ○ Client reconnect (solved in master)
- 19. OVSDB Clustered Mode- High CPU ● OVSDB Raft Implementation ○ Preprocessing on followers before sending to leader - share some load for leader ○ Send preprocessed transaction to leader together with a prerequisite version ID ● Problem ○ Lots of prerequisite check failure and retry at large scale ■ Different HVs update chassis/port_binding at the same time through different follower nodes ○ Continuous retry causes 100% CPU ● Solution (in master -> v2.12) ○ Retry only when the follower have applied the largest local Raft log index ■ Otherwise, the prerequisite is already out-of-date, so don’t waste CPU
- 20. OVSDB Clustered Mode- Follower Latency ● Original behavior: leader sends Raft log update to follower nodes when: ○ A new change is proposed, or ○ A heartbeat is sent ● Problem ○ Update from follower node suffers big latency ● Solution (in master -> v2.12) ○ Send log to followers as soon as a new entry is committed ● Test result: 100 updates through same follower from same client ○ Before: >30 sec ○ After: 500 ms
- 21. OVSDB Clustered Mode- Leader Flapping ● Problem: heartbeat timeout, triggering re-election ○ Large transaction execution ○ Raft log compression (snapshot) ● Solution ○ Quick and dirty: Increase election timeout (hardcode) ○ Short term: Make election timeout configurable at cluster level (WIP) ○ Longer term: Separate thread for Raft RPC (WIP) ■ Still need to configure timeout for snapshot scenarios
- 22. OVSDB Clustered Mode- Client Reconnect ● Problem: during leader failover, all clients of new leader will reconnect ○ DB state changes to “disconnected” when there is no leader (temporarily) ○ Client tries to reconnect to a new node ● Solution (in master -> v2.12) ○ Don’t change state to “disconnected” if ■ Current node is candidate, and ■ Election didn’t timeout yet
- 23. Scale Test forClustered Mode ● Setup ○ 3-node cluster, 1k HVs ○ Election timeout: 10s (hardcoded in the test) ● Test ○ Keep creating and binding ports up to 10k ○ Periodically kill->wait(10s)->start each ovsdb-server randomly ● Test passed at scale! ○ All port creation and binding completed correctly. ○ Fast-resync helped!
- 24. Further Improvement: SB-DBScale-out Replicas (TODO) ● How to support more HVs - 2k? 5k? 10k? ○ More nodes in cluster? Doesn’t scale. ○ Multi-threading OVSDB? Would help, but... ● Precondition: no write to SB from HV ○ Chassis/Encap/Port-binding update by CMS/northd only ○ Does not use dynamic ARP (mac-binding) ● How ○ Use replication mode of OVSDB to create N read-only replicas ○ HV connections sharding on read-only replicas ○ HV can failover to other replicas NorthdNorthd SB ovsdb SB Replica 1 SB Replica 2 SB Replica n … HV HV HV … HV HV HV … HV HV HV … CMS NB ovsdb
- 25. Northd North-bound ovsdb South-bound ovsdb Central North-bound ovsdb Northd South-bound ovsdb OVN-Northd Scaling Challenges HV… OVSDB protocol (RFC7047) HV GW CMS (OpenStack/K8S) Virtual Network Abstractions Logical Flows OpenFlows ● Factors ○ Size of data ○ Rate of changes ● Problems ○ Recompute
- 26. OVN-Northd Incremental Processing(WIP from community) ● OVN-Northd is a perfect target user of Differential Datalog (DDlog) ○ Inputs - NB DB tables (logical routers, switch, port, etc.) ○ Outputs - SB DB tables (logical flows, port-bindings, etc.) ○ Rules to convert inputs to outputs ● Differential Datalog ○ An open-source datalog language for incremental data-flow processing ○ Defining inputs and outputs as relations ○ Defining rules to generate outputs from inputs ● Efforts can be reused by OVN-Controller ○ OVSDB - DDlog wrappers ○ Process framework changes
- 27. ● OVN-Northd ● OVN-SBDB ● OVN-Controller Northd North-bound ovsdb South-bound ovsdb Central North-bound ovsdb Northd South-bound ovsdb Recap Scaling Bottlenecks OVN-Controller OVS HV HV … OVSDB protocol (RFC7047) HV GW CMS (OpenStack/K8S) Virtual Network Abstractions Logical Flows OpenFlows
- 28. Some More ScalingProblems ● Security Group / Network policy using ACLs ● Nested workloads (K8S containers)
- 29. ACLs ● Used bySecurity Group (OpenStack) / Network Policy (K8S) ● Typical use case: members of same group are allowed to access each other ● Naked => O(N^2) ● Using Address Set => O(N) ● #Flows in OVS is always O(M*N) (M = number of ports on the HV) outport == <port1_uuid> && ip4 && ip4.src == {ip1, ip2, …, ipN} outport == <port2_uuid> && ip4 && ip4.src == {ip1, ip2, …, ipN} ... outport == <portN_uuid> && ip4 && ip4.src == {ip1, ip2, …, ipN} outport == <port1_uuid> && ip4 && ip4.src == $as_ip4_sg1 outport == <port2_uuid> && ip4 && ip4.src == $as_ip4_sg1 ... outport == <portN_uuid> && ip4 && ip4.src == $as_ip4_sg1
- 30. Solution - PortGroup (Released in v2.10) ● All-in-one ● Greatly simplified CMS Implementation ○ networking-ovn ○ ovn-kubernetes ● Enables more efficient OVS flow generation with conjunction, when multiple ports on same HV belongs to same port-group ○ E.g. ■ N members in a port-group, all M ports on HV1 belong to this group ■ Number of OVS flows on HV1 will be M + N, instead of M * N outport == @port_group1 && ip4 && ip4.src == $port_group1_ip4 CMS creates port-group instead of address-set OVN-Northd generates address-set for you
- 31. Further Improvement -Group-ID in Packet (TODO) ● Problem - still too many OVS flows ○ Best case: M + N, if all M ports on HV belongs to same group. ○ Worst case: M * N, if ports are distributed randomly. ■ M ports on HV, each belongs to a different group, each group has N members ● Solution (just an idea) ○ Encoding port-group in tunnel metadata ■ Only M flows in all cases ■ Best part: no local flow change needed for remote member changes ○ Challenge: what if a port belongs to multiple groups ■ Limit the number of groups for a single port ■ Fall back to old way if exceeds ○ Limitation: works for ingress (to-lport) rules only outport == @port_group1 && src_group_id == <group1 id> From tunnel metadata
- 32. Scaling Nested Workloads ●Use Case ○ VM overlay networking with OVN (e.g. using OpenStack networking-ovn) ○ Run Kubernetes on top of the VMs ● Problem ○ How to connect the pods at scale?
- 33. ARP Proxy ● OVNdoesn’t support MAC-learning (MAC-Port binding learning), but IP-MAC binding can be learned through ARP ● How ○ LR send ARP request for Pod IPs ○ ARP proxy in the VM replies with VM’s MAC for all Pod IPs on the VM ● Works, but ○ Requires VM and Pods on same subnet ○ Unreliable when SB DB connection fails ○ Scale: O(N), N = number of pods, usually much bigger than number of VMs ■ Note: IP-MAC Binding incremental processing change handler is implemented - no re-compute. HV VM OVS Pod Pod Pod Pod ARP Proxy OVN Controller SB IP-MAC Binding Table LR ARP Cache (dynamic): 10.0.0.102 => aa:bb:cc:dd:ee:ff 10.0.0.103 => aa:bb:cc:dd:ee:ff 10.0.0.104 => aa:bb:cc:dd:ee:ff ... 10.0.0.102 10.0.0.103 10.0.0.104 10.0.0.105 10.0.0.2 (aa:bb:cc:dd:ee:ff)
- 34. LR Static Route ●Assign Pod subnet(s) per VM (minion) ● How ○ Configure static routes in OVN LR for pod subnets: next hop = VM IP ● Considerations ○ De-couples VM and Pod subnets ○ Declarative, more reliable than ARP ○ May waste more IPs, but size of subnet is flexible ○ Scale: O(S), S = number of pod subnets ■ Worst case O(N), N = number of pods, if subnet size is /32. HV VM OVS Pod Pod Pod Pod 10.0.0.2/25 10.0.0.3/25 10.0.0.4/25 10.0.0.5/25 172.0.0.2/24 LR Routing Table (static): 10.0.0.0/25 => 172.0.0.2 10.0.0.128/25 => 172.0.1.100 10.0.0.1/25 => 172.0.1.3 ...
- 35. ● OVS/OVN ○ http://www.openvswitch.org/ ●Networking-OVN ○ https://docs.openstack.org/networking-ovn/latest/ ● OVN-Kubernetes ○ https://github.com/openvswitch/ovn-kubernetes/ ● OVN-Scale-Test ○ https://github.com/openvswitch/ovn-scale-test ● GO-OVN library ○ https://github.com/eBay/go-ovn References