Chapter 7: Leaf-Spine Fabric

This chapter describes a leaf-spine switching fabric implemented by a collection of control applications. We use Trellis, running on ONOS, as our exemplar implementation. Various aspects of Trellis were introduced in earlier chapters, so we summarize those highlights before getting into the details.

  • Trellis supports the leaf-spine fabric topology that is commonly used to interconnect multiple racks of servers in a datacenter (see Figure 9), but it also supports multi-site deployments (see Figure 14). Trellis uses only white-box switches to build out the fabric. It can run on a mix of fixed-function and programmable pipelines, but is running in production with the former.
  • Trellis supports a wide-range of L2/L3 features, all re-implemented as SDN control apps (with the exception of a DHCP server used to relay DHCP requests and a Quagga BGP server used to exchange BGP routes with external peers). Trellis implements L2 connectivity within each server rack, and L3 connectivity between racks.
  • Trellis supports access/edge networking technologies, such as PON (see Figure 10) and RAN (see Figure 14), including support for (a) routing IP traffic to/from devices connected to those access networks, and (b) off-loading access network functionality into the fabric switches.

This chapter does not give a comprehensive description of all of these features, but it does focus on the datacenter fabric use case, which is sufficient to illustrate the approach to building a production-grade network using SDN principles. More information about the full range of Trellis design decisions is available on the Trellis website:

Further Reading

Trellis. Open Networking Foundation, 2020.

7.1 Feature Set

SDN provides an opportunity to customize the network, but for pragmatic reasons, the first requirement for adoption is to reproduce functionality that already exists, and do so in a way that reproduces the resilience and scalability of legacy solutions. Trellis has satisfied this requirement, which we summarize here.

First, with respect to L2 connectivity, Trellis supports VLANs, including native support for forwarding traffic based on VLAN id, along with QinQ support based on an outer/inner VLAN id pair. Support for QinQ is particularly relevant to access networks, where double tagging is used to isolate traffic belonging to different service classes. In addition, Trellis supports L2 tunnels across the L3 fabric (both single and double tagged).

Second, with respect to L3 connectivity, Trellis supports IPv4 and IPv6 routing for both unicast and multicast addresses. For the latter, Trellis implements centralized multicast tree construction (as opposed to running a protocol like PIM), but does include IGMP support for end hosts wishing to join/leave multicast groups. Trellis also supports both ARP (for IPv4 address translation) and NDP (for IPv6 neighbor discovery), along with support for both DHCPv4 and DHCPv6.

Third, Trellis provides high availability in the face of link or switch failures. It does this through a combination of well-known techniques: dual-homing, link binding, and ECMP link groups. As illustrated in Figure 36, each server in a Trellis cluster is connected to a pair of ToR (leaf) switches, where the OS running on each compute server implements active-active link bonding. Each leaf switch is then connected by a pair of links to a pair of spine switches, with an ECMP group defined for the pair of links connecting each leaf to a given spine and for the set of links connecting each leaf to a pair of spines. The cluster as a whole then has multiple connections to external routes, shown via leaf switches 3 and 4 in the Figure. Not shown in Figure 36 is the fact that Trellis runs on top of ONOS, which is itself replicated for the sake of availability. In a configuration like the one shown here, ONOS (and hence the Trellis control applications) are replicated on three to five servers.

_images/Slide31.png

Figure 36. High availability through a combination of dual-homing, link bonding, and ECMP groups.

The use of link aggregation and ECMP is straightforward: the packet forwarding mechanism is augmented to load balance outgoing packets among a group (e.g., a pair) of links (egress ports) rather than having just a single “best” output link (egress port). This both improves bandwidth and results in an automatic recovery mechanism should any single link fail. It is also the case that switch forwarding pipelines have explicit support for port groups, so once equivalences are established, they can be pushed all the way into the data plane.

To be clear, ECMP is a forwarding strategy that Trellis applies uniformly across all the switches in the fabric. The Trellis control application knows the topology, and pushes the port groups into each of the fabric switches accordingly. Each switch then applies these port groups to its forwarding pipeline, which then forwards packets across the set of ports in each group without additional control plane involvement.

Fourth, with respect to scalability, Trellis has demonstrated the ability to support up to 120k routes and 250k flows. This is in a configuration that includes two spine switches and eight leaf switches, the latter implying up to four racks of servers. As with availability, Trellis’s ability to scale performance is directly due to ONOS’s ability to scale.

7.2 Segment Routing

The previous section focused on what Trellis does. This section focuses on how, where the core strategy is based on Segment Routing (SR). The term “segment routing” comes from the idea that the end-to-end path between any pair of hosts can be defined by a sequence of segments, where label-switching is used to traverse a sequence of segments along an end-to-end path. The idea is an application of Multi-Protocol Label Switching (MPLS), which you can read more about here:

Further Reading

Multi-Protocol Label Switching. Computer Networks: A Systems Approach, 2020.

When applied to a leaf-spine fabric, there are always two segments involved—leaf-to-spine and spine-to-leaf—where Tellis programs the switches to match and then push/pop MPLS labels. Figure 37 illustrates how SR works in Trellis using a simple configuration that forwards traffic between a pair of hosts: 10.0.1.1 and 10.0.2.1. In this example, the servers connected to Leaf 1 are on subnet 10.0.1/24, the servers connected to Leaf 2 are on subnet 10.0.2/24, and each of the switches have an assigned MPLS id: 101, 103, 102, and 104.

_images/Slide32.png

Figure 37. Example of Segment Routing being used to forward traffic between a pair of hosts.

When Host 1 sends a packet with destination address 10.0.2.1 it is by default forwarded to the server’s ToR/leaf switch. Leaf 1 matches the destination IP address, learns this packet needs to cross the fabric and emerge at Leaf 2 to reach subnet 10.0.2/24, and so pushes the MPLS label 102 onto the packet. Because of ECMP, Leaf 1 can forward the resulting packet to either spine, at which point that switch matches the MPLS label 102, pops the label off the header, and forwards it to Leaf 2. Finally, Leaf 2 matches the destination IP address and forwards the packet along to Host 2.

What you should take away from this example is that SR is highly stylized. For a given combination of leaf and spine switches, Trellis first assigns all identifiers, with each rack configured to share an IP prefix and be on the same VLAN. Trellis then pre-computes the possible paths and installs the corresponding match/action rules in the underlying switches. The complexity having to do with balancing load across multiple paths is delegated to ECMP, which is similarly unaware of any end-to-end paths. From an implementation perspective, the Trellis control application that implements SR passes these match/action rules to ONOS, which in turn installs them on the underlying switches. Trellis also maintains its own Atomix map to manage the set of ECMP groups connecting leaf and spine switches.

7.3 Routes and Multicast

In addition to Segment Routing, which establies data paths between leaf switches, Trellis also takes advantage of the Route and Mcast services introduced in Chapter 6. They determine which of the leaf-spine switches serve each IP prefix, and where to find all the hosts connected to each multicast group, respectively.

Trellis does not run distributed protocols like OSPF to learn about routes or PIM to construct multicast trees. Instead, it computes the right answers based on global information, and then pushes these mappings to the Route and Mcast services. This is straightforward to do because Trellis imposes the simplifying constraint that each rack corresponds to exactly one IP subnet.

To make this discussion more concrete, consider that all the ONOS Services described in Chapter 6 can be invoked via a RESTful API, or alternatively, through a CLI that is a thin wrapper around REST’s GET, POST and DELETE calls. Using the CLI to illustrate (because it is easier to read), one can query the Route service to learn the existing routes as follows:

onos> routes

B: Best route, R: Resolved route

Table: ipv4
B R  Network            Next Hop        Source (Node)
     0.0.0.0/0          172.16.0.1      FPM (127.0.0.1)
> *  1.1.0.0/18         10.0.1.20       STATIC
> *  10.0.99.0/24       10.0.1.1        FPM (127.0.0.1)
  *  10.0.99.0/24       10.0.6.1        FPM (127.0.0.1)
   Total: 2

Table: ipv6
B R  Network                                     Next Hop                                Source (Node)
> *  2000::7700/120                              fe80::288:ff:fe00:1                     FPM (127.0.0.1)
> *  2000::8800/120                              fe80::288:ff:fe00:2                     FPM (127.0.0.1)
> *  2000::9900/120                              fe80::288:ff:fe00:1                     FPM (127.0.0.1)
  *  2000::9900/120                              fe80::288:ff:fe00:2                     FPM (127.0.0.1)
   Total: 3

Similarly, one can add a static route to the Route Service:

onos> route-add <prefix> <nexthop>
onos> route-add 1.1.0.0/18 10.0.1.20
onos> route-add 2020::101/120 2000::1

One thing to note about these examples is that there are two possible sources for routes. One is that the route is STATIC, which usually means that Trellis inserted it, with full knowledge of the what prefix it has assigned to each rack in the cluster. (Human operators could also add a STATIC route using the CLI, but this would be an exception rather than the rule.)

The second possibility is that FPM was the source. FPM is yet another ONOS Service (one of the Trellis suite of services), and its job is to learn routes from external sources, which it does by tapping into a locally running Quagga process that is configured to peer with BPG neighbors. Whenever FPM learns about an external route, is adds the corresponding prefix-to-nexthop mapping to the Route service, indicating that the destination prefix is reachable via the leaf switches that connect the fabric to upstream networks (e.g., Switches 3 and 4 in Figure 36).

The story with multicast is similar. Again using the ONOS CLI, it is possible to create a new muticast route and add a sink to it. For example:

onos> mcast-host-join -sAddr * -gAddr 224.0.0.1 -srcs 00:AA:00:00:00:01/None -srcs 00:AA:00:00:00:05/None -sinks 00:AA:00:00:00:03/None -sinks 00:CC:00:00:00:01/None

specifies Any-Source Multicast (ASM) (sAddr *), a multicast group address (gAddr), the group source addresses (srcs) and the group sink addresses (sinks). A sink can then be removed as follows:

onos> mcast-sink-delete -sAddr * -gAddr 224.0.0.1 -h  00:AA:00:00:00:03/None

Again, there is no PIM running, but instead, Trellis offers a programmatic inteface for network operators to define a multicast tree through a sequence of such calls. For example, when Trellis runs as part of an access network that delivers IPTV to subscribers, one option is for software running on the operator’s set-top boxes to issue calls similar to the one’s shown above (except, of course, using the RESTful API rather than the CLI). Another option is to have set-top boxes send IGMP messages, which Trellis intercepts using the Packet Service (similar to how the Host service intercepts ARP and DHCP packets). So the next time you use your TV remote to change channels, it is possible you are triggering procedure invocations up and down the SDN software stack described throughout this book!

7.4 Customized Forwarding

Trellis is an example use case for SDN. It is a set of control applications running top of a Network OS, which in turn runs on top of a collection white-box switches arranged in a leaf-spine topology, where each switch runs a local Switch OS. In this way, Trellis serves as a capstone for our bottom-up tour of the SDN software stack.

But if we knew from the outset that a leaf-spine fabric supporting the Trellis feature-set was exactly what we wanted, we might go back to lower layers and tailor them for that purpose. This is what has happened over time with Trellis, resulting in a customized forwarding plane implemented by a P4 program called fabric.p4. We conclude this chapter by giving a high-level summary of fabric.p4, highlighting how its design meshes with the rest of the software stack.

Before doing that, it is important to acknowledge that knowing exactly what you want from a network at the outset is an impossibly high bar. Networks evolve based on experience using and operating them. No one knew how to write fabric.p4 on day one, but after iterating through a series of implementations of the other layers up-and-down the stack (including the introduction of Tofino as a programmable forwarding pipeline), fabric.p4 emerged. The point is that treating the network as a programmable platform frees you to continually and rapidly evolve it.

Said another way, we introduced forward.p4 as our canonical example of “a forwarding plane customized to do exactly what we want” in Chapter 4, but then spent the rest of the chapter describing all the machinery that makes something like forward.p4 possible, without ever revisiting what network-specific functionality it might actually implement. In short, fabric.p4 is a specific example of forward.p4, which we are only now able to describe because of how it relates to the control plane.

There are three things of note about fabric.p4. First, it is loosely based on the Broadcom OF-DPA pipeline, which makes sense because Trellis was originally implemented on top of a set of Tomahawk-based switches. The fabric.p4 pipeline is simpler than OF-DPA, as it eliminates tables that Trellis does not need. This makes fabric.p4 easier to control.

Second, fabric.p4 is designed to mimic ONOS’s FlowObjective API, thereby simplifying the process of mapping FlowObjectives onto P4Runtime operations. This is best illustrated by Figure 38 which shows fabric.p4’s ingress pipeline. The egress pipeline is not shown, but it is a straightforward rewriting of the header fields in the common case.

_images/Slide40.png

Figure 38. Logical pipeline supported by fabric.p4, designed to parallel the Filtering, Forwarding, and Next stages of the FlowObjective API.

Third, fabric.p4 is designed to be configurable, making it possible to selectively include additional functionality. This is not easy when writing code that is optimized for an ASIC-based forwarding pipeline, and in practice it makes heavy use of pre-processor conditionals (i.e., #ifdefs). The code fragment shown below is the main control block of fabric.p4’s ingress function, annotated to highlight optional functionality. The details of the options are beyond to scope of this book, but at a high level:

  • SPGW (Serving and Packet Gateway): Augments IP functionality in support of 4G Mobile Networks.
  • BNG (Broadband Network Gateway): Augments IP functionality in support of Fiber-to-the-Home.
  • INT (Inband Network Telemetry): Adds metric collection and telemetry output directives.
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apply {
#ifdef WITH_SPGW
     spgw_normalizer.apply(hdr.gtpu.isValid(), hdr.gtpu_ipv4, hdr.gtpu_udp,
                           hdr.ipv4, hdr.udp, hdr.inner_ipv4, hdr.inner_udp);
#endif // WITH_SPGW
     pkt_io_ingress.apply(hdr, fabric_metadata, standard_metadata);
     filtering.apply(hdr, fabric_metadata, standard_metadata);
#ifdef WITH_SPGW
     spgw_ingress.apply(hdr.gtpu_ipv4, hdr.gtpu_udp, hdr.gtpu,
                        hdr.ipv4, hdr.udp, fabric_metadata, standard_metadata);
#endif // WITH_SPGW
     if (fabric_metadata.skip_forwarding == _FALSE) {
         forwarding.apply(hdr, fabric_metadata, standard_metadata);
     }
     acl.apply(hdr, fabric_metadata, standard_metadata);
     if (fabric_metadata.skip_next == _FALSE) {
         next.apply(hdr, fabric_metadata, standard_metadata);
#if defined WITH_INT
         process_set_source_sink.apply(hdr, fabric_metadata, standard_metadata);
#endif // WITH_INT
     }
#ifdef WITH_BNG
     bng_ingress.apply(hdr, fabric_metadata, standard_metadata);
#endif // WITH_BNG
}

For example, a companion file, spgw.p4 (not shown), implements the forwarding plane for the SPGW extension, which includes the GTP tunnel encapsulation/decapsulation required by the 3GPP cellular standard to connect the Trellis fabric to the base stations of the Radio Access Network. Similarly, bng.p4 (not shown) implements PPPoE termination, which is used by some Passive Optical Networks deployments to connect the Trellis fabric to home routers. (As an aside, the code fragment also illustrates the basic structure of fabric.p4’s core functionality: lines 6-7 invoke the filtering objective, lines 12-14 invoke the forwarding objective, and lines 16-17 invoke the next objective.)

In addition to selecting which extensions to include, the pre-processor also defines several constants, including the size of each logical table. Clearly, this implementation is a low-level approach to building configurable forwarding pipelines. Designing higher level language constructs for composition, including the ability to dynamically add functions to the pipeline at runtime, is a subject of on-going research.