Chapter 1: Introduction
Software-Defined Networking (SDN) is an approach to how we implement networks, which matters because it impacts the pace of innovation. SDN does not directly address any of the technical challenges of routing, congestion control, traffic engineering, security, mobility, reliability, or real-time communication, but it does open new opportunities to create and deploy innovative solutions to these and similar problems. Exactly how SDN accomplishes this has both business and technical implications, which we discuss throughout this book.
Our approach is to view SDN through a systems lens, which is to say, we explore the collection of design principles that guide the journey to realizing software-defined networks (a journey that is still in progress), rather than to talk about SDN as though it were a point solution. Our approach emphasizes concepts (bringing abstractions to networking is a key part of the original case for SDN), but to keep the discussion concrete, we also draw on our experience implementing a collection of open source platforms over the last six years. These platforms are being used to deliver SDN-based solutions into production networks, including Tier-1 network operators.
This focus on the software stack is a central theme of the book. Because SDN is an approach to building networks, a set of software and hardware artifacts is required to put that approach into practice. The open source examples we draw upon are available on GitHub, with links to both code and hands-on programming exercises available throughout the book.
Before getting into the details, it is helpful to understand the origin story for SDN, which started as an effort by the Computer Science research community to address the ossification of the Internet, opening it up to more rapid innovation. That history is well-documented in an article by Feamster, Rexford, and Zegura.
N. Feamster, J. Rexford, and E. Zegura. The Road to SDN: An Intellectual History of Programmable Networks. SIGCOMM CCR, April 2014.
We add two footnotes to that history. The first is a 2001 National Academy report, which brought the ossification of the Internet into focus as a major challenge. In doing so, the report catalyzed what turned out to be a 20-year R&D effort. The fruits of that research are now directly impacting networks being deployed by Cloud Providers, enterprises, and Internet Service Providers.
Looking Over the Fence at Networks: A Neighbor’s View of Networking Research. The National Academies Press, 2001.
The second is Scott Shenker’s iconic presentation making the intellectual case for SDN. Understanding the central thesis of Shenker’s talk—that the practice of building and operating networks is in dire need of abstractions to help manage complexity—is the linchpin to also understanding the systems, platforms, tools, and interfaces described in this book.
S. Shenker. The Future of Networking and the Past of Protocols. Open Networking Summit, October 2011.
1.1 Market Landscape
To fully appreciate the role and ultimate impact of SDN, it is important to start by looking at the market landscape. SDN was in part conceived as a way to transform the marketplace, inspired by the transformation that the computing industry went through in previous decades.
The computing industry was historically structured as a vertical market. This meant that a customer wanting a solution to some problem (e.g., finance, design, analysis) bought a vertically integrated solution from a single vendor, typically a large mainframe company like IBM. The vertically integrated solution included everything from the underlying hardware (including processor chips), to the operating system running on that hardware, to the application itself.
As shown in Figure 1, the introduction of microprocessors (e.g., Intel x86 and Motorola 68000) and open source OS’s (e.g., BSD Unix and Linux), helped transform that vertical market into a horizontal marketplace, with open interfaces spurring innovation at every level.
SDN, when viewed as a transformative initiative, is an attempt to spur the same sort of changes in the networking industry, which as the 2001 National Academy report observed, had ossified. As shown in Figure 2, the end goal is a horizontal ecosystem with multiple network operating systems enabled on top of bare-metal switches1 built from merchant silicon switching chips, which in turn enable a rich marketplace of networking applications.
The term “bare-metal” originated in the server world to refer to a machine without either an OS or hypervisor installed. By analogy, the term has come to apply to switches provided without a bundled operating system or set of networking applications. Disaggregating the switching hardware from the software is central to SDN.
The value of such a transformation is clear. Opening a vertically integrated, closed, and proprietary market creates opportunities for innovation that would not otherwise be available. Or to put it another way: by opening up these interfaces, it becomes possible to shift control from the vendors that sell networking equipment to the network operators that build networks to meet their users’ needs.
To understand this opportunity in more depth, we need to get into the technical details (which we introduce in the next section), but appreciating the backstory of SDN as a means to transform the networking industry is an important place to start.
1.2 Technical Landscape
With the understanding that SDN is an approach rather than a point solution, it is helpful to define the design principles at the core of that approach. Framing the design space is the goal of this section, but one important takeaway is that there is more than one possible end-state. Each network operator is free to pick different design points, and build out their network accordingly.
That said, this book makes a point of describing the most complete application of SDN principles, which is sometimes called pure play SDN. Given that the whole point of SDN is to disrupt the existing vertical market, it should come as no surprise that incumbent vendors would offer hybrid solutions that align with their established business models and ease adoption. We sometimes call these hybrid solutions SDN-lite because they take advantage of some aspects of SDN, but not the full spectrum. Apart from pointing out the existence of these partial solutions, we do not attempt to be encyclopedic in our coverage of them. Our goal is to chart the full potential of SDN, and do so with as much technical depth as today’s state-of-the-art allows.
1.2.1 Disaggregating the Control and Data Planes
The seminal idea behind SDN is that networks have distinct control and data planes, and the separation of these two planes should be codified in an open interface. In the most basic terms, the control plane determines how the network should behave, while the data plane is responsible for implementing that behavior on individual packets. For example, one job of the control plane is to determine the route packets should follow through the network (perhaps by running a routing protocol like BGP, OSPF, or RIP), and the task of forwarding packets along those routes is the job of the data plane, in which switches making forwarding decisions at each hop on a packet-by-packet basis.
In practice, decoupling the control and data planes manifests in parallel but distinct data structures: the control plane maintains a routing table that includes any auxiliary information needed to select the best route at a given point in time (e.g., including alternative paths, their respective costs, and any policy constraints), while the data plane maintains a forwarding table that is optimized for fast packet processing (e.g., determining that any packet arriving on Port i with destination address D should be transmitted out Port j, optionally with a new destination address D’). The routing table is often called the Routing Information Base (RIB) and the forwarding table is often called the Forwarding Information Base (FIB), as depicted in Figure 3.
There is no controversy about the value of decoupling the network control and data planes. It is a well-established practice in networking, where closed/proprietary routers that predate SDN adopted this level of modularity. But the first principle of SDN is that the interface between the control and data planes should be both well-defined and open. This strong level of modularity is often referred to as disaggregation, and it makes it possible for different parties to be responsible for each plane.
In principle then, disaggregation means that a network operator should be able to purchase their control plane from vendor X and their data plane from vendor Y. Although it did not happen immediately, one natural consequence of disaggregation is that the data plane components (i.e., the switches) become commodity packet forwarding devices—commonly referred to as bare-metal switches—with all the intelligence implemented in software and running in the control plane.2 This is exactly what happened in the computer industry, where microprocessors became commodity. Chapter 4 describes these bare-metal switches in more detail.
By our count, over 15 open-source and proprietary disaggregated control planes are available today.
Disaggregating the control and data planes implies the need for a well-defined forwarding abstraction, that is, a general-purpose way for the control plane to instruct the data plane to forward packets in a particular way. Keeping in mind disaggregation should not restrict how a given switch vendor implements the data plane (e.g., the exact form of its forwarding table or the process by which it forwards packets), this forwarding abstraction should not assume (or favor) one data plane implementation over another.
The original interface supporting disaggregation, called OpenFlow, was introduced in 2008,3 and although it was hugely instrumental in launching the SDN journey, it proved to be only a small part of what defines SDN today. Equating SDN with OpenFlow significantly under-values SDN, but it is an important milestone because it introduced Flow Rules as a simple-but-powerful way to specify forwarding behavior.
OpenFlow was actually not the first effort to do this; it was the one that got the most traction. Earlier efforts included Ipsilon’s GSMP and the ForCES work at the IETF.
A flow rule is a Match-Action pair: Any packet that Matches the
first part of the rule should have the associated Action applied to
it. A simple flow rule, for example, might specify that any packet
with destination address D be forwarded on output port i. The
original OpenFlow spec allowed the header fields shown in
Figure 4 to be included in the Match half of
the rule. So for example, a Match might specify a packet’s MAC header
Type field equals
0x800 (indicating the frame carries and IP
packet) and its IP header
DstAddr field be contained in some
The Actions originally included “forward packet to one or more ports” and “drop packet,” plus a “send packet up to the control plane” escape hatch for any packet that requires further processing by a controller (a term introduced to signify the process running in the control plane responsible for controlling the switch). The set of allowed Actions became more complex over time, which we will return to later.
Building on the flow rule abstraction, each switch then maintains a Flow Table to store the set of flow rules the controller has passed to it. In effect, the flow table is the OpenFlow abstraction for the forwarding table introduced at the beginning of this section. OpenFlow also defined a secure protocol with which flow rules could be passed between the controller and the switch, making it possible to run the controller off-switch. This enabled the configuration shown in Figure 5.
The OpenFlow specification grew more complicated over time (and was certainly defined with much more precision than the previous paragraphs), but the original idea was purposely simple. At the time (2008), the idea of building a switch that included an “OpenFlow option” in addition to its conventional forwarding path was a radical idea, proposed under the pretense of enabling research. In fact, the original OpenFlow publication was written as a call-to-action to the research community.
N. McKeown, et. al. OpenFlow: Enabling Innovation in Campus Networks. SIGCOMM CCR, March 2008.
Today, the OpenFlow specification has been through multiple revisions, and work is underway to replace it with a more flexible (i.e., programmable) alternative. We return to OpenFlow—and P4, the alternative programming language—in Chapter 4.
We conclude this section by calling attention to two related but distinct concepts: Control and Configuration. The idea of OpenFlow (and SDN in general) is to define an interface for controlling the data plane, which implies making real-time decisions about how to respond to link and switch failures, as well as other data plane events. If the data plane reports a failure, the control plane needs to learn about this failure and provide a remedy (e.g., a new Match/Action flow rule) generally within milliseconds.4 Otherwise, the disaggregation implied by SDN would not be viable.
There are also events that require attention in sub-millisecond response times. In such cases it is necessary to implement the remedy in the data plane, and then inform the control plane, giving it the opportunity to re-program the data plane. Fast failover groups are an example of this in OpenFlow.
At the same time, operators are accustomed to configuring their switches and routers. This has historically been done using a Command Line Interface (CLI) or (less commonly) a management protocol like SNMP. Looking back at Figure 3, this corresponds to the northbound interface to the RIB (as opposed to the interface between the RIB and the FIB). This interface is capable of installing new routes, which on the surface seems to be equivalent to installing a new flow rule. Would a switch be considered “SDN-capable” if it merely exposed a programmatic configuration interface in lieu of the conventional CLI?
The answer is likely no, and it comes down to hitting the mark on both generality and performance. While a well-defined programmatic configuration interface is certainly an improvement over legacy CLIs, they are intended for modifying various settings of the control plane (such as RIB entries) and other device parameters (e.g., port speeds/modes) rather than modifying the data plane’s FIB. As a consequence, such configuration interfaces are (a) unlikely to support the full range of programmability implied by a control/data plane interface, and (b) unlikely to support the real-time control loop required by control/data plane disaggregation. In short, the momentum of SDN has had the side-effect of improving the configuration interfaces exposed by switch and router vendors (and we describe the state-of-the-art in such interfaces in Chapter 5), but doing so is not a substitute for the granularity of control SDN requires.
To be clear, all elements in a switch require configuration. The data plane requires configuration of things like port speeds. The platform requires configuration of fans, LEDs, and other peripherals. The on-switch software needs to be informed what certificate it should use when a client connects and what log level should be set. The control plane components also require configuration. For example, the routing agent needs to know its IP address, who its neighbors are, and if it has any static routes. The key distinction is the purpose, but more quantitatively, the rate of updates: configuration implies potentially thousands of updates/day while control implies potentially thousands of updates/sec.
1.2.2 Control Plane: Centralized vs Distributed
Having disaggregated the control and data planes, the next consideration is how to implement the control plane. One option is to run the software that implements the control plane on-switch. Doing so implies each switch operates as an autonomous device, communicating with its peer switches throughout the network to construct a local routing table. Conveniently, there already exists a set of protocols that can be used for this purpose: BGP, OSPF, RIP, and so on. This is exactly the distributed control plane the Internet has employed for the last 30+ years.
There is value in this scenario. Because disaggregation led to the availability of low-cost bare-metal switches built using merchant silicon switching chips, network operators can buy hardware from bare-metal switching vendors, and then load the appropriate control plane software from some other vendor, or possibly even use an open source version of those protocols. Doing so potentially lowers costs and reduces complexity (because only the required control modules need to be loaded onto the device), but it does not necessarily realize the pace of innovation SDN promises. This is because the operator remains stuck in the slow-paced standardization processes implied by today’s standardized protocols. It also fails to deliver the new networking abstractions envisioned by SDN’s pioneers (as in Shenker’s talk noted above, for example).
The alternative, which is the second design principle of SDN, is that the control plane should be fully independent of the data plane and logically centralized. This implies the control plane is implemented off-switch, for example, by running the controller in the cloud. For completeness, we note that it is also possible to adopt a mixed approach, with some control functionality running on-switch and some running off-switch, in a cloud-hosted controller.
We say logically centralized because while the state collected by the controller is maintained in a global data structure (think of this as the centralized counterpart to the per-switch routing table), the implementation of this data structure could still be distributed over multiple servers, as is now the best practice for cloud-hosted, horizontally scalable services. This is important for both scalability and availability, where the key is that the two planes are configured and scaled independent of each other. If you need more capacity in the data plane you add a bare-metal switch. If you need more capacity in the control plane you add a compute server (or more likely, a virtual machine).
Figure 6 depicts the centralized control plane associated with a distributed data plane, but goes a step further by also introducing one of the key components implied by this approach: a Network Operating System (NOS). Like a server operating system (e.g., Linux, iOS, Android, Windows) that provides a set of high-level abstractions that make it easier to implement applications (e.g., users can read and write files instead of directly accessing disk drives), a NOS makes it easier to implement network control functionality, otherwise known as Control Apps.
The idea behind the NOS is to abstract the details of the switches and provide a Network Map abstraction to the application developer. The NOS detects changes in the underlying network (e.g., switches, ports, and links going up-and-down) and the control application simply implements the behavior it wants on this abstract graph. This means the NOS takes on the burden of collecting network state (the hard part of distributed algorithms like Link-State and Distance-Vector routing protocols) and the app is free to simply run the shortest path algorithm on this graph and load the resulting flow rules into the underlying switches. An introduction to Link-State and Distance-Vector routing algorithms is available online.
Routing. Computer Networks: A Systems Approach, 2020.
By centralizing this logic, it becomes possible to do something that wasn’t previously possible in distributed networks: compute globally optimized solutions. As we discuss in later chapters, the published evidence from cloud providers that have embraced this approach confirms this advantage. It was well understood for many years that the fully distributed approach of the Internet did not lend itself to global optimizations, but until SDN, there wasn’t really a feasible alternative. SDN brings this possibility to fruition. This is the power of offering a centralized network abstraction.
The idea of “collecting network state” is central to SDN and the role played by a NOS. We are not talking about collecting the full range of network telemetry data that is used, for example, to troubleshoot misconfigurations or do long-term planning, but we are talking about fine-grain meters that may require an immediate control plane response, an obvious example being the number of bytes/packets sent and received on each port. Protocols like OpenFlow define the means to report such meters to the NOS, in addition to providing the means for the NOS to install new flow rules based on the information it collects.
There is a related benefit of control plane centralization that will become clearer as we get into SDN use cases. A logically centralized control plane provides a single point to expose network APIs. The idea of putting programmatic APIs on individual switches and routers has been around for decades, but failed to make much impact. By contrast, a central API to an entire collection of switches or routers has enabled all sorts of new use cases. These include network virtualization, network automation, and network verification. To take the example of automation, it’s quite hard to automate something like BGP configuration because it so hard to reason about how a set of BGP speakers will respond when they all start talking to each other. But if your central control plane exposes an API in which you can say “create an isolated network that connects the following set of endpoints” then it is quite reasonable to make that request part of an automated configuration system. This is precisely what happens in many modern clouds, where the provisioning of network resources and policies is automated along with all sort of other operations such as spinning up virtual machines or containers.
Returning to the original question of centralized versus distributed control plane, proponents of the latter often base their rationale on the historical reasons the Internet adopted distributed routing protocols in the first place: scale, and survival in the face of failures. The concern is that any centralized solution results in a bottleneck that is also a single point-of-failure. Distributing the centralized control plane over a cluster of servers mitigates both these concerns, as techniques developed in the distributed systems world can ensure both high availability and scalability of such clusters.
A secondary concern raised about control plane centralization is that, since the control plane is remote (i.e., off-switch), the link between the two planes adds a vulnerable attack surface. The counter-argument is that non-SDN networks already have (and depend on) out-of-band management networks, so this attack surface is not a new one. These management networks can be used by off-switch controllers just as readily as by other management software. There is also the argument that a small number of centralized controllers can present a smaller attack surface than a large number of distributed controllers. Suffice it to say, opinions differ, but there is certainly a wealth of support for the centralized approach.
1.2.3 Data Plane: Programmable vs Fixed-Function
The final dimension of the design space is whether the switches that implement the data plane are programmable or fixed-function. To appreciate what this means, we need to say a little more about how switches are implemented.
The preceding discussion has implied a simple model of a switch, in which the switch’s main processing loop receives a packet from an input port, does a lookup of the destination address in the FIB (or using OpenFlow terminology, in the flow table), and puts the packet on the output port or port group indicated by the matched table entry. This is a reasonable implementation strategy for low-end switches (i.e., the main processing loop is implemented in software on a general-purpose processor), but high-performance switches employ a hardware-based forwarding pipeline.
We postpone an in-depth description of these pipelines until Chapter 4, but the important characteristic for now is whether that pipeline is limited to matching a fixed set of fields in the packet headers (e.g., the fields shown in Figure 4) and perform a fixed set of actions, or if the bit-patterns to be matched and the actions to be executed are dynamically programmed into the switch. The former are referred to as fixed-function pipelines and the latter as programmable pipelines. But first we have to answer the question: “What exactly is a forwarding pipeline?”
One way to think about a forwarding pipeline is that instead of a single flow table, as suggested in the previous section, switches actually implement a series of flow tables, each focused on a subset of the header fields that might be involved in a given flow rule (e.g., one table matches the MAC header, one matches the IP header, and so on). A given packet is processed by multiple flow tables in sequence—i.e., a pipeline—to determine how it is ultimately forwarded. Figure 7 gives a generic schematic for such a pipeline of flow tables, based on a diagram in the OpenFlow specification. The idea is that a set of actions are accumulated as the packet flows through the pipeline, and executed as a set in the last stage.
At first glance this might not seem to be important since header fields like those shown in Figure 4 are both well-known and at easy-to-compute offsets in every packet a switch has to forward (e.g., Table 0 tries to match the MAC header fields, Table 1 tries to match the IP fields, and so on). And to this point, the initial idea of SDN was purposely data plane agnostic—SDN was entirely focused on opening the control plane to programmability. But early experience implementing SDN controllers exposed two problems.
The first problem was that as SDN matured from a research experiment to a viable alternative to legacy, proprietary switches, performance became increasingly important. And while flow rules were general enough to say what forwarding behavior the controller wanted to program into a switch, switches didn’t necessarily have the capacity to implement that functionality in an efficient way. To ensure high forwarding performance, flow tables were implemented using highly optimized data structures that required specialized memories, like Ternary Content Addressable Memory (TCAM). As a consequence, they supported only a limited number of entries, which meant the controller had to be careful about how they were used.
In short, it proved necessary for the controller to know details about the pipeline in order to install a set of flow rules that the switch could map to hardware. As a consequence, many control applications were implicitly tied to a particular forwarding pipeline. This would be analogous to writing a Java or Python program that can only run on an x86 processor and is not easily ported to an ARM processor. It proved necessary to have more control over the forwarding pipeline, and because we don’t want to limit ourselves to a single vendor’s pipeline, we also need an abstract way to specify a pipeline’s behavior, that can in turn be mapped onto the physical pipeline of any given switch.
The second problem was that the protocol stack changed in unexpected ways, meaning that the assumption that all header fields you might need to match against are well-known is flawed. For example, while OpenFlow (and early forwarding pipelines) correctly include support for VLAN tags, a cornerstone for creating virtual networks in enterprise networks, the 4096 possible VLANs was not sufficient to account for all the tenants that a cloud might host.
To address this problem, the IETF introduced a new encapsulation, called Virtual Extensible LAN (VXLAN). Unlike the original approach, which encapsulated a virtualized ethernet frame inside another ethernet frame, VXLAN encapsulates a virtual ethernet frame inside a UDP packet. Figure 8 shows the VXLAN header, along with all the packet headers a switch might have to process to make a forwarding decision.
Adding support for VXLAN to OpenFlow is hard enough since agreeing to standards takes time, but adding support for VXLAN to fixed-function forwarding pipelines is an even more time-consuming endeavor: Hardware needs to change! One could argue that with VXLAN we are now done changing the protocol stack, but that’s unlikely. For example, QUIC is gaining momentum as an alternative to TCP when used with HTTP. Another example on the horizon is MPLS vs SRv6. Even VXLAN is now being superseded in some settings by a new, more flexible encapsulation called GENEVE.
Programmable forwarding pipelines, coupled with a high-level language that can be used to program the pipeline, is one viable response to these two issues. Both have emerged in the last few years, in the form of a Protocol Independent Switching Architecture (PISA) and the P4 programming language. We will discuss both in more detail in Chapter 4, but the big takeaway for now is that SDN has evolved beyond its original goal as a means to program the control plane. Today, SDN also includes the possibility of a programmable data plane.
1.3 SDN: A Definition
To summarize, the original definition of SDN is simple to state:
A network in which the control plane is physically separate from the forwarding plane, and a single control plane controls several forwarding devices.5
This is a succinct way of saying what Sections 1.2.1 and 1.2.2 explain in long-form. Since that original definition, SDN has been interpreted by different stakeholders to mean both less (e.g., a programmatic configuration interface to network devices qualifies as SDN) and more (e.g., SDN also includes switches with programmable forwarding pipelines). This book covers the full spectrum by taking the more expansive view.
From Nick McKeown’s 2013 presentation entitled Software Defined Networking.
Another way to frame SDN is to think of it as having two phases. In Phase 1, network operators took ownership of the control plane, and now in Phase 2, they are taking control of how packets are processed in the data plane. Phase 2 is still a work-in-progress, but as Nick McKeown posits, the aspirational end state is one in which:
“Networks will [hopefully] be programmed by many, and operated by few.”
Which is to say, SDN is not just about shifting control from vendors to operators, but ultimately, it is about shifting control from vendors to operators to users. That’s the long-term goal, inspired by what commodity servers and open source software did for the computing industry. But we still have a ways to go, so we return to more modest predictions about the next phase of the SDN journey in Chapter 10.
N. McKeown. The Network will be programmed by many, operated by a few. March 2021.