MultiPath TCP (MPTCP) is an effort towards enabling the simultaneous use of several IP-addresses/interfaces by a modification of TCP that presents a regular TCP interface to applications, while in fact spreading data across several subflows. Benefits of this include better resource utilization, better throughput and smoother reaction to failures.

You can learn more about M-TCP here and here.

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According to the recent SONAR report, 52% of respondents reported they are using Software Defined Networking (SDN) tools to automate their networks, while 57% reported they are using network management tools. The report notes “52% may be slightly exaggerated, depending on how one defines SDN…” Which leads naturally to the question—what the difference between SDN and DevOps is, and how does AI figure into both or either of these.  SDN, DevOps, and AI describe separate and overlapping movements in the design, deployment, and management of networks. While they are easy to confuse, they have three different origins and meanings.

Software Defined Networking grew out of research efforts to build and deploy experimental control planes, either distributed or centralized. SDN, however, quickly became associated with replacing some or all the functions of a distributed control plane with a centralized controller, particularly in order to centralize policy related to the control plane such as traffic engineering. SDN solutions always work through a programmatic interface designed to primarily supply forwarding information to network devices.

Development Operations, or DevOps, is a movement away from human-centered interfaces towards machine-centered interfaces for the deployment, operation, and troubleshooting of networks. DevOps is centered on the deployment, configuration, and management of the entire device, rather than providing the information required to forward traffic. DevOps can either use a programmatic interface, such as YANG, or “screen scraping,” to configure and manage network devices.

Finally, Artificial Intelligence, or AI, in the context of computer networks, is focused on the use of data gathered from the network to improve operations, from decreasing the time required to troubleshoot a problem to making the network adapt more quickly to shifting application and business requirements. AI, applied to networks, is narrow in scope, so it is Artificial Narrow Intelligence, or ANI. Real implementations of AI in the networking field are often applications of Machine Learning, or ML; while these two terms are often used interchangeably, they are not quite the same thing.

The following illustration will be useful in understanding the relationship between these three concepts.

 

In the figure, the SDN and DevOps controllers interact with two different aspects of the network devices forwarding traffic; both SDN and DevOps can be deployed in the same network to solve different problems. For instance, DevOps might be used to configure network devices to reach the SDN controller so they can receive the information they need to forward packets. Or the DevOps system might be used to configure a distributed control plane, such as IS-IS, on all the network devices, and also to configure a centralized controller which can override the local decisions of the distribute routing protocol for traffic engineering.

There are some situations where the difference between SDN and DevOps solutions is not obvious. The most common example is DevOps could be used to configure routing information on each network device, performing the same function as an SDN controller. In this case, what is the difference?

First, an SDN solution is intended specifically to replace the distributed control plane, rather than to configure the entire device. Second, the configurations pushed to a device through DevOps is normally persistent; if a device reboots, the configuration pushed through DevOps will be loaded and enabled, impacting the operation of the device. In contrast, any information pushed to a device through an SDN controller would normally be ephemeral; when the device is rebooted, information pushed by the SDN controller will be lost.

Finally, AI and self-healing are shown on the right side of this diagram as a way to turn telemetry into actionable input for either the DevOps or the SDN system. The ability of ML networks to find and recognize patterns in streams of data means it is perfectly suited to find new patterns of network behavior and alert an operator, or to match current conditions to the past, anticipating future failures or finding an otherwise unnoticed problem.

While SDN, DevOps, and AI overlap, then, they serve different purposes in the realm of network engineering and operations. There are many areas of overlap, but they are also different enough to argue the three terms should be cleanly separated, with each adding a different kind of value to the overall system.


The Transmission Control Protocol, or TCP, is one of the foundational technologies of packet switched networks. TCP not only provides windowed flow control, it also manages the retransmission of data when errors are detected, and sockets for addressing individual applications on a host. Doug Comer was involved in the early development of TCP/IP.

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Dr. Comer’s book on networking technologies is a classic in the field.

We all use the OSI model to describe the way networks work. I have, in fact, included it in just about every presentation, and every book I have written, someplace in the fundamentals of networking. But if you have every looked at the OSI model and had to scratch your head trying to figure out how it really fits with the networks we operate today, or what the OSI model is telling you in terms of troubleshooting, design, or operation—you are not alone. Lots of people have scratched their heads about the OSI model, trying to understand how it fits with modern networking. There is a reason this is so difficult to figure out.

The OSI Model does not accurately describe networks.

What set me off in this particular direction this week is an article over at Errata Security:

The OSI Model was created by international standards organization for an alternative internet that was too complicated to ever work, and which never worked, and which never came to pass. Sure, when they created the OSI Model, the Internet layered model already existed, so they made sure to include today’s Internet as part of their model. But the focus and intent of the OSI’s efforts was on dumb networking concepts that worked differently from the Internet.

This is partly true, and yet a bit … over the top. 🙂 OTOH, the point is well taken: the OSI model is not an ideal model for understanding networks. Maybe a bit of analysis would be helpful in understanding why.

First, while the OSI model was developed with packet switching networks in mind, the general idea was to come as close as possible to emulating the circuit-switched networks widely deployed at the time. A lot of thought had gone into making those circuit-switched networks work, and applications had been built around the way they worked. Applications and circuit-switched networks formed a sort of symbiotic relationship, just as applications form with packet-switched networks today; it was unimaginable, at the time, that “everything would change.”

So while the designers of the OSI model understood the basic value of the packet-switched network, they also understood the value of the circuit-switched network, and tried to find a way to solve both sets of problems in the same network. Experience has shown it is possible to build a somewhat close-to-circuit switched network on top of packet switched networks, but not quite in the way, nor as close to perfect emulation, as those original designers thought. So the OSI model is a bit complex and perhaps overspecified, making it less-than-useful today.

Second, the OSI model largely ignored the role of middleboxes, focusing instead on the stacks implemented and deployed in hosts. This, again, makes sense, as there was no such thing as a device specialized in the switching of packets at the time. Hosts took packets in and processed them. Some packets were sent along to other hosts, other packets were consumed locally. Think PDP-11 with some rough code, rather than even an early Cisco CGS.

Third, the OSI model focuses on what each layer does from the perspective of an application, rather than focusing on what is being done to the data in order to transmit it. The OSI model is built “top down,” rather than “bottom up,” in other words. While this might be really useful if you are an application developer, it is not so useful if you are a network engineer.

So—what should we say about the OSI model?

It was much more useful at some point in the past, when networking was really just “something a host did,” rather than its own sort of sub-field, with specialized protocols, techniques, and designs. It was a very good attempt at sorting out what a network needed to do to move traffic, from the perspective of an application.

What it is not, however, is really all that useful for network engineers working within an engineering specialty to understand how to design protocols, and how to design networks on which those protocols will run. What should we replace it with? I would begin by pointing you to the RINA model, which I think is a better place to start. I’ve written a bit about the RINA model, and used the RINA model as one of the foundational pieces of Computer Networking Problems and Solutions.

Since writing that, however, I have been thinking further about this problem. Over the next six months or so, I plan to build a course around this question. For the moment, I don’t want to spoil the fun, or put any half-backed thoughts out there in the wild.

When a recursive resolver receives a query from a host, it will first consult any local cache to discover if it has the information required to resolve the query. If it does not, it will begin with the rightmost section of the domain name, the Top Level Domain (TLD), moving left through each section of the Fully Qualified Domain Name (FQDN), in order to find an IP address to return to the host, as shown in the diagram below.

This is pretty simple at its most basic level, of course—virtually every network engineer in the world understands this process (and if you don’t, you should enroll in my How the Internet Really Works webinar the next time it is offered!). The question almost no-one ever asks, however, is: what, precisely, is the recursive server sending to the root, TLD, and authoritative servers?

Begin with the perspective of a coder who is developing the code for that recursive server. You receive a query from a host, you have the code check the local cache, and you find there is no matching information available locally. This means you need to send a query out to some other server to determine the correct IP address to return to the host. You could keep a copy of the query from the host in your local cache and build a new query to send to the root server.

Remember, however, that local server resources may be scarce; recursive servers must be optimized to process very high query rates very quickly. Much of the user’s perception of network performance is actually tied to DNS performance. A second option is you could save local memory and processing power by sending the entire query, as you have received it, on to the root server. This way, you do not need to build a new query packet to send to the root server.

Consider this process, however, in the case of a query for a local, internal resource you would rather not let the world know exists. The recursive server, by sending the entire query to the root server, is also sending information about the internal DNS structure and potential internal server names to the external root server. As the FQDN is resolved (or not), this same information is sent to the TLD and authoritative servers, as well.

There is something else contained here, however, that is not so obvious—the IP address of the requestor is contained in that original query, as well. Not only is your internal namespace leaking, your internal IP addresses are leaking, as well.

This is not only a massive security hole for your organization, it also exposes information from individual users on the global ‘net.

There are several things that can be done to resolve this problem. Organizationally, running a private DNS server, hard coding resolving servers for internal domains, and using internal domains that are not part of the existing TLD infrastructure, can go a long way towards preventing information leaking of this kind through DNS. Operating a DNS server internally might not be ideal, of course, although DNS services are integrated into a lot of other directory services used in operational networks. If you are using a local DNS server, it is important to remember to configure DHCP and/or IPv6 ND to send the correct, internal, DNS server address, rather than an external address. It is also important to either block or redirect DNS queries sent to public servers by hosts using hard-coded DNS server configurations.

A second line of defense is through DNS query minimization. Described in RFC7816, query minimization argues recursive servers should use QNAME queries to only ask about the one relevant part of the FQDN. For instance, if the recursive server receives a query for www.banana.example, the server should request information about .example from the root server, banana.example from the TLD, and send the full requested domain name only to the authoritative server. This way, the full search is not exposed to the intermediate servers, protecting user information.

Some recursive server implementations already support QNAME queries. If you are running a server for internal use, you should ensure the server you are using supports DNS query minimization. If you are directing your personal computer or device to publicly reachable recursive servers, you should investigate whether these servers support DNS query minimization.

Even with DNS query minimization, your recursive server still knows a lot about what you ask for—the topic of discussion on a forthcoming episode of the Hedge, where our guest will be Geoff Huston.