Category Archives: SDN

SDN with Big Data Analytics for an Intelligent Network

Software, cloud computing and IOT are rapidly transforming networks in a way, and at a rate, never seen before. With software-as-a-service (SaaS) models, enterprises are moving more and more of their critical applications and data to public and hybrid clouds. Enterprise traffic, that never left the corporate network, is now shifting to the Internet, reaching out to different data centers across the globe. Streaming Video (Netflix, Youtube, Hulu, Amazon) accounts for an absurdly high percentage of traffic in the Internet and content providers have built out vast content distribution networks (CDNs) that overlay the Internet backbone. Higher resolutions (HD and UHD) will increase the traffic further, and by some accounts, will be over 80% of the total network traffic by 2020. More and more businesses are being created that reach their customers exclusively over the Internet (Spotify, Amazon, Safari, Zomato, etc). Real-time voice and video communications are moving to cloud-based delivery and network operators are challenged to deliver these services without impacting user quality of experience. And if this was’nt enough, with the advances being made in IOT, we have more devices than ever, lively communicating and chatting in real time over the Internet.

Security becomes a prime concern as more business critical applications migrate to the cloud. The number of DDOS attacks are only increasing and IOT devices can be compromised by hackers to launch some very lively and innovative attacks. A large scale cyber attack in 2016 used a botnet consisting of a multitude of IoT devices such as printers, camera, web cams, residential network gateways, and even baby monitors causing a major outage that brought down a big chunk of the Internet.

All this traffic goes over service provider networks that were built and designed using devices, protocols and management software from the Jurassic age. The spectacular growth and variability of traffic that is experienced today was not anticipated when these networks were built. There is a dire need to cope with changing traffic patterns and to optimize the use of available network resources at all levels (IP, MPLS and Optical) — we’ll talk about the multi-layer SDN controller that optimizes the IP-Optical layers some other time.

Given these challenges, its imperative that service providers work towards gaining realtime visibility into the network behavior and extract actionable insights needed to react immediately to network anomalies, changing traffic patterns and security threats and alarms.

And this is where big data analytics, like a knight in the shining armour, comes in.

Given the data rates that we are dealing with, and the rate at which traffic volumes and speeds are growing, deep packet inspection at line rate gets ruled out in most parts of the network. There is only so much that one can do with hardware’s brute force approach. Additionally, with most traffic being encrypted, DPI offers limited — no, zero — insight into whats happening in the network.

What can help at the scale that networks run today is streaming telemetry combined with big data analytics. Instead of constantly polling the devices in the network and then reacting to what is learnt, the new age mantra is for these devices to periodically push the relevant statistics to the data collectors, which can analyse this data and act based on that. One can argue that streaming network telemetry may not even require an IETF standard in order to be useful. A standard format like JSON could be used, and it’s up to the collector to parse and interpret the incoming barrage of data. This allows network operators to quickly write dev-ops tools that they can use to closely monitor their network and services. This opens up room for hyper innovation where new-age startups can quickly come up with products that can smartly mine the data from the network and draw rich insights into whats happening that can help the service providers in running their networks smarter and hotter.

Big data analytics entails ingesting, processing and storing exabytes worth of network data over a period of time that can be analysed later for actionable insights. With advances made in streaming analytics, this analysis can also happen in real time as the data comes piping hot from the network. New age scalable stream processors make it possible to fuse data streams to answer more sophisticated queries about the network in real-time.

By correlating data from sources beyond traditional routing and networking equipment (IX router-server views, DNS and CDN logs, firewall logs, billing and call detail records) it is possible for the analytics engine to identify patterns or behaviors that can not be identified by merely sifting through the device logs (collected traditionally using SNMP, syslogs, netflow, sflow, IPFIX, etc). The ability to correlate telemetry data from the network with applications such as Netflix or Youtube or SaaS applications such as an iOS upgrade can provide insights that can never be found with traditional traffic engineering approaches.

I claim that we now have the smarts to avoid the famous iOS7 meltdown that happened when iOS7 was released. Let’s see how:

The analytics engine feeding the controller can identify and correlate iOS updates to a new spike — an anomaly — in the network utilization inside an enterprise. The SDN controller can install more specific flows that will steer all iOS update traffic on a different path in the network. This way the controller can automatically adjust the enterprise customer flows to either (i) provide an improved iOS update experience OR (ii) prevent other enterprise traffic to get affected with the iOS update tsunami.  Advanced IP controllers (and those are being demo’ed to several service providers currently) can steer such traffic across multiple ASes as well.

We recently demo’ed a hierarchical SDN controller to a very big customer in Europe. The SDN controller was used to set up inter-domain IP/MPLS services and it used telemetry feeds to determine the realtime link utilization of the inter-domain links. We used that information to place the inter-domain IP services across multiple ASes — the new services were placed on the least utilized inter-domain link at that instance. The services could be moved around as the link utilization changed. This is very different from how its done today, where the BW utilization is reserved and services are placed based on the hard reservations. IMO, the concept of hard reservations will get obsoleted very soon. Why assume that a VPLS service on a link will take up 1Gbps, when the traffic that it “historically” sends never exceeds 100 Mbps?

The figure below shows the different sources feeding into a typical big data analytics cluster that feeds the output to the SDN controller.

Flow telemetry and network telemetry will help in monitoring the traffic flowing inside the service provider networks. We could use this to gain a deep understanding of what a network looks like during normal operations and how it looks like when an anomaly is present in the network.

If one understands the “normal”, the abnormal can become apparent. What comprises abnormal may vary from network to network and from attack to attack. It could include large traffic spikes from a single source in the network, higher-than-typical traffic “bursts” from several or many devices in the network, or traffic types detected that are not normally sent from a known device type. Once the abnormal has been identified, the attacks can be controlled and eliminated.

Network telemetry will also help in peering analytics to select the most cost-effective peering and transit connections based on current and historic traffic trends. Correlating this data with BGP feeds from route servers can help in visualizing how the traffic flows/shifts from one AS to the other.

Data collected from different sources is fed to a scalable publish/subscribe pipeline that feeds this to the big data analytics platform. Some of this can be fed to a real time streaming analytics platform for deriving rich real time insights from the network. This can then be fed to a machine learning cluster for predictive analytics.

The data is stored in a scalable data lake which can be optimized for complex, multi-dimensional queries that becomes the building block for the SDN controller to do something useful. This data can be coupled with the other data that is being learnt off different sources (syslog records, DNS and CDN logs, IX views, etc) and all this can be processed and transformed into actionable intelligence. For example, this can help service providers understand the amount of Facebook, Netflix, Youtube and Amazon Prime Video traffic thats flowing in their networks. It can help them construct a “heat map” of the most active sources and the sinks. Combine this with anonymized subscriber demographics, and the big data analytics framework can provide high fidelity insights into how the subscribers, applications and the network are correlated.

This level of insight cannot be derived by merely observing the telemetry feeds alone since it is not straightforward to correlate flows with specific applications, services and subscriber end points. The ability to mine data from a panoply of sources (as shown on the left side of the figure above — DNS servers, repositories that can identify servers and end points by owner, geo-location, type and purpose) and being able to correlate them is what differentiates the new age intelligent networks from the ones that exist today.

This level of sophistication can not be achieved without a solid big data analytics framework supporting the SDN controller. The limitless potential of what can be achieved will only unfold as more real deployments start happening in the next few years. We’re living in very interesting times, and I’m waiting with bated breath to see what the future holds and how the networking industry becomes “great again”!

Advertisements

Software defined WAN (SD-WAN) is really about Intelligence ..

Lets admit that most of us in the networking domain know as much about SD-WAN as an average 6th grader on sex — which is to say pretty much nothing. We take it as something much grander and exotic than what it really is and are obviously surrounded by friends and well-wishers who wink conspiratorially that they “know it all” and consider themselves on an intellectual high ground to educate us on matters of this rich and riveting biological social interaction. Like most others in that tender and impressionable age, i did get swayed by what i heard and its only later that i was able to sort things out in my head, till it all became somewhat clear.

The proverbial clock’s wound backwards and i experience that feeling of deja-vu each time i read an article on SD-WAN that either extols its virtues or vilifies it as something that has always existed and is being speciously served on a platter dressed up as something that it is not. And like the big boys then, there are men who-know-it-all, who have already written SD-WAN off as something that has always existed and really presents nothing new here. Clearly, i disagree with that view.

I presume, perhaps a trifle rashly, that you are already aware of basic concepts of SDN and NFV (and this) and hence wouldnt waste any more oxygen explaining those.

So what really is the SD-WAN technology and the precise problem that its trying to solve?

SD-WAN is a way of architecting, designing and deploying enterprise WANs using commodity Internet connections in a manner that makes those “magically” appear as a private “MPLS-like” connection. Its the claim that it can appear “MPLS-like” that really peeves the regular-big-mpls-vendors-and-consultants. I will delve into the “MPLS-like” aspect a little later, so please hold on to your sabers till then. What makes the “magic” work is the control plane that implements and enforces the network access policies (VOIP is high priority/low latency/low jitter, big data sync medium priority and all else low priority, no VOIP via Afghanistan, etc) and the data plane that weaves an L2/L3 overlay on top of the existing consumer-grade Internet links (broadband links and in a few cases the LTE/4G connections).

The SD-WAN evangelists want to wean enterprises off their dedicated prohibitively priced private WAN connections (read MPLS circuits) with commodity enterprise broadband links. Philosophically, adding a new branch should just mean shipping a CPE device (perhaps in a virtualized form-factor) that auto-magically dials into a central controller when brought to life. Once thats done and the credentials verified, the branch should just come online (viola!) and should be visible to all the geo-separated branches. Contrast this with the provisioning time (can go as high as a year in some remote locations) and the complexity it takes to get a remote branch online today with MPLS and you will understand why most IT folks have ulcers and are perennially on anti-anxiety/depressant medicines. And btw we’ve not even begun talking about the expenses and long term contracts with the MPLS connections here!

Typically SD-WAN solutions have a central SDN controller which is really a cluster of x86 devices (servers, VMs, containers, take your pick) and hence has computing and analytical horsepower much more than a dedicated HW network device. The controller has complete visibility right from the source all the way till the destination and can constantly analyze traffic and can carve out optimal network paths for applications and individual flows based on the user and application policies. In the first mile the Internet links are either coalesced to form a fatter pipe or are used separately as dictated by the customer policies. The customer traffic is continuously finger-printed and is routed dynamically based on the real time network conditions.

Where most people go wrong is when they believe that SD-WAN solutions lose control over the traffic once it leaves the customer premises or the SD-WAN edge node. Bear in mind that there is nothing in the SD-WAN technology that prevents further control over how the traffic is routed and this could perhaps be one aspect differentiating one SD-WAN offering from the other. Since SD-WAN is an overlay technology you will not have control over each physical hop, but you can surely do something more nuanced given the application and end-to-end network visibility that exists with the controller.

MPLS and SD-WAN !

Its “MPLS-like” in the sense that you can, in most cases, guarantee the available bandwidth and network up time. The central controller can monitor each overlay circuit for loss/jitter/delay and can take corrective actions when routing traffic. Patently enterprise broadband connections in certain geographies dont come with the same level of reliability as MPLS and it behooves upon us to ask ourselves if we need that level of reliability (given the cost that we pay for such connections). An enterprise can always hedge its risks by commissioning a few backup enterprise broadband connections for those rainy days when the primary is out cold. Alternatively, enterprises can go in for a hybrid approach where they maintain a low bandwidth MPLS connection for their mission-critical traffic and use the SD-WAN solution for everything else OR can implement a policy to revert to the MPLS connection when the Internet connections are not working satisfactorily. This can also provide a plausible transition strategy to the enterprises who may not be comfortable switching to SD-WANs given that the technology is still relatively new.

And do note that even MPLS connections go down, so its really not fair to say that SD-WAN solutions stand on tenuous grounds with regard to the reliability. Yes i concede that there are SLAs given with MPLS that just dont exist with regular Internet pipes. However,  one could argue that you can get some bit of extra reliability by throwing in an additional Internet link (with a different provider?) thats only there as a standby. Also note that with service providers now giving fiber connections, the size and the quality of Internet links is only going to improve with time. A large site for instance can aggregate a 1Gbps Google Fiber and a 1Gbps Verizon FIOS connection and can retain a small MPLS connection as the standby. If the enterprise discovers that its MPLS connection is underutilized it can negotiate on pricing or can go with lower MPLS pipe and thereby save on its costs.

I recently read a blog which argued that enterprise broadband promising 350Mbps would mostly give only around 320Mbps on an average. Sure this might be true in a few geographies, but seriously, who cares? Given the cost difference between a broadband connection and an MPLS circuit i will gladly assume that i only had a 300Mbps connection and derive utmost pleasure any time it gives me anything more than that!

The central controller in the SD-WAN technologies amongst other things (analyzing traffic, links) can also continually learn about the customer network conditions and can predict when link qualities will deteriorate and can preemptively reroute traffic before the links start acting up. Given that the controller is monitoring paths end-to-end and is also monitoring and analyzing the traffic emanating from the branch sites there are insights that enterprises can draw that they could have never imagined when using traditional WAN architectures since in that world all connections are really only “dumb pipes”. SD-WAN changes all that — it changes how the enterprise connections and the applications running there are viewed. The WAN architecture is aligned to the application service requirements and its management is greatly simplified. You can implement complex network policies and let the SD-WAN infrastructure sweat on your behalf (HINT: intent driven networking).

So watch out before you disdainfully write off SD-WAN as a technology thats merely replacing your dumb MPLS pipes with the regular Internet connections, since i argue, it can really do a lot more than that. Perhaps a topic worth discussing some other day.


NFV – CPE vendors MUST evolve!

Customer Premises Equipment (CPE) devices have always been a pain point for the service providers. One, they need to be installed in large large numbers (surely you remember the truck rolls that need to be sent out), and second, and more importantly, they get complex and costlier with time. As services and technology evolve, these need to be replaced with something more uglier and meaner than what existed before. In a large network, managing all the CPEs — right from the configuration, activation, monitoring, upgrading and efficiently adding more services – in itself becomes a full time job (and not the one with utmost satisfaction i must add).

Hate CPEs

ETSI’s Use case #2 describes how the CPE device can be virtualized. The idea is to replace the physical CPEs with all the services it supports on an industry standard server that is and cheaper and easier to manage. Doing this can reduce the number and complexity of the CPE devices that need to be installed at the customer sites.

The jury is still out on the specific functions that can be moved out of the CPE. Clearly, what everybody agrees to is a need for a device that will physically connect the customer to the network. There will hence always be a device at the customer premises. If we can virtualize most of the things that a CPE does, then this device could be a plain L2 switch that takes packets from the customers and pushes those towards the network side.

So what do we gain by CPE virtualization?

You reduce the number of devices deployed at customer premises. Most enterprise customers when adding new services add more devices beyond the access point/demarcation device or NID. If the functions serviced by those devices can be virtualized, then you dont need to add those extra devices.

In residential markets, we can completely remove the set-top boxes (including storage for video recorders) and the layer 3 functions provided by home gateways as these functions can be virtualized (on standard servers driven by highly scalable cloud-based software) , leaving each home with a plain L2 switch. This apparently is already underway as we speak.

Since each site has a vanilla L2 switch, you dont need to replace it till its potent enough to handle the incoming traffic onslaught. Since all the intelligence resides in the standard server, it can easily be replaced/upgraded without involving the dreaded truck rolls.

Truck rolls

Your engineers dont have to visit customer premises for upgrades. Since most of the services are hosted over the cloud, all upgrades happen at the hosting location or the data center. Even if the virtualized services are deployed at the customer premises, you dont have to upgrade each CPE device. Its only the server at the customer premises that needs an upgrade.

Newer services and applications can be easily introduced, since those can be tested out at the hosting location or the data center. You dont have to worry about trying it out on all the different CPE devices. Barrier to entry in the network has suddenly lowered since the legacy CPE equipment doesnt need to be replaced. Also helps avoid vendor lock-in if all CPE devices are plain L2 switches and all the “work” is being done in SW on the standard servers.

Scaling up becomes less of a headache. BGP routers, as they start scaling, run out of control plane memory much before they hit the data plane limits. If the control plane has been virtualized, then its much easier to address this problem vis-a-vis when BGP is running on physical routers.

There are several vendors pushing for CPE virtualization. If you’re a CPE vendor who believes that your services are far too complex to be virtualized, then beware that things are moving very fast in the NFV space. I had earlier posted about how virtual routers can replace the existing harware here. Its fairly easy to imagine CPEs going virtual — from being high end devices to easily commoditized L2 switches! So if you dont evolve fast, then you run the risk of getting extinct!


NFV: Will vRouters ever replace hardware routers?


When i started looking at NFV, i always imagined it being relegated to places in the network that would receive only teeny weeny amount of data traffic since the commodity hardware and software could only handle so much of traffic. I also naively believed that it would be deployed in networks where customers were not uber-sensitive to latency and delay (broadband customers, etc). So if somebody really wanted a loud bang for their buck they had to use specialized hardware to support the network function. You couldnt really use Intel x86-based servers running SW serving customers for whom QoS and QoE were critical and vital. The two examples that leap to my mind are (i) Evolved Packet Core (EPC) functions such as Mobility Management Entity (MME) and BNG environments where the users need to be authorized before they can expect to receive any meaningful services.

While i understood that servers were getting powerful and Intel was doing its bit with its Data Plane Development Kit (DPDK) architecture, it didnt occur to me till recently that we would be seeing servers handling traffic at 10G+ line rate. Vyatta, a Brocade company now, uses vRouters to implement real network functions. Vyatta started with its modest 5400 vRouter that could only handle 1G worth of traffic at the line rate. But then last year it announced 5600 vRouter  that takes advantage of Intel multi-core and DPDK architecture to achieve 10x+ performance. Essentially how DPDK drastically improves the performance is by directly passing the packets from the line card to the code running in the userspace by completely bypassing the high-latency DRAM processing thus speeding up the packet processing. It also supports amongst other things, lockless FIFO implementation  for packet enqueue/dequeue as semaphores and spinlocks are expensive.

The Vyatta 5600 vRouter can be installed on pretty much any x86 based server and can support number of network functions such as dynamic routing, policy-based routing, firewalls, VPN, etc. Vyatta redesigned its software to make use of multiple cores — so while the control plane ran on one core, the data plane was distributed across multiple cores. Using a 4 core processor, they ran control plane on 1 core, and 3 instances of line traffic were handled by the remaining 3 cores.  This way Vyatta was able to handle 10G traffic through a single processor.

Now imagine putting 3-4 such x86 based servers in a network. If (and we look at this in some other blog post) you can split the data traffic equitably, you can achieve close to 30-40G throughput.

Wind River a few weeks ago announced its new accelerated virtual switch (vSwitch) that could deliver 12 million packets per second to guest virtual machines (VMs) using only two processor cores on an industry-standard server platform, in a real-world use case involving bidirectional traffic. 

Many people believe that NFV is best suited to deployed at the edge of the network — basically close to the customers and isnt yet ready for the core or places where the traffic volumes are high or the latency tolerance is low. I agree to this, and covered this aspect in great details here.

What this shows is that its patently possible for virtual routers to run at speeds comparable to regular hardware based routers and can replace them. This augurs well for NFV since it means that it can be deployed in a lot many places in the carrier network than what most skeptics believed till some time back.


NFV and SDN – The death knell for the huge clunky routers?

Last IETF i ran into a couple of hallway discussions where the folks were having a lively debate on whether Network Function Virtualization (NFV) and Software Defined Networking (SDN) will eventually sound the death knell for huge clunky hardware vendors like Cisco, Juniper, Alcatel-Lucent, etc. I was quickly apprised about some Wall Street analyst’s report that projected a significant drop in Cisco’s revenue over the next couple of years as service providers moved to SDN and NFV solutions . I heard claims about how physical routers (that i so lovingly build in AlaLu) will get replaced by virtual routers (vRouters) and other server based software that even small startups could build. The barrier to entry in the service provider markets had suddenly been lowered and the monopoly of the big 3 was being ominously challenged. There was talk about capex spending reduction happening in the service provider networks and how a few operators were holding on to their purchase orders to see how the SDN and NFV story unfurled. There was then a different camp that believed that while SDN and NFV promised several things, it would take time before things got really deployed and started affecting capex spending and OEM’s revenues.

So whats the deal?

Based on my conversation with several folks actively looking into SDN/NFV and a good bit of reading I understand that operators are NOT interested in replacing their edge aggregation and core routers with software driven vRouters. They still want to continue with those huge clunky beasts with full control plane intelligence embedded alongside their  packet pushing data plane. These routers are required to respond to network events in real time (remember FRR?) to prevent outages and slowdowns. Despite all performance improvements the general purpose processors can typically process not more than 2-3 Gbps per core (Intel with DPDK module and APIs for Open Virtual Switch promises better throughput) which is embarrassingly slow when compared to the throughput of 400-600 Gbps thats possible with NPUs and ASICs today. Additionally routers using non-ethernet ports (DSL, PON, Coherent Optical, etc)  cannot be easily virtualized since the general purpose CPUs cannot perform the network functions along with the DSP components required to support these ports.

So while a mobile gateway that essentially forwards packets can be virtualized, it would only make sense to do this where the amount of traffic its handling is relatively small.

So where can we deploy these NFV controlled server based vRouters?

The Provider Edge (PE) routers does several things today, few of which could be easily moved out to be implemented on standard server hardware. ETSI’s NFV Use cases document (case #2)  identifies vPE as a potential NFV use case. The “PE” routers in the MPLS world connects the customer edge (CE) router at the customer premises to the P routers in the provider network. The PE router serves as the service delimiter where it provides L3 VPNs, VPLS, VLL, CDNs and other services to the customers.

The ETSI NFV use-case document (case #2) describes how enterprises are deploying multiple services in branch offices; several of these enterprises use dedicated standalone appliances to provide these services (firewalls, IDS/IPS, WAN optimization, etc), which is “cost prohibitive, inflexible, slow to install and difficult to maintain”.

As a result, many enterprises are looking at outsourcing the virtualization of enterprise CPE (access router) into the operator’s network.

Increased capex and opex pressure is edging enterprises and providers to look at virtualization capabilities made possible by NFV. So, lets look at what all can be virtualized by NFV.

The ETSI NFV use-case document states that “Traditional IP routers  based on custom hardware and software are amongst the most capital-intensive portions of service-provider infrastructure. PE routers run out of control plane resources before they run out of data plane resources and virtualization of control plane functions improves scalability.”

It further states that moving some of the control plane to equivalent functionality implemented in standard commercial servers deploying NFV can result in significant savings.

The figure below gives an idea of the components that can be moved out of the PE router and onto an NFV-powered server.

Network functions/services that can be offloaded from the PE router

Network functions/services that can be offloaded from the PE router

If we’re able to push out the functions/services shown in the figure above, the PE router effectively gets reduced to a router thats mainly pushing the packets out and vPE, the device for service delivery. NFV appears to be most effective at the edge of the network where customers are served — this also happens to be mostly ethernet, which works in the favor of NFV since other ports cannot be served as effectively.

Operators believe NFV can be used for mobile packet core functions for 3G and EPC. LTE operators believe that while basic packet pushing functions must still reside in the routers, the other ancillary functions that have been added to the routers over the time are good candidates for NFV. We can keep BRAS, firewalls, IDS, WAN optimizers, and other service functions separate and use the physical router for merely transferring the packets.

Clearly, the vPE can handle many network functions that are currently done by the conventional physical routers. While the PE may still handle pushing the packets, the intelligence for many of the services typically handled by the PE can be moved to vPE. This is a paradigm shift from what the PE routers have been doing all this while. The network functions and services that can be moved to vPE are:

  • Mobile packet core functions for 3G and LTE EPC
  • Firewalls (FW) and IDS/IPS (Intrusion Detection and Intrusion Prevention systems)
  • Deep Packet Inspection (DPI)
  • CDNs (content delivery networks) and caching
  • IP VPNs – control plane to set up the MPLS VPNs
  • VLLs and VPLS – control plane to set up the MPLS VPNs

These functions can be virtualized to run either on the servers under NFV or can be SDN controlled. Where these reside in the network will depend upon the QoS and QoE (Quality of Experience) required by the customers. If latency and speed is an issue, the functions should reside in servers close to the customers. But if latency is not an issue the functions could reside deep in the provider network or a remote data center.

Conclusion

Operators will deploy NFV and SDN, which will impact their buying decisions. Its clear that they will not be replacing their core and  edge aggregation routers with NFV driven software solutions. Instead, NFV will be used at the edge to offload service functions from the HW PE router onto servers with vPE in the NFV environment to deliver new services agilely to end users and generate higher revenue.

There is thus no need for the Ciscos, Junipers and Alalu’s of the world to worry about falling revenues since the NFV powered solutions are not targeting their highest margain businesses — at least not yet!


BFD in the new Avatar

 

BFDWe all love Bi-directional Forwarding Detection (BFD) and cant possibly imagine our lives without it. We love it so much that we were ready with sabers and daggers drawn when we approached IEEE to let BFD control the individual links inside a LAG — something thats traditionally done by LACP.

Having done that, you would imagine that people would have settled down for a while (after their small victory dance of course) — but no, not the folks in the BFD WG. We are now working on a new enhancement that really takes BFD to the next level.

There isnt anything egregiously wrong or missing per se in BFD today. Its just not very optimal in certain scenarios and we’re trying to plug those holes (and doing our bit to ensure that folks in data comm industry have ample work and remain perennially employed).

Ok, lets not be modest – there are some scenarios where it doesnt work (as we shall see).

So what are we fixing here?

Slow Start

Well for one, BFD takes awfully looooong to bring up the session. Remember BFD starts with sedate timers and then slowly picks up (each side needs to come to an agreement on the rate at which they will send packets) . So it takes a while before BFD can really be used for path/end node liveliness detection. If BFD is being used to validate an MPLS path/LSP then it will take a few additional seconds for BFD to come up because of the LSP ping bootstrapping procedures (RFC 5884).

In certain deployments, this delay is bad and we want to eliminate it. It is expected that some MPLS deployments would require traffic engineered LSPs to be created dynamically, driven by external applications as in Software Defined Networks (SDN). It is operationally critical to ensure that the forwarding paths are up (via BFD) before the applications start utilizing the newly created tunnels. We cant hence wait for BFD to take its time in coming up since the applications are ready to push data down the tunnels. So, something needs to be done to get BFD to come up FAST!

This is an issue in SDN domains where a centralized controller is managing and maintaining the dynamic network. Since the tunnels are being engineered by this centralized entity we want to be really sure that the new tunnel is up before sending traffic down that path. In the absence of additional control protocols (eg. RSVP) we might want to use BFD to ensure that the path is up before using it. Current BFD, with large set up times, can become a bottle neck. If the centralized controller can quickly verify the forwarding path, it can steer the traffic to the traffic engineered tunnel very quickly without adversely affecting the service.

The problem exacerbates as the scale of the network and the number of traffic engineered tunnels increase.

Unidirectional Forwarding Path Validation

The “B” in BFD, stands for “Bi-directional” (in case you missed that). The protocol was originally defined to verify bidirectional connectivity between two nodes. This means that when you run BFD between routers A and B, then both A and B come to know when either router goes down (or when something nasty happens to the link). However, there are many scenarios where only one of the routers is interested in verifying the data plane continuity between the two nodes (e.g., static route using BFD to validate reachability to the next-hop router OR a Unidirectional tunnel using BFD to validate reachability to the egress node). In such cases, validating the reverse direction is not required.

However, traditional BFD requires the other side to maintain the entire BFD state even if its not interested in the liveliness of the remote end.  So if you have “n” routers using a particular gateway, then the gateway has to maintain “n” BFD sessions with all its clients. This is not required and can easily be done away with.

Anycast Addresses

Anycast addressing is used for high availability, fast recovery, load balancing and dispersed deployments where the IGPs direct the traffic to the nearest server(s) within a group of potential servers, all sharing the same Anycast address. BFD as defined today is stateful, and hence cannot work with Anycast addresses.

With the growing need to use Anycast addresses for higher reliability (DNS, multicast, 6to4, etc) there is a need for a BFD variant that can work with Anycast addresses.

BFD Fault Isolation

BFD works in a binary state – it either tells you that the session is UP or its DOWN. In case of failures it doesnt help you identify and localize the fault. Using other tools to isolate the fault may not necessarily work as the OAM packets may not follow the exact same path as the BFD packets (e.g., when ECMP is employed).

There is hence a need for a BFD variant that has some capabilities that can help in fault isolation.

So, where does this lead to?

We have attempted to fix all the issues that i have described above in a new BFD variant that we call the “Seamless BFD” (S-BFD). Its stateless and the receiver (or the reflector) responds with an S-BFD response packet whenever it receives an S-BFD packet from the source. You can imagine this as a ping-pong game between the source and the destination routers. The source (or the client in S-BFD speak) wants to check if the path to the destination (or the Reflector in S-BFD speak) is UP or the reflector is UP and sends an S-BFD “ping” packet. The Reflector upon receiving this, responds with a S-BFD “Pong” packet.  The client upon receiving the “Pong” knows that the Reflector is alive and starts using the path.

Each Reflector selects a well known “Discriminator” that all the other devices in the network know about. This can be statically configured, or a routing protocol can be used to flood/distribute this information. We could use OSPF/IS-IS within an AS and BGP across the ASes. Any clinet that wants to send an S-BFD packet to this Reflector (or a server if it helps) sends the S-BFD packet with the peer’s Discriminator value.

A reflector receiving an S-BFD packet with its own Discriminator value responds with a S-BFD packet. It must NOT transmit any BFD packet based on a local timer expiration.

A router can also advertise more than one Discriminator value for others to use. In such cases it should accept all S-BFD packets addressed to any of those Discriminator values. Why would somebody do that?

You could, if you want to implement some sort of redundancy. A node could choose to terminate S-BFD packets with different Discriminator values on different line cards for load distribution (works for architectures where a BFD controller in HW resides on a line card). Two nodes can now have multiple S-BFD sessions between them (similar to micro-BFD sessions that we have defined for the LAG in RFC 7130) — where each terminates on a different line card (demuxed using different Discriminator values). The aggregate BFD session will  only go down when all the component S-BFD sessions go down. Hence the aggregate BFD session between the two nodes will remain alive as long as there at least one component S-BFD session alive. This is another use case that can be added to S-BFD btw!

This helps in the SDN environments where you want to verify the forwarding path before actually using it. With S-BFD you no longer need to wait for the session to come up. The centralized controller can quickly use S-BFD to determine if the path is up. If the originating node receives an S-BFD response from the destination then it knows that the end point is alive and this information can be passed to the controller.

Similarly applications in the SDN environments can quickly send a S-BFD packet to the destination. If they receive an S-BFD response then they know that the path can be used.

This also alleviates the issue of maintaining redundant BFD sesssion states on the servers since they only need to respond with S-BFD packets.

Authentication becomes a slight challenge since the reflector is not keeping track of the crypto sequence numbers (remember the point was to make it stateless!). However, this isnt an insurmountable problem and can be fixed.

For more sordid details refer to the IETF draft in the BFD WG which explains the Seamless BFD protocol and another one with the use-cases. I have not covered all use cases for Seamless BFD (S-BFD) and we have a few more described there in the use-case document.


Why do we need specialized switches in Data Centers?

data center

Whats the big deal about Data centers and why do they need special routers and switches anyway? Why cant they use the existing switches that folks use in their back offices or service providers in their networks. What’s so special, really, about a bunch of servers that need Internet connectivity, huh?

Working in the metro Ethernet space all my life I wasn’t sure if I really understood the hype and the reason why Data centers required specialized HW.

It’s only once I started reading about Data centers and how they work and what they’re supposed to do that I was able to appreciate their need for specialized HW – and why the existing products may not be cut for them.

In the world of Wall Street, milliseconds can mean billions of dollars. Really, am not kidding here. Packets carrying Wall Street transactions get delivered to the switch and are then forwarded to the server in the Data Center. There they ride up the protocol stack to the application that executes the trade. The commit message then has to go back down the stack and then be sent over the wire to the switch. The switch does a lookup in its forwarding tables and sends it out on an egress destination port.

One of the things that would differentiate one Data Center switch from the other would be the time it takes for the switch to process the incoming packet, the amount and the nature of queuing that happens (which directly affects the latency), the serialization delays at the ingress and egress, and other factors that can contribute to adding a few microseconds to each packet processing (or transaction in Wall Street speak).

So is adding a few microseconds really a big deal?

Oh Yes, you bet it is – especially in the big bad world of Wall Street.

wall street

You only need to google for “high-frequency trading” and you would understand why it’s the suddenly become one of the most talked about thing in the Wall Street.

Lets see how shaving off a few microseconds can help?

A Mutual Fund house places an order to purchase 100000 shares of a company ABC that’s currently going at $10. NASDAQ (or some other exchange) could offer a few selected high frequency traders a peek into the incoming orders for 30 milliseconds or so (this is illegal, but there are loopholes in the system). The high frequency trader, knows that a purchase order for 100000 shares of ABC is coming and immediately picks up all the available shares at $10. After a few seconds, the Mutual Fund house order hits the market place and the high frequency trader sells their shares at $10.50, pocketing $50000 from a single transaction. Now, multiply this by the average number of transactions that typically take place in an Exchange and you would you arrive at the staggering amount of $$$ that’s at stake here.

Its thus imperative that the high speed computers that are doing all the number crunching have supporting network infrastructure that can help them in making the kill. Lower network latency and increased throughput means faster and better profits for the trading companies.

Firms using high frequency trading earned over $21 billion in profits last year. The TABB Group estimates that a 5 millisecond delay in transmitting an automatic trade can cost a broker 1% of its flow; which could be worth $4 million in revenues per millisecond. According to Reuters, trading a stock is now far faster than a blink of an eye or the speed of a lightning strike.

In fact several high frequency traders house their systems as close as possible to the exchanges to minimize the latency in executing their orders.

There are also other environments where low latency is desirable. Environments such as computer animation studios that may spend 80 to 90 hours rendering a single frame for a 3D movie, or scientific compute server farms (for Computational Fluid Dynamics) that might involve tens of thousands of compute cores. If the network is the bottleneck within those massive computer arrays, the overall performance is affected.

The Data centers thus patently need switches that have extremely extremely low latency in forwarding packets.

So what are the other things that the Data center switches must support – and which may not be available in ordinary switches?

Micro-bursting often happens in Data Centers, wherein the buffers overrun and the switches drop packets. The problem is that these micro-bursts happen often at microsecond intervals, so the switches may not report them. A good Data Center switch will absorb the micro-burst and forward the packets without dropping ’em.

Data centers as we just saw are designed for critical systems that require high availability. This means redundant power, efficient cooling, secure access, ideally no down time, and a whole lot of other things, but most of all, it means no single points of failure.

Every device in a data center should have dual power supplies, and each one of those power supplies should be fed from independent power feeds. The power supplies are sized such that the device operates with only power path. All devices in a data center should have front-to-back airflow, or ideally, airflow that can be configured front to back or back to front. Thermal guidelines for Data Centers is a science by itself and there is more than petabytes of information available on the net on how this needs to be effectively done.

All devices in a data center should support the means to upgrade, replace, or shut down any single chassis at any time without interruption to meet the hard Service Level Agreements (SLAs). In-Service Software Upgrades (ISSU) should ideally be available, but this can be circumvented by properly distributing load to allow meeting the prior requirement. Data center devices should offer robust hardware, even NEBS compliance where required, and robust software to match.

This isnt the most exhaustive list of the things required out of switches deployed in Data Centers, and only serves to give a hint of whats needed there.

Oh and btw, I must finish this post and rush to place an order on NASDAQ before some high frequency trader preempts me and books all the profits!