NFD16 – Gigamon and Splunk (with a Dash of Phantom)

I had the opportunity to take a trip to the Gigamon mothership (no, not like the Apple Mothership, it’s a normal HQ) last week at Networking Field Day 16. I was pretty excited as I’ve not had a ton of hands on with Gigamon, but I’ve run into their products at a goodly portion of all the customers I’ve worked with over the years.

If you’d like to take a peak at some Gigamon presentations before continuing you can check out a ton of them here on Tech Field Day’s Youtube channel.

This events presentations were focused on leveraging Gigamon, and some of their partners (Splunk and Phantom), ability to react to security incidents. The core idea in their presentation is that security is a very hard problem (they ain’t wrong!), and that many organizations spend a large quantity of time and money, generally across a broad set of tools. In order to make security simpler the idea is that you can use Gigamon and Splunk to in concert to detect things that you would prefer not happen on your network, and that would require tons of other tools to do without these platforms combined power. The integration between the platforms allows for Splunk to fire off these triggers which Gigamon can then react to by dropping traffic or alerting on this traffic. Taking things a step further via the integration with Phantom these events as seen in Splunk could fire off a whole host of mitigation tactics/processes in order to automate away a lot of the manual tedious work that SOC personnel may have to deal with. All told, this is a pretty cool story. The integration with both of these other platforms seemed from the demo to be pretty smooth; flexible, but not super open-source-y (i.e. your average Joe/Jane could probably figure it out without pulling out too many hairs).

In a perfect world, I can certainly see Gigamon (and team) supplanting possibly many other products by consolidating functionality. Gigamon itself is a pretty powerful platform, couple that with Splunk which is a beast and can provide very interesting data correlation/insights, and finally wrap it all up with Phantom to put the sexy bow of automation on this and things look interesting (unfortunately time was limited for the Phantom portion of the presentation so I don’t have much insight there but it really did look awesome!). That being said, there are some challenges…

Gigamon at its core relies on being inline with traffic, or at least receiving traffic (of course if you’re not inline you can’t drop things so keep that in mind). This has historically been more or less a non-issue — data centers always have had choke points, so go ahead and plop your Gigamon appliance right there and you’re in business. That whole Christmas tree type topology where we had easily defined choke points is not really a thing anymore (at least in data centers being deployed now — of course they still exist). Most data centers, and certainly the ones I’m involved in, are opting to build out in a Clos topology. In a Clos topology we can have crazy things — like 128 way ECMP!! Not that 128 way ECMP is common, but even in small 2-4 spine node topologies there aren’t any especially good places to place a device like a Gigamon. You can of course put Gigamon/IPS/whatever inline between leaf and spine nodes, however this is an atrociously expensive proposition — for several reasons, firstly just for the sheer amount of links that may entail, and secondly from a capacity perspective — if you’re going 40G, 100G or looking toward the crazy 400G you’re going to have to pay to play to run that kind of throughput through a device (Gigamon or otherwise). Depending on the topology, it may be easy to snag “north/south” traffic (border leaf nodes -> whatever is “northbound” for example), but with an ever-increasing focus on micro segmentation within the data center this is *probably* not sufficient for most orgs.

One option to address some of this that was not mentioned, or was mentioned only briefly, at the Gigamon presentation is the GigaVUE-VM. The idea here is that this is a user-space virtual machine that can be either in-line with VM traffic, or sitting “listening” in promiscuous mode. Because this is living in the user-space there are no hypervisor requirements/caveats, it just kind of hangs out. If used in “inline mode” (which I’ve actually not seen so maybe thats not a thing?) there is the potential for this to replace the big iron hardware appliances, and fit more neatly into a Clos topology. I would have liked to see/hear more about this… a bit more about why at the end…

I had two major takeaways from the Gigamon presentation, firstly — Splunk is like a magical glue to tie things together! The data being fed into Splunk could have come from any number of sources (syslog of course, clients on agents, http events, etc.); in this case it was from Gigamon, and Gigamon performed drop actions based on the rules created in Splunk. I suspect that Splunk could be (relatively?) easily configured to make an API call to a firewall or other device/platform to react to data being fed into it. Splunk without data though, is not really all that useful — and here is where Gigamon showed their value. Being able to capture LARGE amounts of data, and then do something to it (really just drop, but thats an important thing) is very valuable.

That being said, my second takeaway was that this felt largely out of sync with what most customers I see are doing, at least in the data center. When pressed for how to practically adapt this into a Clos topology the answers were thin at best: (paraphrasing) “just tap all the links to leaf/spine”, “tap at chokepoints” etc.. This is all well and good and depending on requirements and budget may be just fine, however I didn’t exactly get warm fuzzies that Gigamon knows how to play nice in these Clos data centers. Obviously tapping everything is a non-starter financially, and chokepoints are well and good but that means that the substantial investment in Gigamon/Splunk (because it really does seem like they  need to be deployed in unison to justify the expenditures) doesn’t actually do you much/any good for securing east/west traffic.

Having ran into Gigamon in several Cisco ACI deployments I’ve been a part of I can say that customers really love — or at least have invested so much that they feel the need to continue to get value out of — Gigamon, but each time I’ve seen this there has been a big struggle to find a good home for the appliances. This is why I really would have liked to have seen and heard more about the GigaVUE-VM — my knowledge is quite limited on it but it certainly seems to be a possible work around for the challenges of finding choke points in a  Clos fabric. The big caveat to this is that the Gigamon folks did mention that the VM does NOT have feature parity with the HC hardware appliances. It sounds like they are investing in adding these features though which would obviously be helpful.

One final note, as I have very data center focused goggles on I’ve more or less ignored the campus/WAN, but I definitely think this could be useful in those areas, perhaps much more so than in the data center.