Arista Networks, Inc. (ANET) Earnings Call Transcript & Summary

Good afternoon, everyone. I'm Samik Chatterjee. I cover hardware and networking companies at JPMorgan here and I have the pleasure of hosting the Arista team. Here with me, we have Chantelle Breithaupt, who's the Chief Financial Officer, Ashwin Kohli as well and Liz as well from Investor Relations. Thank you all for making it to the conference. And thank you to the audience as well for joining. I'll direct a few questions. Just let me know whoever wants to take it. But I do want to start with a question that we've been asking most of our companies to just share their thoughts on how they think the next 12 months will shape out in terms of -- just project for us, when you think about your main end markets, or primary end markets, where do you think they will be in terms of either spending intent or from a overall sort of positive/negative outlook compared to where we are today, how does the next 12 months look. I think for you, especially, it looks like maybe going by vertical when we talk about either the hyperscalers or the specialty cloud or enterprise, if you want to break it down that way rather than in any generic macro comments, we can -- we'd definitely appreciate that as well.

Yes, sure. Good afternoon. I think that from the perspective of the next 12 months, so if you had listened to the earnings call we had on February 12, you would think from the perspective of looking at the raise of our guide for the year to 12% to 14% growth and with that comes to your question, Samik, in the sense of what we see. So when we raised the guide for the year, part of that was looking at optionality of different ways to get to that outcome and that's robustness across many of our vertical sector segments. And if you take cloud and enterprise and the specialty providers, those 3 segments, we've seen good traction across those 3 things. So I think that we're excited by what we're seeing from that perspective. Mostly, that was in the sense of traditional cloud, classic cloud and enterprise. I know -- I have a feeling you'll probably ask us something about AI but we'll wait and see. But I think from an AI perspective, that's kind of like a tertiary adjacent that would be something we should think about going into 2025 with the $750 million revenue target that we expressed constructive optimism towards. And so we're excited. I don't know. I guess.

So let me just, Chantelle, follow up on that. I mean, the optimism on that front is definitely something, when we compare to 2023, when the cloud companies were not spending as rapidly, when you think about the change from there -- that -- from that time horizon, how do you think about what's changing for the cloud companies itself for them to come back to invest in the traditional sort of infrastructure? Is it just purely a function of inventory digestion and that we are sort of -- that's behind us? Or is there something more sort of technology-related, structural-related that's getting them to come back and reengage in the traditional infrastructure? And I know we are not talking about the AI side just yet but even come back and invest in this, how do you see that change? What's driving that?

Yes. I think there are a few things in that conversation. I think part of it is just timing of the conversation. I think with the fiscal calendar years, working through budget cycles, planning cycles, et cetera, gaining visibility, we talked about gaining visibility from 3 to 4, 5, 6 months of visibility. So that's encouraging. And I think the hypothesis is, speaking on their behalf in the sense of what we see is just continuing that refresh cycle, continuing the investment side or adjacent to their cloud -- their AI CapEx conversation, so I think it's part of their refresh cycle that we're seeing. And then just having set plans and intention with -- within our fiscal year '24.

Okay. I'll digress for a bit and we'll get to the AI related questions, which we obviously have a turn of. But one of the things that investors have come up and mentioned to me a few times, I did want to get that out as a question and get your feedback on it or comments on it. For an incredibly stable management team that you've had over the years, investors have been caught a bit by surprise in terms of the magnitude of changes more recently, including Anshul departure, changes to the Board. That's definitely got investors more sort of curious about what's happening. How do you sort of reassure investors that there's no change in the road map, everything sort of as they should expect in terms of Arista executing the way it has always, which is execute better than expected, right? How do you reassure investors on that front?

Yes, I think a couple of things I would mention. I think given the size of Arista and the length of time Arista has been a company, I think having some of this tenured staff for anywhere between 8, 12, 16 years, I think that's actually in the tech industry, quite a long tenure. I think that you had a couple of things happening around the same time that are not related. And so maybe that was a bit of the form factor of the thinking that there's lots of change. I think they are very specific changes. Regardless of that, we have a ton of bench strength across all the items and it allows the leadership that was there before to kind of rise up and do things and add to their career that they couldn't have before. So we have in the sense of mentioning Anshul leaving, we have great capacity and capability. We have Ken Kiser, who's leading the sales. We have Martin Hull, who's from a product engineering perspective. We have John McCool, who has like engineering and operations. So a ton of strength that's been there a long time as well. So we have all the people that you know and love working on the tech road map that have not changed, including Andy [indiscernible] that we're very excited about. So I don't think any one departure changes the direction of the company. Coming from bigger companies, we have a structure and a matrix to help bolster what we need to bolster, tech road map, leadership, sales engagement. We have Ashwin here as the Chief Customer Officer, working with the team in the enterprise. So from that perspective, the enterprise is covered. So we're excited. We feel we have the leadership we need, the relationships we need, the engagements. And we have the confidence to raise the guide in that environment. So I'm optimistic.

Great. Moving to AI. And before we get into the demand road map here, we are also curious in asking all of our companies to talk about how they're adopting it internally, where do they see the tangible improvements in terms of internal operations coming through?

Yes. No, that's a great question. Good afternoon, everyone. So we've made investments as well to take care of how we can leverage AI internally. So both from a development standpoint of view and from my team, which is a lot more field operations focused, so on the development side, while you are coding, you can actually see efficiencies from there. For my team, specifically, we've actually -- the goal is -- from field operations, we want to try to go figure out how do we help customers make money and how do we help customers save money. And so the goal is, okay, how do we go get better documentation, better support, better alignment, automation of designs and support out there. We've obviously got our internal tool, which is called Ask EVA. And we've been enhancing that and leverage that as well for a number of different products internally in order to go drive efficiencies from there.

Got it. Great. So let's move to the demand side but I do want to sort of first hit the biggest debate that investors have been focused on, which is Ethernet's opportunities related to InfiniBand. Can you talk about where Arista is winning against InfiniBand? And what are the drivers to leading your customers to choose Ethernet?

No, great question, right? So in specifics to AI, typically, when a customer is thinking about AI, they're thinking about the -- what's called the back-end infrastructure side over there. And so customers have a choice either to go for InfiniBand in that scenario or they can go from an Ethernet -- as an option over there. And so when they're looking specifically from Ethernet, they want to make sure they're actually going to a non lock-in, nonproprietary standards-based architecture, both from a hardware side and from a software side in order to go scale out their back-end infrastructure. This actually drives their total cost of ownership much lower, which is of interest for a lot of customers. Additionally, when they're actually looking at Ethernet, what they want to do is, they want to make sure there are several metrics from a technology perspective, they want to look at it as well. So they want to look at whether it's a lossless architecture, whether it actually does a good priority flow control, whether it does congestion. But there are several other metrics over there that customers want to look at when they're deploying Ethernet. And this is not only from a day one perspective, which is the day you actually buy the equipment but exactly how do you roll this out and what's called life cycle management. So when you're thinking about life cycle management, you want to be thinking about, okay, how do I automate the infrastructure, how do I do code upgrades because in all networks, there is software. And there are going to be bugs in software. So the question that comes in is, how do I do a seamless code upgrade in my -- in AI infrastructure without actually bringing down the AI infrastructure because when you do, then the GPUs are not active. And so you want to be able to go do a software upgrade, which is what's called Hitless. Additionally, you may have security patches on the software as well. So you want to be able to patch your security infrastructure or the AI infrastructure for any security patches, once again Hitless, so there's no impact to the business specifically on the GPU clusters as well. The other -- in order to lower the total cost of ownership, customers are thinking about visibility. Can I actually manage my AI infrastructure in exactly the same way for the other use cases that have -- so let's say, for example, they have data center, they have campus, they have routing. They want to make sure that they're actually using the same tools, the same people, the same processes in order to go and manage the AI infrastructure as well. So all very, very key points that anybody who's thinking about looking at making an investment choice on an AI fabric, they want to be considering all these as well.

Yes. And I think just to add to that, Ashwin, I think 6 months ago, we were having this debate Ethernet versus InfiniBand. And 2 quarters ago, we started talking about kind of these 4 out of 5 AI opportunities that we were invited into that have -- 4 of them have chosen Ethernet to move forward. That means these customers are putting engineering resources behind kind of the development and wanting to see Ethernet service those back-end AI clusters. So kind of showing that momentum. And I think that on the most recent earnings call, Jayshree, went on to talk about these clusters progressing through the pilot stage, so we've talked about kind of 2023 being the trials, 2024 being pilots. And some of those pilots scaling up to tens of thousands of GPU connections and then moving on to kind of the production in 2025, which is where our $750 million target comes from. And those having aspirations of scaling well beyond up to 100,000, maybe beyond that. So I think showing that progression, I think Jayshree has been very good at kind of dictating the last couple of quarters about the progress that we're making with some of these larger AI opportunities.

Great. Maybe let's extend that sort of discussion a bit more towards now Spectrum-X which has come up a lot in conversations, Liz, as you're aware as well. Just how do you see them as a competitor when Arista's winning with the 4 out of 5 you've talked about. Obviously, it's a choice by the customer to adopt Ethernet but then Spectrum-X obviously then gets included as an Ethernet option. So how do you think about the competitiveness against that product?

Yes. I mean I would try to simplify that down into 2 big buckets, right? One being hardware and one being software. So customers obviously want a choice, once again back to Ethernet, whether it's going to be proprietary or non lock-in. And so Arista delivered value over there for the last 20 years. When you actually look at the hardware specifics, depending on the scale of the AI fabric that you're trying to build, you want to try to look at, okay, is the traffic leaving the rack, right? That's the first out of the scale that you're looking at. If it's going to be leaving the rack and if it's going to a small cluster of GPUs, then you want to figure out do you want a what's called a lossless fabric. So Arista has a solution over there, which is very Jericho-based. that gives the customers the confidence that if traffic is going from one rack to another, then we'll guarantee that they're actually not going to be dropping packets. So they can actually use the Arista 7800 chassis to go maneuver traffics at what's called a single-tier AI fabric. The question then comes in is, like Liz said before, if you're going to be scaling to tens of thousands of GPUs, if not hundreds of thousands of GPUs, scale becomes a massive factor over there. At that point in time, you want to look at a 2-tier architecture and so what differentiates us from spectrum specifically over there is, Arista has a Jericho-based platform that actually allows us to scale not only at the single-tier fabric, which is a lossless architecture, they can use a Jericho-based family of products or they can use a Tomahawk 5 or they can go to what's called a 2-tier architecture and they can actually use the Jericho platform in the spine layer over there, which actually allows them to scale. So that's from a hardware differentiation that Arista has -- offering for our customers. From a software side, it comes back down to basics, right? Arista has been very good at -- our software platform, which is called EOS. EOS allows and gives our customers, and I always tell this a lot of times to our customers, any network should just work. It should not be just a specific use case, whether you have a software that actually is used for the data center. If you've got a use case for the campus, routing, AI is simply another use case as well. And so what we've been really good at differentiating our software value is basically being able to use the same code across multiple use cases. And I can articulate this very simply. I was giving a conversation earlier today, which is imagine if you've got a MacBook Pro, you've got an iPad and you've got an iPhone. So different hardware but they all have the same look and feel across different types of platforms. So for the users, they don't care about which platform they're using, they can actually use it across all. It's the same apps, very similar to what Arista does, right? Different use cases, same software gives our customers the value to go leverage from there as well.

So one other thing that I would add to that, thank you Ashwin. Never underestimate that -- the software importance, right? So if you talk to any of these guys that are building large AI clusters, it's a mission-critical application, right? It's a competitive advantage. Like if the network doesn't work, the GPUs are not talking to each other. That is a very important factor. So we've gotten a couple of questions where it's like, well, if it's single application, does software really matter? It definitely matters. And it matters even more when it's a mission-critical app and especially because these resources are so expensive, right? You want to get your most utilization out of those GPUs. So EOS has always been built on this culture of quality, right? We don't ship a product before it's ready. We will not risk melting down a customer network in order to hit a specific date like that's just not the way that we've decided to build products. In EOS -- and Ken and his team are committed to this culture where -- so that Ashwin can tell customers, it just works, right? There is a quality aspect to our code that is a competitive advantage. And that remains true even in AI networks.

Maybe just following up on that. You talked about the 4 out of 5 wins. Just want to get more sort of nuance to that. When you think about that, is it a win against InfiniBand? Or do you also see Spectrum-X as a competitor there that you were able to displace and would you really, in the marketplace today, when you go to your customers, are you seeing Spectrum-X being offered as a solution already? Or is this more something that will be offered in the future?

Yes. So I think -- so if you look at the 4 out of 5, we've talked about these 4 out of 5 AI opportunities that 4 of them on Ethernet, one of them stayed InfiniBand. Right. Inside the Ethernet, I think -- and some of you have probably seen, there's public postings around one of those deployments. One of our customers kind of outlining what it looks like at the leaf layer and putting Arista the 7800 at the spine. Ethernet in general has always been a competitive landscape, right? There's always been multiple players. And really, even the advent of Spectrum, that's not a new player. Those assets have been around for a while. And I think when we look at kind of the front-end network, right, where we've shined classic, take AI out of it, I think even through the cycles, you can see the market share numbers. And our job is to continue to develop and execute on the products that are going into this next cycle, which includes these AI use cases and AI opportunities. So I mean, I think that the competitive landscape, like I said, it's always a competitive landscape. There's always multiple players. I think that we view this AI cycle unlike any others where our job is to show up and execute with the best-of-breed products. As you've seen through the last cycles, I think that we've been happy with our share and now we have to go do it again, right?

Okay. Let's talk a bit more about UEC and the performance improvements that allows you to offer to your customers. You've talked about a set of products that probably launch more next year that will be more UEC compliant. What are you sort of envisioning those performance improvements to be? How does that change in your thinking, what your win rate will be?

Yes. Simply put, I think there have been third-party reports that basically have indicated that you'll actually get a 10% improvement in performance, based on that as well. And it's all around 2 things, right, job completion times which is very critical in an AI infrastructure and then the path, right from point A to point B, is when we think those are the 2 things that you should be looking at, whenever the products do come out, right? That's where you'll actually see the performance improvements from that side.

Yes. And I think some of the stuff that the UEC is working on is really getting that ecosystem already. So like just like Ashwin said, the end-to-end path, that includes [indiscernible] the NICs, the switches, right? Every half of that network. I think that as far as initiatives go, it's really around congestion management, obviously, managing the congestion in these AI workloads. You don't want packets colliding, et cetera. You don't want droppage. You don't want congestion. You want to get the most use out of your GPU resources. And then load balancing, right? So how do I effectively utilize all of the available bandwidth within the network? And I think those are kind of this -- the goals that -- the initiatives that UEC is working on kind of day 1. I think that we're expecting some sort of draft kind of here later on this year. Is it a stop gap to customers kind of continuing out their pilots? Like obviously, there's a lot of customers that are still working on their pilots today. But again, it's working on enhancing Ethernet to better service this new AI use case.

Okay. Let me ask you one more and then I'll open it up to the audience. How should I think about -- I mean, within the industry, there's also this big -- on the compute side, there's this big trend towards AI accelerators and looking at sort of adopting custom silicon that's sort of beyond the NVIDIA sort of ecosystem, right? How do you think about the win rate on those? How does that change this overall sort of market opportunity for Ethernet related to what you have when a customer is using or more locked into the NVIDIA ecosystem?

I mean I would say that a open ecosystem is good for everyone, right? It's good for Ethernet in general, right, more of these accelerators are coming out with support for Ethernet. It's good for customers, right, giving them a choice. I think especially these larger customers, they don't want to be locked into kind of a vertical stack and they don't want to be locked into a single vendor. So choice allows them to pick the best of breed for the application that they're going for. And when they can pick best-of-breed GPUs, you can pick best-of-breed networking and you can have all the building blocks, that best service, kind of their use case and their application.

And if I can add to that, outside the win rate, it's -- this is not the first time that InfiniBand -- there's been a conversation around InfiniBand and Ethernet as well. Right? InfiniBand has been around for the last 15-plus years. And so if you want to think about it, almost 15 years ago, there was a use case for InfiniBand where it was around low latency, high-frequency trading applications. So you actually had a bunch of HFT customers that were actually using InfiniBand to go try to go figure out the lowest latency, high bandwidth, lowest drop rate to go to market data, trading execution, trading portfolio servers. And then those same customers said, okay, we don't want to be locked in. We want to use something which is open standards, that's what Liz talked about. And so they actually migrated to Ethernet. That was about 15 years ago. Roughly speaking, about 10 years ago, there was another separate use case where customers were thinking about, okay, we have a fiber channel for storage environment, which is once again lock-in proprietary fabric and vendor lock-in as well. And the goal was, okay, can we migrate to something which is open standards-based and then they actually ended up using Ethernet for storage and Ethernet [ over ] storage or what became hyper -- HPC clusters basically from there. And today, it's exactly the same conversation, right? So this is, of course, this is the third use case almost in 15 years where you can see customers may try a specific technology and then they'll migrate over to Ethernet as well, right?