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Nutanix Weekly: Elevating hybrid cloud for AI, databases and general-purpose workloads at Microsoft Ignite · Nutanix Weekly

WEBVTT 1 00:00:02.740 --> 00:00:09.549 Philip Sellers: Hey, and welcome again to another episode of Nutanix Weekly. One of the many podcasts here at Zintegra. 2 00:00:09.630 --> 00:00:29.060 Philip Sellers: content with context is what we like to call them. And we're happy to have you back on listening with us for another episode. I'm Phil Sellers. I am the practice manager for modern Data center here at Integra, and I'm joined with some awesome guests, including 3 00:00:29.160 --> 00:00:35.889 Philip Sellers: none other than our chief enthusiasm officer Andy Whiteside Andy, how you doing. 4 00:00:35.890 --> 00:00:39.400 Andy Whiteside: I'm doing good, Phil, glad, glad to be on for an episode here. 5 00:00:39.400 --> 00:00:41.424 Philip Sellers: I know long time. 6 00:00:42.324 --> 00:00:50.099 Philip Sellers: for a long time you were the the primary host for this podcast. And handed over the reins to me not long ago, and 7 00:00:50.160 --> 00:00:53.279 Philip Sellers: it's good to have you back to join us in this afternoon. 8 00:00:53.280 --> 00:00:55.410 Andy Whiteside: I'll I'll try to contribute where I can. 9 00:00:55.934 --> 00:01:00.134 Philip Sellers: We've also got Jaira Cox. Jaira is 10 00:01:00.720 --> 00:01:07.760 Philip Sellers: chief putin tate from Nutanix. I don't know what title I should give you. I always title right. 11 00:01:07.760 --> 00:01:13.000 Jirah Cox: I've been called the Grand Poobah of the East men's bathroom, working on the west. 12 00:01:14.530 --> 00:01:16.638 Philip Sellers: Working on the West. Yeah. 13 00:01:17.060 --> 00:01:18.259 Jirah Cox: Got to aspire to something. 14 00:01:18.500 --> 00:01:26.730 Philip Sellers: Happy to have you here on the podcast we're also joined by Ben Rogers. Enterprise se here in the Carolinas. Ben, how are you doing. 15 00:01:26.730 --> 00:01:38.059 Ben Rogers: I'm doing great today, man holiday week. So today and tomorrow will be kind of kind of busy. But hopefully, Wednesday, the plane will start to land. Enjoy some family on Thursday and Friday, so I'm in all good spirits this week. 16 00:01:38.210 --> 00:01:56.945 Philip Sellers: That's right. Yeah. And it is the holiday week. So wherever you're at and listening, especially if you're here in the United States. Happy Thanksgiving, and we hope that you spend some time with family, and enjoy some turkey or some tofurky, if you're so inclined. 17 00:01:57.320 --> 00:02:00.570 Jirah Cox: Phil, are you a light light tofu, or dark tofu kind of guy. 18 00:02:00.570 --> 00:02:07.060 Philip Sellers: I am a full, full fledged turkey guy. So yeah, I I will stick to the 19 00:02:07.060 --> 00:02:09.630 Philip Sellers: the anal protein-based anal protein. 20 00:02:09.639 --> 00:02:20.695 Philip Sellers: the animal protein. That's it. Yes, 100%. So yeah, on behalf of everybody. Thanks for listening. You know, as always, we've got a blog post up 21 00:02:21.089 --> 00:02:45.199 Philip Sellers: this past week Andy and I were both out at Microsoft Ignite in Chicago. And so we we had a lot of chance to interact with customers. We brought about 30 customers. It's 1 of the value, adds we. We try to put back into the ecosystem is taking our customers with us to industry events, and so we had a bunch of people that we talked with hosted dinner, for at Microsoft ignite, and. 22 00:02:45.199 --> 00:03:04.549 Philip Sellers: as luck would have it, one of our great partners, Nutanix was also on site at Microsoft Ignite. And you guys were talking about AI databases and all sorts of other things. And so we've got a blog post today called elevating hybrid cloud for AI databases and general purpose workloads at Microsoft Ignite. 23 00:03:04.719 --> 00:03:12.995 Philip Sellers: We'll talk about all the different things that we were unpacking at the event, and dig into those in a little more detail. 24 00:03:13.519 --> 00:03:19.324 Philip Sellers: you know it. It's good to see Nutanix out in the marketplace, not only at their own events. But 25 00:03:19.669 --> 00:03:31.929 Philip Sellers: you know, at bigger industry conferences like ignite 1st time back post covid in person. It's been virtual for a few years. Had about 10,000 people I heard. It seemed busy. 26 00:03:32.109 --> 00:03:36.329 Philip Sellers: Andy, I mean, kind of what was your impression? Just of the week in general. 27 00:03:37.330 --> 00:03:58.519 Andy Whiteside: All things, Microsoft. All things Microsoft partners, which includes partners like us, includes partners like Nutanix. You know the entire, the entire eco ecosystem like the whole ecosystem. Was there? You know a lot of people that we haven't been around a long time where it was good to be back around. I know the pandemic's been over for a little while, but this was the 1st conference where it felt like 28 00:03:58.520 --> 00:04:07.410 Andy Whiteside: all of the vendors and people that we've worked around for all these years were there and active, and everybody was front and center. 29 00:04:07.510 --> 00:04:17.499 Andy Whiteside: Of course, a lot of talk around AI and copilot almost to exhaustion. But I think it's so real that you we have to be talking about it. 30 00:04:19.060 --> 00:04:36.730 Philip Sellers: I I agree. Copilot was a a big, big letter, and I don't just mean the giant letters you could stand in front of and take photos in front of on the show floor. But we saw copilot everywhere. The logo I mean it was it was pervasive. The thing I heard back was 31 00:04:36.790 --> 00:04:43.880 Philip Sellers: how much it's improving, how fast it's improving and getting better at helping people do things. And so 32 00:04:45.300 --> 00:04:50.760 Philip Sellers: there's a lot of different places. You can plug it in. And so that was fun to hear about 33 00:04:51.210 --> 00:05:03.619 Philip Sellers: use cases. How? How are people tangibly getting benefits from that and since we're talking about copilot. It makes sense for us to start off with the 1st topic, which is AI. 34 00:05:03.840 --> 00:05:15.020 Philip Sellers: And as the blog post said, the workload, everyone's talking about just like at Ignite Jaira. Do you want to kind of lead us off? What? What's the 1st big news that you guys were sharing at Microsoft? Ignite. 35 00:05:15.020 --> 00:05:29.279 Jirah Cox: Yeah, so and then, for all of our listeners, right, you can recap this on this blog post. Which serves for us as a an ignite, recap blog post for nutanix, right around what we cover. So you'll find that on our blog for elevating hybrid cloud. 36 00:05:29.290 --> 00:05:34.170 Jirah Cox: The 1st one, of course. Yeah, definitely is AI and helps our customers. 37 00:05:34.190 --> 00:05:43.519 Jirah Cox: 1st off the I don't want to bury the lead. The big announcement. Our product, Nutanix enterprise AI usable, of course, in azure. Right? So now we can offer you 38 00:05:43.790 --> 00:05:53.780 Jirah Cox: that sort of command and control layer to govern your AI deployments on Prem, but also in azure as well. So one consistent identical look and feel 39 00:05:53.880 --> 00:05:57.250 Jirah Cox: for provisioning, for entitling, for operating 40 00:05:57.270 --> 00:06:05.640 Jirah Cox: the Llms. The Gpts that you want to use to power. Your business now, really, truly, anywhere, right within your 4 walls, within azure or both. 41 00:06:06.420 --> 00:06:14.640 Jirah Cox: that has a lot of benefits right? Because the way that I can then do inference in the cloud inference at the edge inference in my data center with my own private data. 42 00:06:15.750 --> 00:06:23.800 Jirah Cox: There's another blog post I saw recently that talked about the larger and more regulated a customer is, the more they want to 43 00:06:23.810 --> 00:06:32.189 Jirah Cox: probably use AI in a private fashion, right? Which doesn't mean they're for their 4 wall data center. It just mean anywhere that is considered within their cloud platform, right? Which 44 00:06:32.230 --> 00:06:35.309 Jirah Cox: part of what we do at Nutanix is, help your cloud. Go anywhere. 45 00:06:35.400 --> 00:06:43.570 Jirah Cox: run anything, run anywhere, including your cloud, can contain public cloud. Right? You can have availability zones in your cloud that are public cloud. 46 00:06:43.660 --> 00:06:55.740 Jirah Cox: so that ability to say, I can now do AI one way across all of this. But I own all of my data. I control all of the access to it. It's all mine. Massive shot in the arm for privacy and really, even data sovereignty. Right? 47 00:06:55.820 --> 00:07:01.930 Jirah Cox: Thinking back a couple weeks. Actually, Phil, to the blog post we covered about Nutanix unified storage 48 00:07:01.940 --> 00:07:09.889 Jirah Cox: for AI training. Remember, we were in that 2 ways, one in our data centers, one on Nc. 2 in public cloud, right? So that ability to 49 00:07:09.960 --> 00:07:21.899 Jirah Cox: host data with full governance, with full sovereignty and privacy over that. But now give that to maybe, Gpus, that I want to rent in the cloud lets that new Phoenix AI fabric really do very powerful things for me. 50 00:07:22.620 --> 00:07:28.399 Philip Sellers: When the interesting thing is the the week after we, we did that, podcast talking about it, I was out 51 00:07:28.690 --> 00:07:48.200 Philip Sellers: with other nutanix technology champions at the San Jose headquarters. We did a deep dive, and they were super super stoked over this performance benchmark we talked about. So if you haven't heard that episode definitely click back a few and listen to the Ml perf podcast episode. It's really great stuff 52 00:07:48.590 --> 00:08:11.380 Philip Sellers: that also gave me the ability to preview what we're talking about here. The enterprise. AI so nutanix enterprise AI or Nai for short, is the next iteration of Gpt in a box. It's the productized version of AI. That's consumable for everyone. And and that's my elevator pitch for it. Right? Is 53 00:08:11.710 --> 00:08:33.929 Philip Sellers: no matter where you run this, it makes AI, which is incredibly complicated, accessible. You get a management plane where infrastructure folks can have a ui, and you can go in and you can add your different large language models. You can expose those endpoints, you can train it. You can 54 00:08:33.990 --> 00:08:39.950 Philip Sellers: kind of control everything in the life cycle of an AI large language model 55 00:08:40.169 --> 00:08:53.600 Philip Sellers: in one place, and so I haven't seen that from anybody else. You know you've got vendor partners like hugging face and stuff like that that are part of this, but nobody's thought about it from an end to end perspective until I saw this. 56 00:08:53.870 --> 00:09:16.689 Jirah Cox: I like the way you put that I'll plant a little flag here. We'll come back to it around, making the difficult more accessible right. And and that is 100%. A great way to marketing might steal that. By the way, just heads up, Phil, that is really what it does right is, it makes things that are very complicated and nebulous, very, very accessible, like, click, click. Next done. Okay. Now, your AI is in production. What did you want it to do again? Let's go start. 57 00:09:16.690 --> 00:09:17.070 Ben Rogers: Right. 58 00:09:18.150 --> 00:09:30.269 Ben Rogers: So what's what's really cool about it for me being out on the sales and seeing how customers are absorbing. This is the simplicity of it also the ability to stand this up fast. So day one's really quick. 59 00:09:30.270 --> 00:09:30.630 Philip Sellers: But yeah. 60 00:09:30.630 --> 00:09:39.710 Ben Rogers: Day, 2 day, 3. Day, 4. The operations piece of it, and the maintenance piece of it. We're also empowering, you know, existing Nutanix engineers 61 00:09:39.710 --> 00:10:00.959 Ben Rogers: to AI now, and you know we're not really changing the game on them if they know Nutanix, and they understand how Nutanix is from a bread and butter standpoint. They can walk in in AI very easily, and so that's been another win for us is for existing customers. They now have, and they have had the platform that they're now going to run their artificial intelligence on. 62 00:10:00.960 --> 00:10:14.329 Ben Rogers: And then the second thing of this is really cool to me is, you know AI has been kind of thought of as a cloud thing, and we've quickly learned that security is is making that where people are wanting to pull that back on Prem. 63 00:10:14.330 --> 00:10:33.200 Ben Rogers: Well, this just gives the best of both worlds. Companies need to run AI on Prem, specifically, in manufacturing and healthcare. It's got to be next to the workload, but they also need to be able to have these engines running in cloud where they can disperse them and scale very easily. And so again, we're bridging that gap between these 2 environments. 64 00:10:33.950 --> 00:10:44.771 Philip Sellers: Yeah. And and it's not always just private data. You know, it's talked about use cases, right? You know, we're we're delving into more and more. How do we make this beneficial for folks? 65 00:10:45.908 --> 00:10:48.840 Philip Sellers: You're a support organization, right? You have 66 00:10:48.890 --> 00:10:54.380 Philip Sellers: tons and tons of cases and notes and things like that you also have knowledge based articles and things. 67 00:10:54.410 --> 00:10:58.930 Philip Sellers: You know you. You turned it loose on your own data. And 68 00:10:59.577 --> 00:11:10.549 Philip Sellers: you know, that's helpful to your support folks to surface that information. We're seeing that applied to other organizations and their knowledge bases. 69 00:11:11.310 --> 00:11:16.969 Philip Sellers: You know, organizations that are based around research. They're private research research repositories. 70 00:11:17.398 --> 00:11:24.849 Philip Sellers: Yeah, I think we're we're far cry from days of it, solving health conditions for us, because there's a lot of other 71 00:11:24.910 --> 00:11:47.772 Philip Sellers: implications to malpractice and other things like that. But even in the healthcare space you could put it at, maybe billing or coding problems in your billing system. And you know, there's there's all sorts of other things that. You can ask it, and and start to draw out conclusions or information and point to information. So 72 00:11:48.230 --> 00:11:52.539 Philip Sellers: again having it close to those workloads is a a huge benefit. 73 00:11:52.540 --> 00:11:57.249 Andy Whiteside: So, Philip, I'm the more the layman at this point in this conversation with you guys. But 74 00:11:57.490 --> 00:12:05.189 Andy Whiteside: this seems like the workload of all workloads that Nutanix was built to satisfy, to solve for. 75 00:12:06.220 --> 00:12:13.016 Philip Sellers: I think so, because a again, our point has been for a long time right? Nutanix is great for many workloads. 76 00:12:13.630 --> 00:12:17.330 Philip Sellers: and in a lot of ways. It's great for consolidating 77 00:12:17.630 --> 00:12:27.049 Philip Sellers: all of these different types of workloads into a standardized way of operating. And so this is another great example of bringing that all together, and putting a bow on top. 78 00:12:27.490 --> 00:12:33.529 Jirah Cox: Totally agree. Yeah, I mean, it's it's a workload powered by data that requires great speed. That 79 00:12:33.600 --> 00:12:40.700 Jirah Cox: needs some general hardware right? For running containers need some, some specific discrete hardware, for, like Gpus for inferring 80 00:12:42.080 --> 00:13:02.620 Jirah Cox: and for the most part for most companies, you don't build it once you want to be able to rebuild it 10 times a week, 10 times a day. Right? You need that automation, that Cicd framework around it for saying, Oh, there's a new model of Llm blah, blah, that runs my application. Let's put it in a dev environment. Put it in test environment. Put it in prod environment and roll it through that whole lifecycle fully autobatable. 81 00:13:02.720 --> 00:13:16.010 Jirah Cox: and go back to what we talked about, Phil, with our that in us for inference episode, I think, I said, like none of us would use Chat Gpt, if it took 3 min to answer your question right like speed matters right? 82 00:13:16.913 --> 00:13:24.030 Jirah Cox: So there really is no such thing as too fast. When it comes to that, when we're like having a model just ransack terabytes of data. 83 00:13:24.060 --> 00:13:27.570 Jirah Cox: the faster the better to get better, more high quality answers. 84 00:13:28.360 --> 00:13:29.863 Andy Whiteside: It's amazing how we 85 00:13:30.710 --> 00:13:48.519 Andy Whiteside: I don't know how we, our expectations change. I, for whatever reason, I just used copilot to look at my emails from the day that part changed my my world last week, not because they they taught me anything. They just got me thinking outside the box on what I could use them, for which one of which was, Hey, summarize my calendar for the day 86 00:13:48.520 --> 00:14:04.023 Andy Whiteside: like Get out of bed, or like at the end of the day. Hey, what was my email today? What was the important stuff? And you know, I still need to look at it. But there was. It really did a good job of giving me a synopsis of that I did a minute ago, and it took 5 seconds, and I literally was like, what in the world is wrong with this thing. It's taking forever. 87 00:14:05.635 --> 00:14:06.710 Philip Sellers: Yeah. 88 00:14:06.710 --> 00:14:14.080 Ben Rogers: You know, Andy, that's funny, because I'm gonna age myself. Here. Do y'all remember Clippy? In the Microsoft office. 89 00:14:14.080 --> 00:14:14.400 Philip Sellers: Oh, yeah. 90 00:14:14.400 --> 00:14:24.489 Andy Whiteside: Yes. So I listened to a podcast yesterday Mark Benioff, the the salesforce. CEO founder, was talking about co-pilot from Microsoft is just another clippy, and I'm like none 91 00:14:24.960 --> 00:14:26.496 Andy Whiteside: more valuable than that. 92 00:14:26.880 --> 00:14:40.440 Ben Rogers: So, my boss, at the time, who was a visionary, he said, Ben, can you imagine when you get up and you look in the mirror. Clippy comes up in the corner and goes, hey, this is what you got going on today. This is what's important. This is what you need to pay attention to 93 00:14:40.440 --> 00:15:05.359 Ben Rogers: when you said you had it. Recap your calendar. I can just see the little clippy coming up going, hey, Andy, it's bedtime. Here's what's important for you today. Here's what's going to be important for you tomorrow. So that's how I kind of see AI really getting into our lifestyle where it is truly a digital assistant, and we'll remind you and bug you and let you know that these are the things that you need to be paying attention to in your 94 00:15:05.360 --> 00:15:06.290 Ben Rogers: daily life. 95 00:15:06.290 --> 00:15:06.940 Andy Whiteside: Yeah. 96 00:15:07.370 --> 00:15:10.996 Philip Sellers: He sees Ben reach for the comb and goes. Oh, it's a customer meeting day, is it? 97 00:15:11.496 --> 00:15:17.229 Philip Sellers: You know, if it could get me into the right t-shirt for the right vendor for the right day. 98 00:15:17.230 --> 00:15:19.060 Philip Sellers: Right help, too. Right, you know. So. 99 00:15:19.060 --> 00:15:22.520 Jirah Cox: Oh, totally! I could walk in my closet and go like internal calls or customer calls today 100 00:15:23.250 --> 00:15:24.230 Jirah Cox: like the polo shirt. 101 00:15:24.230 --> 00:15:24.890 Ben Rogers: Right? That's right. 102 00:15:24.890 --> 00:15:49.237 Philip Sellers: But I mean, you know, this is the ultimate assistive technology, right? We, we have a lot of things built into our modern operating systems or phones to help with accessibility. But this is ex assistance. This is true digital assistance at its core. And you know, AI comes in all different places, but it really is around making us more productive. 103 00:15:49.650 --> 00:15:55.637 Philip Sellers: And I'm weird the way I said that more productive at the end of the day 104 00:15:55.990 --> 00:16:19.700 Ben Rogers: There is a back back end platform that this AI engine has to run on, and that's where Nutanix has hit the nail on the head of being able to provide that platform. And in a lot of cases with existing customers, with things they have today. And so that's what I'm excited about. Is this AI thing you know the front end of? It's cool. But, man, how you deliver that as a platform is even cooler to me sometimes. 105 00:16:19.700 --> 00:16:38.781 Philip Sellers: Well, well, let's think about that. I mean, it's a great call out to Ben, like, what is the front end for this in a lot of places. It may be somewhere you already interact in your organization. Maybe it's in Microsoft teams. Maybe it's in slack that may ultimately be the front end talking to an Api that's hosted back in the Nutanix. 106 00:16:39.080 --> 00:16:51.610 Philip Sellers: We may not be talking about going to a chat gpt like web interface. We may be using this in our daily productivity tools. I think that's even more powerful when you can bring something like this to the 107 00:16:51.660 --> 00:16:54.889 Philip Sellers: day to day of what someone's already consuming. 108 00:16:55.300 --> 00:17:01.009 Ben Rogers: Man. We have a customer that is re-engineering their production floors. 109 00:17:01.020 --> 00:17:25.220 Ben Rogers: and they've actually gone and looked at the footprint of their production devices. And they're able in this software to like move the whole floor around. So before they even move a lick of equipment, they've got the square footage of the building all the components in that building. And they're actually using an AI model to see, where is it most efficient to put this stuff in this line building. So, man, it's happening today. Dude, it's cool stuff. 110 00:17:25.220 --> 00:17:31.710 Ben Rogers: really cool stuff. I've heard AI be considered to what electricity has done for the human man. 111 00:17:31.710 --> 00:17:40.459 Ben Rogers: You know, human being, that this is the next. You know, big wave of technology, that face and the things I've seen. And I'm I'm not a doubter at this point. 112 00:17:41.640 --> 00:17:45.510 Philip Sellers: I guess ultimately it's gonna be a time will tell sort of story. 113 00:17:46.040 --> 00:18:10.231 Philip Sellers: Yeah, there, there is more, though, that we have from Nutanix or from Microsoft ignite and so I don't wanna shortchange. The other 2 big announcements that we were talking about next up is is databases, and I love this topic because Ndb, I think, doesn't get nearly enough spotlight. So I love that we're talking more and more about nutanix database 114 00:18:11.200 --> 00:18:34.739 Philip Sellers: for a lot of people listening. Nutanix database, even though we've talked about it before, may still seem a little weird. It's not a core infrastructure. It's not like vmware we're talking about databases. We're talking about middleware places where data resides. And so I get the feeling that a lot of people find it odd that Nutanix is playing in the data space. But, Jaira, why is that. 115 00:18:35.300 --> 00:18:41.200 Jirah Cox: It's because we're a cloud platform and cloud platforms have advanced services right? Like it shouldn't just be a matter of 116 00:18:41.360 --> 00:18:49.910 Jirah Cox: humans. Go build vms. And then other humans put database engines on those manually forever. Right? Faster time of value, more automation services. 117 00:18:50.336 --> 00:19:16.919 Jirah Cox: Is the value of cloud, right? Or of any kind of mature cloud platform, including ours. So yeah, so ndb, which is our nutanix database service in its core, right? Helps our platform owners to to create inventory power outage over here. But ups is going strong. They helps our platform owners to offer their customers right database as a service anywhere that they want to operate. 118 00:19:17.170 --> 00:19:22.420 Jirah Cox: and with ndp. My usual high level summary right is like 119 00:19:22.510 --> 00:19:35.700 Jirah Cox: helps you provision faster, protect those databases faster, patch those databases faster, and recover whenever you need to recover from like a human oopsie, or from a kind of data, loss, event, or malware, or anything right? 120 00:19:35.820 --> 00:20:05.099 Jirah Cox: So all the kind of things that are like. I said I'd call back to more complex operations that we make more accessible right? I can click a button and patch my database without being an expert in doing that, because I can just have my database. Follow my organization's guidelines and blueprints and recipes for hey, we're moving to this version of SQL. In this patch release click here to have your database align with that declarative standard right? And it's just easier for me as now. Maybe an app owner 121 00:20:05.100 --> 00:20:30.099 Jirah Cox: to get in line with that right without needing to go bug a dba for something like patching right? So the cool part here now is that Ndb, our database service can now provision onto Nc. 2 and azure. So when you have your hybrid cloud stretching into azure powered by Nutanix, that now also can be a super valid deployment target for Ndb. And can also attach to flow virtual networking. So the same way I can stretch networks now 122 00:20:30.100 --> 00:20:44.080 Jirah Cox: from on-prem a lot of boot camp. For this last week we took customers, and in about 90 min we went from on-prem static IP address to moving those vms across to another cluster that didn't have that same Vlan available to it. 123 00:20:44.180 --> 00:20:53.559 Jirah Cox: Static IP just worked so like we could. We could move your vms today, if you wanted to, into cloud, get you there faster. But now also not lose that governance model with Ndb. 124 00:20:54.950 --> 00:21:01.320 Philip Sellers: Well, 2 things that I love about Ndb as a platform really come in play. When we're talking about app dev 125 00:21:01.400 --> 00:21:17.799 Philip Sellers: combined with Ndb, and it's copy data. So you can order up things through the Api or through a user interface. If you're an app developer and you need a copy of a database. Well, now, that's at fingertips. No tickets. It's no 126 00:21:17.910 --> 00:21:24.660 Philip Sellers: waiting. It's near instantaneous, because you're tapping into all the goodness of the underlying storage subsystem right? 127 00:21:24.842 --> 00:21:25.570 Ben Rogers: In the West baby. 128 00:21:25.570 --> 00:21:28.170 Philip Sellers: You know, Aos for the win. 129 00:21:28.370 --> 00:21:49.410 Philip Sellers: and then the other thing is is being able to then take that and extend that into automation. So app dev platforms, pipelines, automated testing. You know, data has to be a part of the total application landscape. Now, when you're testing those things out and doing things. You can do that automatically. With the 130 00:21:49.801 --> 00:22:00.759 Philip Sellers: pipeline integrations against Ndb. So I I love to call those things out because I came from a large at dev before joining integra. And so 131 00:22:00.760 --> 00:22:11.419 Philip Sellers: data is a tough layer to handle. You know, Ben, I know you get really excited talking to customers about Ndb. You know what what sorts of things 132 00:22:11.500 --> 00:22:13.600 Philip Sellers: resonate most with them. 133 00:22:13.910 --> 00:22:25.909 Ben Rogers: Well, so the one thing I would like to go to before I answer that is man. I think the way Jaira described Ndb was very eloquent. I'm a little more, you know, core, and 134 00:22:25.930 --> 00:22:40.819 Ben Rogers: our management of data is really kind of where Ndb bubbled out of. We understand the zeros and ones. So you're you're mentioning of, you know, test dev app deployment, being able to snapshot the database real quickly and then anonymize it. 135 00:22:40.820 --> 00:22:59.990 Ben Rogers: All of those things are really what bring that to the table. But they all come down to Aos, and our ability to manage the zeros and ones, and where the zeros and ones need to reside and where they need to be. And so that's where I see customers getting excited in 2 things, and I'll go back to. You know, our Nkp product. 136 00:22:59.990 --> 00:23:07.030 Ben Rogers: The reason that the Nkp people love us is that we brought a storage platform that they can now leverage. 137 00:23:07.030 --> 00:23:31.600 Ben Rogers: and that's where customers are really digging. Ndb. Is that they now can leverage the same goodness they get with Aos. But now they can do that in a database sense and the ability to patch the databases, the ability to look across your SQL landscape and go. Okay, I've got multiple versions of SQL out there. I need to make sure they're all patched at a level so that I can come back to a compliance standpoint 138 00:23:31.600 --> 00:23:49.750 Ben Rogers: and feedback to my company, that we're compliant for security reasons, Yada, Yada Yada. So again, man, understanding where the zeros and ones are being able to deliver those zeros and ones in the way our customers need, and then being able to manage. That is really, I think, what the power of the database engine is for us. Ndb. 139 00:23:49.940 --> 00:23:59.239 Jirah Cox: Well, and we're in the business of helping customers get where they want to go faster. Right? So in your stuff is, call it, you know, all in in one place, all within your 4 walls today. 140 00:23:59.300 --> 00:24:23.529 Jirah Cox: But you want to get to cloud as fast as reasonably possible. This helps you can get. This helps you get those databases there way faster, right like I can. Now take those databases running on Nutanix. Take a snapshot, make that instantly available over in azure or even use both. Right? I can have one data center. That's for test dev, one that's for production. Maybe I do production in the cloud test dev on prem, either. These are totally valid in my data. Landscape now stretches wherever I go. 141 00:24:24.570 --> 00:24:34.710 Philip Sellers: Yeah. And and to me, like, you know, when when I think about the nutanix platform, Lcm in particular comes out, you know lifecycle management. When Nutanix is in 142 00:24:34.760 --> 00:24:39.960 Philip Sellers: control, you're getting the best practices. You get the correct order of operation. 143 00:24:40.230 --> 00:25:07.580 Philip Sellers: You're making it accessible back to that flag we planted earlier in the podcast you're making difficult things accessible. And I think Ndb is another one of those. Now with a generalist team, not a team of highly skilled expert database administrators. You're able to get outcomes where their best practices they're going to pass audits things like that in addition. How accurate am I on that. 144 00:25:07.850 --> 00:25:14.520 Jirah Cox: Totally. Totally. I mean not just. I mean, we can keep it kind of sequel themed, because this is the ignite recap. 145 00:25:14.780 --> 00:25:29.149 Jirah Cox: But think about how many customers run 90% SQL. But a little bit of other things right? Some postgres, or some mongo or some oracle, and so that standardization of like look. The habit is, go to Ndb, click the patch button and know that it's going to do what you need to do in the back end, whether it's 146 00:25:29.240 --> 00:25:52.840 Jirah Cox: SQL. Single instance, or Ag. Or Fc. Or the Postgres, or the Maria, or the Oracle, or whatever like my team's in the habit of. I go to the dashboard click, patch right like that's pretty high value of like abstraction, not having to go like crack open the manual. And how do I do this one again just because it's a 1 off. I get that that simplicity of I do everything. Quote the same way because I do it all through Ndb 147 00:25:53.070 --> 00:26:05.589 Jirah Cox: or recover the same, or patch the same, or replicate the same. Because I can just move this data around wherever I choose to. So yeah, I think it's a pretty apt analogy to kind of compare it to Lcm of like, let it do the right thing for you the same way every time. 148 00:26:06.070 --> 00:26:06.630 Philip Sellers: Yeah. 149 00:26:07.860 --> 00:26:21.229 Philip Sellers: you know, Andy, you you say you're the novice in the room today. But as we're talking about Ndb, I mean, like you've been around databases from the very early days, you know. Every single citrix app. 150 00:26:21.230 --> 00:26:21.920 Jirah Cox: Ouch! 151 00:26:21.920 --> 00:26:28.570 Philip Sellers: Installation. We've we've had databases as a persistent part of our world, right? 152 00:26:28.930 --> 00:26:34.839 Philip Sellers: Making that easier. I mean, how much does that sound like the amazing thing. 153 00:26:34.840 --> 00:26:55.429 Andy Whiteside: If you'd have told me before this AI thing happened. What's the best workload for this extensible in the cloud on Prem, in a partner's data center. You know this thing that could go anywhere you wanted to. Aka hyperconverged the thing that Nutanix, you know, created for all of us. I would have told you that a database. 154 00:26:55.430 --> 00:26:55.810 Philip Sellers: Isn't. 155 00:26:55.810 --> 00:26:58.450 Andy Whiteside: Other workload that makes the most sense. 156 00:26:58.450 --> 00:26:58.910 Philip Sellers: Yeah. 157 00:26:58.910 --> 00:27:08.030 Andy Whiteside: And that's coming from the Vdi guy that's like, hey? If you don't, if you run Vdi, and you don't run it on a hyper converged solution like Nutanix. Well, you're totally missing the mark. Database. 158 00:27:08.270 --> 00:27:13.020 Andy Whiteside: you know. Once that became a reality in the nutanix world is even a better workload. 159 00:27:14.010 --> 00:27:14.690 Philip Sellers: Yeah, yeah. 160 00:27:14.690 --> 00:27:24.759 Jirah Cox: I was in a briefing last week and learned that something like 90% of all customers actually run databases on our platform. It actually probably is eclipsing Vdi as our our most applied workload. 161 00:27:26.100 --> 00:27:31.382 Philip Sellers: And I can believe that I mean data rules the world, right? I mean, everyone has this need. And 162 00:27:31.730 --> 00:27:37.749 Philip Sellers: you know, we go there to prove out what's a high performant platform 163 00:27:38.194 --> 00:27:48.515 Philip Sellers: we have tons and tons of tests around it, and that's it's it's an easy way to prove out that you can you? You've got the real chops. You got the real deal for infrastructure. 164 00:27:49.060 --> 00:27:50.770 Philip Sellers: It's a great, great call out, 165 00:27:52.140 --> 00:28:02.620 Philip Sellers: But that's not all that we have. We also have some more. Nc, 2 news, and so we'll keep going close out the blog post from Microsoft ignite. But 166 00:28:03.130 --> 00:28:07.349 Philip Sellers: continuing innovation around Nc 2, Jaira, I'm gonna throw it to you again. 167 00:28:07.570 --> 00:28:26.700 Jirah Cox: So some good quality of life improvements here for Z. 2 and azure, which is how we can get bare metal nodes out of the azure cloud. Use them to build a new Tnx cluster, to run our customers, workloads. It runs just like any other new Phoenix cluster either in a service provider environment like integra, or in your own data center 168 00:28:26.860 --> 00:28:42.360 Jirah Cox: behind your own firewall. You can now run Nutanix, of course, and you've been able to for years run it in the azure environment. Now, with an enhancement to be able to support user defined routing. So now, like even more of those kind of customizable. I need this traffic to go to certain kind of ways of custom. Routing 169 00:28:43.070 --> 00:28:50.749 Jirah Cox: makes it more useful for virtual appliances as well. When I want certain things to get hair pinned, or certain kinds of of inspection to occur on that traffic. 170 00:28:50.810 --> 00:28:59.470 Jirah Cox: and then kind of the usual, what's new with Nc. 2. Now I can run it more places, right? So enhancing availability in Uae and also India Central 171 00:28:59.480 --> 00:29:07.299 Jirah Cox: as well. What's cool about Nc. 2, right is when you run nutanix on Prem, you basically buy servers, you buy licenses, you deploy it all 172 00:29:07.390 --> 00:29:11.289 Jirah Cox: in Nc. 2. You actually can blend some of that. Maybe I own 173 00:29:11.340 --> 00:29:16.320 Jirah Cox: a pilot light cluster. I do a multi-year commit and use part of my Mac and all that good stuff 174 00:29:16.350 --> 00:29:21.529 Jirah Cox: for building that environment and using it against my traditional committed funds. 175 00:29:21.690 --> 00:29:34.309 Jirah Cox: Maybe when I want to have a want, want is the wrong word. When I have a declared disaster for Dr. I can get additional nodes in more of a pay as you go by the hour model. Right? So I get to rent part of my Dr. Environment only when I need to 176 00:29:34.400 --> 00:29:40.450 Jirah Cox: and go back to minimally viable after the disaster is over. So I just have some replication targets set up there as well. 177 00:29:41.040 --> 00:29:42.779 Jirah Cox: So some really good flexibility. There. 178 00:29:43.680 --> 00:30:03.696 Philip Sellers: Yeah. And and I will add, I mean that Nc, 2 is a great place to run these workloads. And it's not the only place. There's also service providers like integra gotta throw a plug in there, too, right? And we we offer very similar things, and and it gives me a good opportunity to kind of share and brag on the team. We had a 179 00:30:04.100 --> 00:30:21.969 Philip Sellers: an unplanned outage like you said not something that you ever really want. But it came in as an email and email request came in and and I saw the email. And it says, this is not a test. And so you know it's bad when the the customers coming to you going, this is not a test. This is, this is not a drill. 180 00:30:22.950 --> 00:30:32.420 Philip Sellers: And in 20 min we had everything failed over and their users logging back into Citrix. The technology is extremely powerful 181 00:30:32.918 --> 00:30:41.160 Philip Sellers: being able to do that and map out and test full Dr. Recovery, whether that's Nc. 2 or managed service provider like us. 182 00:30:41.440 --> 00:30:58.219 Philip Sellers: the underlying Nutanix provides us with an incredible platform to orchestrate that, and to have a successful outcome. And so, you know, these are great use cases again, where you don't necessarily have to make that capital investment in a second location. 183 00:30:58.410 --> 00:31:21.840 Jirah Cox: I mean, it's to call back. It's that 3rd area of helping people get a complex outcome done more simply and faster. I won't say fastly, I'm going to put that out there because it's like I want to use cloud for Dr. I want to move my production to cloud faster. And then we're like, let's go right like we can move your vms today if you want to. We can help you use Cloud as a Dr. Target, which is 184 00:31:21.840 --> 00:31:38.359 Jirah Cox: one of the most common desires I see customers starting with, for, like what I want to do with Cloud, let's use it as a dear target. Get rid of that second data center, move that into a cloud environment and we're here for it. Right? We help make that happen more fastly. I'll own that, and and more simply as well. 185 00:31:39.230 --> 00:31:46.100 Ben Rogers: See more customers leveraging Nc. 2 for Robo. So I mean, I'm working with a customer in Asia 186 00:31:46.100 --> 00:32:11.859 Ben Rogers: that they're looking at moving their remote sites that are in the Asia pack into in C 2 clusters in azure, because we're building out more in that environment. And it makes sense. And you know, they're they're reducing their real estate. They're going to more of a subscription type model, which is where the company obviously want to go, and we're able to deliver next to where the workloads are and their users are. So that's all. Good wins for the customer and for Nutanix and for azure. 187 00:32:12.420 --> 00:32:15.513 Philip Sellers: Well, you know, I having past experience offshoring 188 00:32:16.210 --> 00:32:23.090 Philip Sellers: it. It may be a very viable use case where you will never have hands in Asia pack. 189 00:32:23.110 --> 00:32:34.240 Philip Sellers: You will never have people on the ground. But you have constituents, consultants, 3rd party contractors. You're delivering services to. You need to be in their region. 190 00:32:34.290 --> 00:32:40.840 Philip Sellers: It is an extremely valid cloud. Use case to extend your geography. 191 00:32:41.310 --> 00:32:48.329 Philip Sellers: Let someone else handle everything below that. Nc 2 layer, and then you handle the things that matter on top 192 00:32:49.006 --> 00:32:54.580 Philip Sellers: where you can arguably provide more distinguished value to your company. 193 00:32:54.840 --> 00:33:14.479 Jirah Cox: I think I've said it at some point on the on the podcast, right, like, in my opinion, running nutanix on a hardware as a service platform really like completes the initial vision of Nutanix. Right? We already assume that hardware in a long enough timeframe is gonna fail. We don't tightly couple to anyone hardware node, we can fail forward, we can rebuild. 194 00:33:14.640 --> 00:33:38.370 Jirah Cox: we do software, defined self healing in place. So when I can get a new node as a service. Right? I don't care about that, failed dim that failed. Power supply that that downed motherboard. I give that node back to the Cloud provider. Now it's their problem. I get a new healthy one, and that's now part of my cluster, and I'm back to normal right? I don't go get a new tire. A new tire just appears for me. I put it on the car and keep on driving. 195 00:33:38.370 --> 00:33:58.890 Jirah Cox: The analogy breaks down. Sorry, but same thing with patching. Right? I don't do bios updates in the cloud. Right? I go. Request a new prepatched node from the cloud provider that already has their new. Whatever new recipe for hardware success prepatched at the time, cluster and inject an older one that I don't need to go, patch. It's not mine anymore. So it's really a really cool paradigm in a way that 196 00:33:59.250 --> 00:34:06.810 Jirah Cox: you know, owning nutanix on-prem running tennis service provider doesn't quite get me as abstracted from a look. It's just hardware as a service. 197 00:34:07.610 --> 00:34:14.899 Ben Rogers: So I'm gonna give a call out to my boss here, Tom Powell, he drills into our heads that we're a software company. 198 00:34:14.900 --> 00:34:39.559 Ben Rogers: We're not a hardware company. And sometimes this, he's look back at him. Go, yeah, we're a software company that's dependent upon hardware. With the Nc. 2 story. He is absolutely correct. This is us at software at its finest, with infrastructure, hardware being provided to it that we really might have a knowledge of or might not have a knowledge of, but again to his point. And if he's listening to this, I hope he has a grin. This does define Nutanix as truly a software company. 199 00:34:42.260 --> 00:34:57.460 Philip Sellers: Yeah, well, and and you're breaking that dependency right? Everything else we've talked about, you know, lives directly on the Nutanix platform. But there are lots of things you guys are working on, you know. Files now can run natively in cloud. 200 00:34:57.480 --> 00:35:06.349 Philip Sellers: You get all the same. Goodness. So you're starting to see a paradigm shift within the company, too, that you're getting more and more native services that are closer to cloud 201 00:35:06.906 --> 00:35:20.099 Philip Sellers: but arguably, Aos for the win right. And we said it earlier. A lot of this innovation is powered by that core storage subsystem. So yes, you are really a storage company under the covers. But 202 00:35:20.270 --> 00:35:29.210 Philip Sellers: as a cloud company to Jairus Point earlier. It's all about the services that you can deliver, and you're delivering the services that people need. Whether that's 203 00:35:29.270 --> 00:35:31.349 Philip Sellers: nutanix enterprise. AI, 204 00:35:31.640 --> 00:35:45.359 Philip Sellers: whether that's databases disaster recovery as a service across the board. You're giving lots of choice. Nkp, I heard a shout out for earlier. You've got all the high level services that a customer is looking for 205 00:35:47.300 --> 00:35:50.470 Philip Sellers: any closing remarks before we wrap it up today. 206 00:35:52.060 --> 00:35:54.490 Ben Rogers: It's a good time to work for Nutanix. Man, we're busy. 207 00:35:54.730 --> 00:36:00.129 Ben Rogers: The the market is is is doing good for us. So, man, we're excited about the future. Here. 208 00:36:01.350 --> 00:36:08.749 Jirah Cox: If we missed you at ignite. Sorry about that. Call your intense account team. Call yours integra account team for a personalized recap. 209 00:36:08.750 --> 00:36:09.570 Ben Rogers: Yeah, no doubt. 210 00:36:09.570 --> 00:36:11.970 Philip Sellers: I'm I'm just gonna highlight that. 211 00:36:12.400 --> 00:36:16.889 Andy Whiteside: You know, Nutanix having what they have, being where they are at this moment in time. 212 00:36:17.150 --> 00:36:19.939 Andy Whiteside: is, you know, a lot of dedication, hard work 213 00:36:19.990 --> 00:36:38.340 Andy Whiteside: fortuitous timing with the idea that the guys over at Vmware we're not doing this in the hyper converged motion in the one foot in the cloud, one foot into the data center, one foot in the semi-private data center, or wherever you want to put it with the software driven approach. I mean, it's all just kind of working out 214 00:36:38.490 --> 00:36:42.280 Andy Whiteside: to be at the right time, right place, the right motions, right investments. 215 00:36:42.280 --> 00:36:53.580 Philip Sellers: Yeah. And and I like to point out as we're doing lunch and learns and stuff around the country right now, there's differentiated value here, you know, there there are places Nutanix playing that those other guys aren't 216 00:36:53.640 --> 00:36:57.539 Philip Sellers: vmware has been really happy in the infrastructure stack. But 217 00:36:57.580 --> 00:37:04.380 Philip Sellers: things like database and you know some of the the differentiated value directing cloud. 218 00:37:04.752 --> 00:37:17.340 Philip Sellers: They're not playing in that space today, and I I don't see it anywhere in the roadmap right now. So there are places where you guys are ahead, too. So that that's also cool to see. And it's 1 of the reasons why 219 00:37:17.460 --> 00:37:20.589 Philip Sellers: we we like to go to market with our Nutanix partner. 220 00:37:20.820 --> 00:37:29.599 Jirah Cox: I think it's only gonna get going to get more fun. I mean, thanks to you guys, thanks to our customers, you guys have helped us get where we are not just financially, but also really through feedback right? Like half of our 221 00:37:29.610 --> 00:37:36.959 Jirah Cox: half our product announcements come from customer direct requests and and feedback. So it's all super important to us. But 222 00:37:37.000 --> 00:37:42.449 Jirah Cox: if we're all dusting off our crystal balls, I think in the next, I don't know. Call it. 1218, 24 months. 223 00:37:42.940 --> 00:37:57.730 Jirah Cox: We're comparing it now in this theme of like, basically a 2 horse race. I think it's gonna get absolutely silly. Right? It's gonna be a 10 horse race like everyone, and their uncle is launching a hypervisor. What? Standby for an announcement for a new gyro visor or something like that like it's they're everywhere, right? 224 00:37:57.964 --> 00:38:00.305 Jirah Cox: Wanna buy into that one. Can I buy into that? 225 00:38:01.350 --> 00:38:05.519 Jirah Cox: The I don't know no features. It just comes with barbecue sauce, or something. 226 00:38:05.520 --> 00:38:07.989 Andy Whiteside: I just want to see the logo. 227 00:38:08.210 --> 00:38:15.659 Jirah Cox: The chaos. I think that we're going to see in the industry around. There's so much of this fracturing ecosystem. 228 00:38:15.740 --> 00:38:26.410 Jirah Cox: I think that the light of like a valuable differentiated solution is only only going to get brighter right? It's gonna be even becoming more of a standout around. Lots of other people like. 229 00:38:26.640 --> 00:38:31.539 Jirah Cox: you know, we're here talking about a platform here that has roots that go back 10 to 15 years. 230 00:38:31.600 --> 00:38:36.019 Jirah Cox: If we're starting a new platform today in 2024, and we're like, look, it's a new hypervisor. 231 00:38:36.900 --> 00:38:39.190 Jirah Cox: Good luck! Best of luck! 232 00:38:39.320 --> 00:38:57.829 Ben Rogers: Well, and I also think that man Kubernetes and containers, the doctor containers, and all that that's going to change. You know, companies are going to have to embrace that. Some companies are already on that model. Some companies are resisting that a little bit. But AI is going to push that container environment. And you're already starting to see that happen. 233 00:38:58.350 --> 00:39:02.059 Philip Sellers: Well, and and let's go back to the flag that gyra planted at the beginning. 234 00:39:02.110 --> 00:39:09.910 Philip Sellers: It needs to be more accessible. That's the thing with Kubernetes. It's inaccessible for most places 235 00:39:10.260 --> 00:39:21.769 Philip Sellers: in the packaged formats that it's existed to date. And so it's good to have you guys partnering to make it more accessible, because that's a very needed valid need in the marketplace. 236 00:39:22.463 --> 00:39:25.029 Philip Sellers: You! I've tried it with 237 00:39:25.940 --> 00:39:35.230 Philip Sellers: 6 different platforms, hands on trying to figure out, how do we? We make it happen, and there are arguably 238 00:39:35.250 --> 00:39:59.629 Philip Sellers: 2 to 3 that have a complete vision when it comes to to making the full Kubernetes stack work. But it's incredibly different. Taking a team through this, it takes years of retraining, getting used to the new way and paradigms of deploying and managing the infrastructure. It's not easy, and so I never go into a customer conversation and understate 239 00:40:00.020 --> 00:40:02.499 Philip Sellers: how difficult it is to turn that curve. 240 00:40:02.500 --> 00:40:11.730 Ben Rogers: Yeah, like, I'll give you an example. I just went through some of our in AI training, and words mean different things in different platforms like even cluster. 241 00:40:11.830 --> 00:40:32.739 Ben Rogers: Are we talking about a new traditional nutanix cluster? Are we talking about an Nkp cluster? And so some words in the environment can mean different things. So you're absolutely correct. But that is one thing that Nutanix does good is, it makes sense of these difficult topics and difficult configurations. And so I think that's where we're going to win. And customers are starting to really see that. 242 00:40:33.140 --> 00:40:36.540 Philip Sellers: I I thought you were. Gonna say, cluster meant something else. 243 00:40:37.260 --> 00:40:39.520 Philip Sellers: Amazing namespace pollution. 244 00:40:39.842 --> 00:41:06.590 Philip Sellers: Well, on behalf of this integra team, and, thanks to Jira and Ben joining us from Nutanix. I wanna say, thanks so much for joining us on this episode of the podcast you know, if you've got a partner out there that's not adding value to your world. Give us a chance, give us a call, and we would love to work with you and partner with you, and and see what we can do to add value to your world 245 00:41:06.800 --> 00:41:15.849 Philip Sellers: on behalf of Andy, and everyone else want to say thanks for joining us, giving us your time, and we will catch you on the next episode of and excuse me, Nutanix weekly.