Hello again and welcome to the sequel to the first screencast where we're looking at a family of functions, two-parameter family of functions f of x equals a times square root of b minus x squared where a and b are positive and we had done in the first screencast we found the domain of this function we found its critical values and we found where the function is increasing and decreasing and we found that every member of the family has a local maximum value at x equals zero of value a times square root of b. Now we want to move on to think about second derivative information namely we're going to find the intervals where this function is concave up and where it's concave down once we've done that we should be able to identify the inflection points very easily. This involves a fairly lengthy second derivative calculation so if you want to see that please hang on if you don't want to see that just scan through to the end where you get through the result. Now to set this second derivative calculation up I'm going to take the first derivative and just rewrite it slightly to make the derivative taking a little easier so f prime of x instead of writing it as a fraction with a root on the bottom I'm going to write it as negative a x times b minus x squared the quantity to the negative one-half power that's going to make derivative taking a little simpler. Now when I go to the second derivative of x again a and b are constants and particularly I have a multiplied constant right here in negative a so the first order of business for me is I'm going to pull out this negative a and take the derivative of what's left over so this is going to be the derivative of x times the quantity b minus x squared to the negative one-half so just to strategize before we go over to the next page and begin this is going to involve a product rule situation because I have two things multiplied together and the second thing is going to involve the chain rule because it's a composite function like I said this is a good recap of what you know about derivatives so watch onward if you want to see that. Okay so let's proceed with the derivative here the negative a is just hanging out here in front it's a multiply constant so the first thing I need to do is use the product rule to take the derivative of x times the expression in the one-half power so this is going to give me the derivative of x which is one times the second function which is b minus x squared to the minus one-half plus x times the derivative of b minus x squared to the minus one-half that's going to need the chain rule so let me switch to a different color to indicate the chain rule portion of this the chain rule I would take negative one-half times the outer function to the negative three-halves power with the original inner function put into it times the derivative of the inner function remember b is a constant so it differentiates to zero and the remaining derivative would be of negative x squared that gives me minus 2x and close that outer parenthesis let's do a quite a bit of cleaning up here to see what we can get done one thing I see is that the negative one-half times the negative two both of those completely divide off so and the one of course multiplying by one doesn't really do anything so I have negative a times let me write this all just the parenthesis portion here b minus x squared to the minus one-half plus let's see I have an x from here and then everything else there's another x down at the end so that's actually x squared and then I have this this expression here to the three-halves it's b minus x squared to the minus three-halves now let's try to simplify this expression as much as possible it may not seem like a good idea but it is actually going to be helpful to take the negative powers here the negative one-half and the negative three-halves and turn those into fractions with roots on the bottom so let's do that negative a times big parenthesis b minus x squared to the minus one-half is one over square root of b minus x squared plus I have an x squared over b minus x squared to the three-halves all right there we go now if I multiply the a the negative a through let's just do that real quickly I would have negative a over square root of b minus x squared minus or let me write it as this plus negative a x squared over again not really a root but negative or b minus x squared to the three-halves now what's going to be helpful for us here is to get common denominators on these fractions to kind of put them together so remember that I could just as easily instead of writing a square root here let me just erase that off I could have very easily rewritten this as b minus x squared to the one-half power now what's the common denominator the common denominator would be b minus x squared to the three-halves and I would get the common denominators by taking this first fraction and multiplying the top and bottom by something let me scoot that equal sign over if I multiply the top and bottom of this thing by b minus x squared to the first power then that's just multiplying by one that doesn't change the fraction but notice that's going to give me common denominators on the bottom because b minus x squared to the first times b minus x squared to the one-half is b minus x squared to the three-halves so on the next page I'm going to continue that calculation and we'll simplify this down completely so let's carry out the multiplication step that you see here on the top of the fraction on the left here I'm going to have negative a times the quantity b minus x squared and on the bottom as we discussed I'm going to have b minus x squared to the first times b minus x squared to the one-half that's b minus x squared to the three-halves now on the second fraction I have negative a x squared over b minus x squared to the three-halves okay so now we have common denominators I can add the numerators so multiplying this negative a uh through the first set of parentheses gives me negative a b plus a x squared this is all going to be over b minus x squared to the three-halves now look at what I'm adding I'm adding on a plus negative a x squared adding the numerators and so this is a really nice simplification these two guys just simply subtract off from each other and here's my final answer this is really worth the simplification step because it comes out to be nice and short negative a b over b minus x squared to the three-halves and that's your second derivative that's a fairly lengthy calculation obviously but every step is just basic derivative techniques carrying it out in algebra now what were we supposed to do with this second derivative we were supposed to use it to determine where the original family of functions was concave up and where it's concave down and then try to find inflection points now where is this function concave up well function is concave up whenever its second derivative is positive and concave down wherever its second derivative is negative so let's take a look at the second derivative expression here and just analyze its sign now on the bottom of this fraction in the denominator I have a quantity raised to the three-halves power a quantity raised to the three-halves power is always going to be positive because three-halves power means I'm cubing something and then taking a square root a square root never outputs a negative result and so that's always a positive number on the bottom on the top notice what happens here I've got a times b now at the very very beginning of this problem we said that a and b are both positive numbers so a times b is always positive therefore the numerator of this fraction which is minus a b is always negative so no matter what the x is no matter what the a is no matter what the b is and this function the second derivative of my family is always negative because I'm always taking a negative quantity divided by a positive quantity so what this tells me is that f is always concave down always concave down there's no value of x that makes f double prime positive f double prime is always negative so f is always concave down therefore there are no inflection points because an inflection point is where the concavity of f changes never changes so no inflection points so there's actually a fairly quick answer although we had to do a lot of algebra work to get to it so that pretty much fully specifies the family of functions here in terms of critical values increasing decreasing behavior concavity is very simple as a parting shot here let's go to geogibra and actually take a look at this family of functions and see if the behavior that we see actually fits with the calculations we made so as you can see here in geogibra I plotted the family of functions here using sliders to change the parameters here all the things that we calculated about this family turn out to be correct as you can see the domain of the function goes from negative screw to b to positive screw to b here's the value of screw to b right there and you can see it does actually fit as you change the b the domain gets larger or smaller the function is increasing from the left end of its domain up to zero and then decreasing until we get to the right end of the domain notice that the critical value there is at x equals zero and the local maximum value is always equal to squared of a times b you can change that either way you can see the parameters do different things to this function but some things always remain the same we also see that the function is always concave down sometimes increasing concave down and decreasing concave down but never concave up so there's no inflection points on the graph of this function and the great thing is we didn't need the visual to tell us this we found it completely through our use of the calculation tools that we know thanks for watching


In today's video, I'll show you how to create a breakout scan like Christian Kuala Maggie for completely free using FinViz. But before we do that, a quick reminder that all the best tools for day trading and investing will be linked down in the description. Let's get into it. So if you're watching this strategy, I would assume that you already know who he is. And the reason why you want to follow his strategy, it's because he's one of the biggest trader out there that's public with his strategy. A lot of big trader don't want to share what they know about the market. So he was kind enough to really share the setup that he trades. You can go on his website and he has a really big detail breakdown on everything you need to know about his setup. And also, if you want to know how big he trades in 2021, his account was at 82 million. And there's a lot of information about who he is and how much he made because he was the 15 biggest earner in Sweden and this is public knowledge. You can find it online. So when it comes to a strategy, the main thing that he trades are breakout on larger cap because he has such a big account. But you can take his exact strategy and just apply it to small cap stock is going to do the exact same thing. So we're going to go over the setting to find really big trade like we had on SMCI. When he broke out of that 356 and it went all the way to 1100. We also had AMD, which was a really good trade. When he broke out of this range right over here and then it went all the way to 220. We had NVIDIA. That was also a very good one when it broke out of this range over here and then it went from 500 to 900. These were more obvious because it was a sector, so it was semiconductor. But sometimes the first breakout in a sector is not the easiest one to find. So that's why we do need Screener to show us what's really happening in the market and how we can find these plates. How we're going to do this is using the Screener on FinViz as I mentioned in the intro of this video because it's completely free. By the way, if you enjoyed this video and you're getting value from it, don't forget to like and subscribe. I also did link all the best tools for trading and investing down in the description. Don't forget to check that out. Let's get back in the video. Something that's annoying is FinViz has a lot of ads. You're going to see pop-ups all the way on your screen. And if you want to remove a lot of them, what I do for anything that's trading relating is I use this browser called Torium. It's a light version of Chrome, so you don't have all the bells and whistle and also blocks all the ads by itself. So the only ads you're going to be able to see is the one from FinViz actually and not from like random website, which is a lot better. And it's also a lot faster if you're looking for a faster browser. So the next thing we're going to do is click on Screener. And what he mainly looks for is stuff that are leading in some sector or some time of time period. So the best way I found to do this using this free tool was really about going into all and then I did over here. It was the performance. So you want to look for performance is going to be right over here. And then what you're going to do is you're going to look first of all for the week. So you want something that's up at least 10% on the week. And then you want some volume. So the current volume is going to be right here. So we can see current volume. And then I want something over five million. This is for me. If you want to pick something wider because you look at more expensive stock, look at one million. The next thing I want to do is look at the volatility on the week. I want it to be over 3%. So I want something with a decent range. This sometime you can just add it to your filter and remove it just to make sure you're not missing anything. But generally speaking, it's going to be the best thing to see what has more volatility and not something that's just not moving or anything like that. And then the next thing we can look for market cap. I'm not going to do market cap yet. I'm just going to go to the one I have for me for the week because I did save it. And if you want to save something when you create the filter, you want it. Just going to save screen and then you can just save it over here with the name that you want. And even if you have the free version is going to remember the screen that you created, which is amazing. So going back to the screener we created, this is going to be the weekly. The weekly is going to be more for stuff that are in trend and having momentum at the moment. But it's really good for shorting stock, which is not really his strategy. But if you're looking to find parabolic, it's going to help you do that. So I'm looking for a week over 10% over 10 million. And like I said, a week over 30% in volatility. And the next thing you want to do is just click on performance at the bottom right over here. And then you're going to be able to click performance per week, which is going to be right over here. So you want to make sure that you're following this order. So the top leader for the week. And then you're going to be able to go in TA and just see all the tickers that are making this big move for completely free and it be able to follow them. From that point on, when I have a list or I see all the tickers I'm supposed to see, I really just scroll through pretty quickly. You know, everything that's happening or everything that's in play. And then when something is important or looks like really in play, I'll go into my platform and I'll set some alert at the price that I want to see them. For example, ACB, you know, I can see that it's in play. If we get above this 761, I want to look for your continuation trade. So I'll set an alert at 744, knowing that 761 is going to be the breakout. This I won't do in FinVis. I'll do it in my TWS platform just because that's the way I do it. But going back in the screener, we're going to create the second one that we need. So because we do have the one week, so this is for mainly what's in play at the moment. We will also want to look for stuff that's been in play for like a month, which is going to be really important. And this, what you're going to do is going to go month and up 10 percent and the volume, you definitely want to put it lower to what you think a price or a stock in your category should fit. So let's say over one million week over 3 percent. And then if you want to add a market cap, it's going to be right over here. And you can also do it for free. You can't just do the custom one. So for me, I look for 10 percent over one million week over 3 percent. And then what I do is I go back to performance and then I click on the month, see how they're performing on the month. And when this is set up, I'll do the same thing. I'll save the screen on my monthly top gainer. It's going to be this one monthly top gainer. And then I can go back to screen when it's saved. And I'll do the same thing. I'll go into TA and I'll be able to just scroll through what's in play and what's really moving the market when it comes to stocks. And we can see we have a lot of small cap. If it's not really what you're looking to trade, the best thing to do is just add a market cap. So you're going to add maybe small over 300 million. And then it's going to remove, you know, everything that's a low float, as we call it, and you're going to see more like the real stuff and no bigger company. You're still going to have the cheap stock, but they're going to have at least a decent market cap. And you're going to be able to really follow what's moving. So this is going to be your one month. Then you're going to go and move on to the quarterly. So quarter is going to be the same thing. I want to see quarter over 10 percent. The 10 percent is just to fill out everything that's not really strong in the market. But we always do the same thing when we have a set up with the filter we want. We're going to go to performances. And then this one is going to be by quarter. You're going to put it descending. And then you're going to save it to save screen. And next thing you know, you're going to do the same thing. And go to TA. And now we can see, right? We have a bigger stock by VKTX. That's the employee. We have an SMCI. That's, you know, in an interesting range, OCGN, ARQT. Now we're starting to see some bigger company or bigger market cap are the leader for the three months. And we can see that. All right. So right now on the one month, it's only a small cap that are really moving, but we can send the three months. We still have set up if we get back to higher prices that are going to be there. So you're just going to be able to set some alerts and sit on your hand and be patient. And what I'll do is I'll go over here and do the same thing after I save this one. And then I'll do half a year and then I'll do the same thing. 10 percent go to performances and also half year. Put it in this order. Then I'll go into my TA and then I'll do the same thing. I'll scroll and just set some alerts at higher prices. See, as soon as something hit, then I'll know that it's really in play and there may be news or just breaking out above an important level. And you can see it's really showing you what's leading the market. Like the crypto coin is still in play. So maybe they set an alert around the 270 for 280 breakout if we get to that price. So I hope you enjoyed this video. If you did, like and subscribe. I'll see you guys in the next one.


Howdy, and welcome to theCUBE. My name is Peter Burris, and I'm broadcasting from ours, Silicon Angle Studios in Silicon Valley. Very excited here to talk about some of the research that's going on in Wikibon Weekly, especially in anticipation of next week's Hadoop Summit. I'm here with George Gilbert, who's the analyst of Wikibon who looks very closely at big data. George, welcome. Good to be here, Peter. So this is gonna be an ongoing series of conversations between Wikibon analysts as part of theCUBE's effort to increase programming, and that we're going to call Wikibon Weekly. So we've got a couple things to talk about. George, I think that the first thing we want to talk about is the event next week. We're at a crossroads in the world of Hadoop. It's been out for a decade now. It's, we've got Spark that just hit and is generating a lot of excitement. We've got still a search for business models that are gonna generate and sustain the type of investment. But we're also getting some indications from our conversations with clients that the adoption of Hadoop and related technologies at least in production is a little bit more segmented than many people might have thought. What do we need to see from the community next week to kind of kick this back in a gear? Well, every technology enterprise technology goes through a process of hardening and streamlining to make it more accessible. And the organizations that are most technically sophisticated can adopt it first and get the most benefits out of it. Standard technology adoption dynamics. But we haven't seen a step function in the accessibility of Hadoop in any time really in the last several years. So in other words, we're trying to reach beyond the Fortune 500 but we haven't really changed the product to reach companies who can't put five specialized admins. And by specialized, I mean different domains to run a 10 node pilot. And where I think we're gonna see that showing up is slowing adoption or more difficult traction in mid-market companies. And mid-market, let's just say, is probably below the US Fortune 500 because they just don't have the numbers of admins in their IT department to specialize to the degree that Fortune 500 companies do. So typically we're talking about a company that might have an IT budget of $50 to $60 million, maybe $100 million. That's a mid-market company by that definition. That's real, that's still a pretty sizable shop. Yes it is, but as we all know that 80% plus of that money is going towards maintaining the existing systems. We call them legacy systems, they call them the systems that work. And you're not gonna, everyone knows that something like Hadoop is necessary as a sort of a next generation strategic data platform or hub, but we have to make it, we have to reduce the friction to install it and to deploy it and widely utilize it. And so we're hearing more noises about the relative, relatively faster adoption of Hadoop in the cloud where some of that friction is reduced. And so in other words that there's a couple of paths that look like we got going forward at least for the mid-market. And the mid-market is where a lot of things end up going mainstream. One is that we can see the mid-market moving toward the cloud where they can run scripts and have Amazon or Microsoft or somebody else actually handle the administrative duties or that might start seeing applications start taking more center stage and new forms of packaging that speak directly to a particular business problem whether it be horizontal, vertical or what else it might be. You've recently done some research on the pain that the market's going through as it tries to develop these application concepts. Where are we right now? Okay, so there's a variety of different business models that are being experimented with, frankly, because the numbers aren't big enough to say we've settled on a dominant one for this point in the adoption cycle. And as I like to say, as Captain Rinoz said in Casablanca, we can round up the usual suspects and put them in their buckets. The vendors that are using consulting-led, semi-templated solutions are IBM, Palantir, Accenture, Teradata, among the largest. Teradata? Yes. Let's come back to that one. Okay. So we keep going. So Teradata, I went to their influencer summit last week and I was expecting to see a lot of speeds and feeds and, hey, we've still got the biggest, baddest decision support database and people who can't stretch Oracle properly will come to us. They were very surprising because they talked about an entirely different way of thinking about big data and transformational business solutions. It wasn't even really big data. It was if we want to be able to rethink how we can manage business processes that cross functions without regard to the source systems or the types of data, here's the underlying infrastructure we have to put together. So it's good to see Teradata who was the, obviously one of the granddaddies of the data warehousing BI era has basically jumped on board and is now trying or is becoming a thought leader also in some of the things that are happening with big data and the broader sense of the overall analytic space. Yeah, their message was really holistic in the sense that they said, look, you're going to have a lot of data that you can't tie together right away. You put that in the data lake, which is what all the heretics have been saying for years. And then you do discovery on that and you find where the relationships are and you do these, you ask these questions in relation to the business, these transformational business opportunities that you might have, where you have to track behavior across a website. You want to track which members, which customers or prospects are most influential in the community. And you might also want to understand manufacturing lots to see which items down at the lot level needed recalls. You know, that crosses many systems. So we've got the idea of the consulting and services led play, which basically somebody rolls in and says, don't worry, I'll build it for you and maybe you'll even let me administer it in some sort of outsourcing relationship. What's the second business model? Before we go off that one, it's worth saying that there's a spectrum even within that in that you can't go in upfront with a whole portfolio of solutions other than slides and that as you do more of the engagements, they get more repeatable and you can take the templates each time they get better and better from each engagement. And the next customer gets the benefit of an even richer, more repeatable engagement and it gets closer to a supportable application as opposed to a consulting engagement. But the key thing is you're starting with smart people who have good knowledge of tools as opposed to starting with promises about great tools that are easy enough to use by normal people. 100%, but also worth mentioning is the people who walk in with that knowledge of solutions and transformations are very different from the people who sell tools to infrastructure buyers. Sure, so let's talk about that second class which really is, to anticipate what you're gonna say, it really is the emerging software guys who are delivering many of the new platforms and trying to bring together, bring greater usability to bear on the platform set companies like Microsoft, Microsoft, SAP, Oracle and even Amazon and Google where to varying numbers or to varying extents, they have big data platforms and tools, let's say SAP with its HANA database and the HANA Vora database which bridges HANA and Hadoop, Amazon with its range of databases and tools which they are progressively integrating so that if you use one, it's actually much easier and much more functional to use them all and frankly the same with Microsoft and Microsoft has done the most work and is heading, is going to have the largest advantage in bridging what's in the cloud and on-prem in a completely compatible way with tools that make it transparent where your workload's going. So these are companies that, unlike the service guys, would start with people and then they had to do a lot of work and then they use tools, let's start with tools, accrete new value in the tools to make it more available to different people. I mentioned earlier, we mentioned earlier the idea that the other side of this is going to be packages up in applications that serve a more specific type of a business purpose. What's going on with the application space? Okay, so this one's kind of puzzling and we've talked about this before because when you're in SAP or in Oracle and you own both the applications and your platform, the development tools, the database, you are in the cat bird seat and being able to say, I control that whole stack. So if I want to write applications that really demand or make great demands on predictive analytics, large data sets and I want that to be realizable out of the box, you would expect those vendors to have done it first and be way ahead of the rest and they haven't. And I think there's a cultural problem partly at SAP without putting names to anyone since I have or used to have relationships with some of them. Their mindsets are systems, even if they led an application company. And the other part is that when you built traditional ERP and enterprise applications, you built a data model, a bucket for all the data and then the UI or the workflow to manage that data. The data was static. That was, you spent years modeling all that. The way these new big data applications work is you have data coming in and the data shape is changing all the time, but you're extracting the logic for the application out of what the data tells you. It's inverse. So let's talk about that because we actually have mentioned this and this is in some of your research that the historical norm in the application world was start with process that is associated with relatively rigid data model. Tune the heck out of it so that you can scale it and deliver it broadly. That's kind of the operational approach. But when we start talking about some of these new applications for engagement, for IoT, now we're talking about the process of not being as well understood. The algorithms and the workflows and the patterns emerge out of the data and we have to rapidly respond to changes that they reveal. That's the key word you said in there, emergent. It's just, and that might be why the big companies can't wrap their heads around it because it's the inverse of what was going on. It's not top down. It's not cathedral. It's bizarre. Very much so. And I don't mean bizarre as in weird.  Right, going back to a number of years. Okay, so we've got those three. We've got service, we've got platform, and we've got this emerging application space, even though it's very much in transition right now. We're still learning about it, but it's very exciting. The last one is this converged infrastructure. You know, slamming infrastructure together so that the infrastructure itself is simpler to use. You don't need all the administrators to do that, to pile it with the n number of nodes. You still need somebody, but you can put more of your professional talent up into this actually administering the higher level parts of the stack. Yeah, the best quote I heard on this was when you have a completely software defined network, you don't need to take a network cable and unplug it from one place and plug it into another place. That's an API. And once you have that software defined infrastructure, and this is where our colleagues, Brian Graceley and David Floyer have done so much really cool work, the operational characteristics of your private cloud resemble more of what's in the public cloud now. Or just your data center. Okay, your data center. You're not meeting the public cloud in terms of costs or operational automation of the software above it, but that data center operation, the hardware and the operation of it become much more standardized. You're much more alike what you see from the public cloud. And some of the vendors here include Dell. HP, the HP sort of, the enterprise version now that's been spun out. Sure, Oracle, IBM's still a big part of that play. So as we think about these efforts to cohere or converge around a set of business models that have the potential anyway to start translating investments in the various open source Hadoop-oriented big data stacks, what are you looking for next week from some of these vendors? Or what do you think is gonna start getting people excited and get them waiting for 2017? Okay, so there's a couple things. We really, really need to do better with cost of ownership. I like to say that, and I think the Hadoop guys, I don't know if this came tongue in cheek or that they name every project in the Apache, she kind of continuum or portfolio, a different animal. And then the guys that, the product that actually keeps them coordinated is called a zookeeper. So the zoo and the zookeepers really have to learn to play well together. Are we gonna see some of that next week at Hadoop, you think? I think we're gonna see incremental progress. Okay, so first recommendation is look for incremental progress in how the packaging is simplifying the interfaces and the activities of administering these things. And just as an example, at Spark Summit, we had Doug cutting of Cloudera on, actually as our kickoff speaker. On theCUBE. Yeah, on theCUBE. And we asked him about that interoperability challenge and, because his VP of engineering had told us previously that they spend, they budget 50% of their R&D cycles for interoperability and only the other 50% for functionality. And Doug was like, yeah, it's some basic stuff like security, making sure we have common permission. So this is important to the customers that are going to the users and the doers that are gonna go there. But it's also important for the members of the ecosystem. All right, what else, in addition to ease of use and simplification? We'll wanna see how much of a difference can a cloud deployment make in terms of the friction? And I think the best way to measure that is, how many specialized admins do you need for a pilot and then for production? In other words, we've heard numbers five or six different differently skilled admins for a 10 node pilot. That's a, you know, like an 80% OPEX kind of workload. We wanna hear what that number becomes when you go to 25, 50, or 100 nodes. In a cloud setting. Well, no, first on-prem. And then to see what that number looks like in the cloud. And that's gonna be crucial to making the mid-market happen. I know we're gonna be looking a lot for the new models that some folks have about thinking about applications and the evolution of application as a technology set within the big data world. Because like Cloudera has always said, and Hortonworks as well, all the distro vendors have said, look, we want a common platform. We will differ at the edges in terms of how we make it, you know, more manageable or more industrial strain set, the storage layer, like with MapR. But we want this to be a common platform like Linux so application vendors can write to it. But the common platform is forked beyond the ability for any sane application. Well, there's a big difference between an operating system and a control program for hardware and a set of technologies that are intended to capture extremely complex data from a wide variety of sources to solve extremely complex problems. You are probably putting your finger on the very weakness that represents this notion of a common platform that abstracts hardware, which is an operating system, and one that is essentially an application server, you know, or application services. And those have been now forking to the point where it's very difficult to support more than one. Yeah, so I'll have one more to add to that, George, and that is I am going to, I'm also going to be going there, and I know you're going to be on the cube there, fair amount. I also am going to go there, and I intend to see if we can discover more about the role that data value is playing and guiding some of these decisions. How are businesses, first of all, are they starting to think in terms of data value as a discrete thing to factor when they make investment decisions in technology? And how are they then using that concept to inform their other investment decisions, their operation decision, and their strategic decisions? We're getting evidence in our research with clients that that's starting to happen, so I'm going to be looking for that. It's funny that you say that because Teradata, you know, who I would have picked as the number one sort of big iron kind of infrastructure vendor said, when we go and engage with a customer and we assess the first business case that we're going to do together, the first thing we do is figure out what is the payback on turning that into an analytic solution, and we only go for the big ones. All right, so let's wrap this up. Once again, my name is Peter Burris, George Gilbert, analyst at Wikibon, and we are broadcasting here from our studios in Silicon Valley in anticipation of next week's Hadoop Summit. The cube will be there by all means, come and check us out at SiliconANGLE TV, or if you're at the show, come to the booth, come to the studio, meet George, have conversations, grab a cup of coffee, whatever else it might be, and this is the cube, Wikibon, thank you very much for listening, and let's make progress on moving the needle on big data and big data adoption and utilization.


If you want to spend some time giving back this holiday season, the Community Christmas Meal in Bemidji is still in need of volunteers. This will be the 39th annual Community Christmas Meal in Bemidji. It rotates between six churches in the area and this year it will be held at Bethel Lutheran Church. Community meals are the perfect way to get to know your neighbors. Whether you choose to volunteer or just enjoy the dinner, the meal will usually serve around 500 people and right now they have only 70 volunteers. We have so far about 75 volunteers but takes a lot of people to get up to 500 meals served whether it be at the church that day or delivered. So we'd be glad for everyone to think about maybe paying it forward a little bit. Maybe you can start a new family tradition and help us as we try to bring the community together. Now volunteers can be of all ages. Some families choose to volunteer together. There's also a wide variety of roles a volunteer can take including making deliveries, serving, and working in the kitchen. The meal will include a ham dinner with all the trimmings including potatoes, coleslaw, corn, Christmas cookies. We try to make it as nice as possible. That's why we need so many volunteers. That day we have the people sit and then volunteers bring them their meals. So I think that's kind of nice to be able to sit and have somebody wait on you. The community dinner will go from noon until 1 30 on Christmas Day. If you enjoyed this segment of Lakeland News please consider making a tax-deductible contribution to Lakeland PBS.


Hi everybody, my name is Afra. Since it's summer, I'm sure everybody is looking for something cold and refreshing to have. So I'm here with a very simple watermelon slush that you could teach your children also to make and you could also enjoy having it. So let us see what all you require to do for this activity. Some watermelon pieces about a bowl. Two or three spoons of sugar, some salt, some cold water or maybe water at room temperature as per your preference. Some pepper, a straw and two spoons. So let us begin with our exercise. Add almost full of the watermelon leaving about three to four pieces in it. Add the entire glass of water. Add about two to three teaspoons of sugar depending upon your taste. Some salt and some black pepper. Now all you need to do is blend it clearly there. Let's blend it together. After the blending of the juice, after the blending of the watermelon, if you wish to strain it otherwise you can just add it into your glass like this. I prefer it like this. Then with the help of the spoon, chop your watermelon pieces like this and then you can add it to your watermelon juice like this. You can also add on some ice cubes if you wish to or you can skip that. Once it's done, just mix it so that the pieces get go down and we are all set to have a refreshing watermelon slush. So let's taste and see how it is. I can't tell you how refreshing it is. I hope you enjoyed this activity. Take care. Have a nice day. Thank you.


Hello and welcome to PCIM 2023. Here we are showcasing ST's silicon carbide power discrease. We are leaders in silicon carbide with our reliable and high performance breakthrough power technologies. Today I am going to tell you about our latest Gen3 6 series, and the different boards you can use to accelerate your development. So, first about Gen3. It is leveraging ST's experience with more than 150 million automotive grade 6 devices already shipped. It has been further optimized in all resistance and gate charge, with outstanding results in conduction and switching losses, to reach the highest efficiency possible in applications. Gen3 is available in a wide range of multi-source industry standard discreet packages. This gives you unbeatable flexibility to select the best fitting solution for your design. ST6 Gen3 is widely used in industrial applications such as high power DC chargers for electrical vehicles, solar inverters, energy storage systems, UPS, motor drives and automotive applications. Let's have a look at a specific solution equipped with silicon carbide. Here you see a complete digital power solution for high power, three phase active front end, based on the three level VN topology. Typical end applications are DC charger stations for electrical vehicles and UPS. It reaches a power of 30 kilowatts with peak efficiency of more than 98.5%, and a frequency of 70 kilowatts. This is possible thanks to the use of SIG Gen3 MOSFETs. Here they are housed in four-lit packages that increase switching frequency, reduce energy losses and allow higher frequency operation. Each SIG MOSFET is driven by an ST galvanic isolated driver from the ST gap drive series. This topology is even using ST SIG dials with high forward charger capability ensuring an outstanding robustness during transient phases. Another point to note is that the system features a fully digital control with the STM32G4 microcontroller. It is providing the full control of the entire system, and it also provides the full control of the entire system. The system also provides the full control of the entire system with the STM32G4 microcontroller. It is providing the full control of the power factor, DC voltage and soft start-up. Here you see another reference design from ST that enables the evaluation of the switching and thermal performances of SIG MOSFETs in four-lit discrete packages, in half-bridge topology. You can use this platform as a tool for double pulse tests. You can measure the rate of voltage and current changes over time, voltage and current overshoot, and energy on and energy off switching energy losses. For more information visit ST.com slash SIG. Thanks, talk to you soon.


So wait, so let's get started. Quick intros, thanks everyone for showing up and look forward to having, I wanted this to be more like a two-way conversation so we're gonna go through the deck fairly quickly, 20 minutes, maybe 30 minutes tops and then spend some time doing Q&A and kind of having a conversation. So I'm Chino Sahu, I'm an IT architect at IBM based at RTP and I'll let Bill introduce himself. Hi, I'm Bill Hankard. I'm based out of the Littleton Mass Lab. So I'm a Boston native and I work with Chino. So just to kind of, well what you guys can expect from the session and you'll get some more details on the context of what we do within IBM. It's basically our internal cloud. It's our internal way of enabling our development teams that are actually building and delivering products and services offerings, making sure they have what they need to do that in an effective, efficient, cost-effective way manner. So what we wanna kind of share today is what sort of challenges we had while operating this global hybrid multi-cloud service, what those challenges were and then how we addressed them. And so just a little bit of context, around 2015 or so we had a mission to enable our development teams, kind of two fundamental business objectives. Ensure that they're able to seamlessly move workload and work and operate and build their software in both an on-premise cloud and in our public cloud, which is software. And also allow them to deliver continuously and in a DevOps-type way. I think I'm one of those topics and we try to enable the developer so we kind of get the IT out of the way. And that's where we found OpenStack very beneficial for us. They're self-enabled, they have the resource, they can go forward and be productive. Yep, it's a great point, Bill. Very much self-service, API-driven. Now that's definitely the key. So this is a really, it's a busy picture slide but it kind of shows some of the technologies and tools that are included. And we're gonna go into a little bit more detail but you'll see OpenStack on the top left. We're leveraging Jenkins, Grafana, they were tied into Slack and GitHub and a couple other corporate tools that the company, that our company uses as well. What we ended up trying to do is not just do OpenStack. It's OpenStack as the base but we kind of think of it as OpenStack plus as a service. And so listed here are all the things that we've built around and on top of OpenStack. We wanna make sure that a consistent user experience. We've built a way to do automated image replication, an engine for users to go build their custom images and have them pushed out to each cloud, custom DNS registration, hybrid networking to and from our public cloud, automated security compliance. We've got a lot of corporate security tools that we've got to integrate with a corporate directory, multiple platform support. We've got a significant investment in power and we're enabling containers as well. Automated continuous business need and other like business processes. And so these are kind of the things that we could focus on because OpenStack solved a lot of the other things that we didn't have to invest in. So the focus was building above the stack and around it to really impact our users. So here's another busy diagram, just kind of our high-level architecture. On the right you'll see our on-premise footprint. Right today we're fuel-managed OpenStack, open-source fuel, open-source Morantis's distro using SpectrumScale which is otherwise known as GPFS, is storage, OpenVswitch for networking and then the StackLite monitoring stack for kind of monitoring availability and operations and et cetera. The just one point, the SpectrumScale is a clustered back-end file service that IBM's had for years and integrates fairly well into OpenStack. And you'll see in the bottom right some of the things we've got to integrate with are corporate tool, corporate ticketing, corporate authentication, our chargeback mechanism. And then on the left you'll see the footprint that we have in SoftLayer. We've got a Bluemix dedicated environment that we're integrated in from a connectivity perspective and this is an instance dedicated to IBM internal. It's not our public Bluemix but we do have cases where we go out to public Bluemix as well. So I won't get into any more details there. So let's jump right into some of the challenges that we faced while building and operating the service. Obviously there's, with any cloud provider, you're gonna have costs. Cost is one of the key constraints. We kept adding on more complexity which resulted in more costs. Our support costs went up as we onboarded more users. We have a global footprint. Four major sites today, two in the US, one in Canada and one in the UK and we're gonna expand that even further. As with any cloud you're gonna have cases where you're not fully utilizing all your resources. So we hit that as well with our OpenStack based solution where teams and users just aren't being responsible. And how do we address that and what do we do to help them be more responsible and optimize their use at the same time, get the most of what they're doing at the lowest cost possible. And then I wanna speak a little bit about how we optimized enabling these teams. Bill had mentioned, IT was kind of seen as a gate as a manual step in a process for our developers. We wanted to eliminate that completely and really put the power in their hands and make sure that they're able to do what they need to do but in a safe, controlled, efficient manner without them crashing the car per se. So we'll jump right into, anything wanna add? Yeah, no, I just, as Chino said, the self-enablement of the end user was key paramount to they have their own networking, they have their own images, they're basically in their own project doing it and we're stepping back just providing the infrastructure for them. That was a key component. Yep. So rising costs from adding complexity, one of our key things that we needed, we know what we needed to do was standardize. It's pretty obvious, the more standardization you do, the less variations you have and hence when everyone's working in the same way, heading on the same mission then you gain efficiencies doing that. But we've got a heterogeneous data centers across the world. We knew standardizing at the harbor layer wasn't gonna be possible and something that we could tackle and so that's where OpenStack really helped us is it helped us standardize at that layer, that infrastructure as a service layer. And so we've got a recipe where we're leveraging the same storage technology, same networking technology, same configuration and we've automated all that so we can literally stand up a cloud in a day or less and roll it out into production very quickly. And that kind of leads me to this last point here. We built a way to incrementally roll out features. So one of the shifts we had with our user base was, they traditionally been used to the VMware base model where they would get a bunch of VMs and they would kind of hold on to them and they would craft them into these snowflakes and they trusted that these VMs would always be there. When we kind of shifted to this OpenStack based service, the message we conveyed was we're not gonna guarantee that your workload's gonna be up all the time or that it's gonna exist. We could have a cloud failure, we could have a hypervisor failure so we wanted to drive them to build their code, build their processes around expecting failure. And so our guarantee was that we would have OpenStack services up. There would always be an OpenStack cloud whether it's in the one in RTP, the one in the UK or the one in Canada, they're always gonna have an OpenStack service but you won't necessarily have your workload, that exact workload, it was not guaranteed to be up all the time and that kind of really forced our users to kind of redefine, look at the process and build that sort of failover mindset into their process. And we do that as well when we're trying to roll out features, we expect things to fail. So when they do fail, we're able to recover quickly and then minimize any impact because of that. So rising costs from support, there's OpenStack is complex, there's things that happen that are difficult to debug and one of the models we chose to go with is instead of purchasing formal support from a vendor, we chose to invest in people. So we skilled up people across our teams to become OpenStack experts and kind of self support our service. And we've realized from that, we were able to really build strong technical people and I think we resolved issues faster. I mean, historically, we've had vendor support for other offerings and usually it takes, it's a lot of back and forth, there's a lot of overhead with that. And so far we found that having our people support the offering versus... I think collaboratively throughout the IT team, we have skills, various skills everywhere and we found that that really helped in this whole global model of deploying and supporting OpenStack moving forward. So having those diverse skills within Python, scripting, hardware, software, storage, networking technologies really helped us immensely. Yep. And it's all about collaborating. I mean, we're all in a Slack channel, we are multiple Slack channels and we're constantly keeping each other abreast of what's going on and because we have a global team, we're able to kind of do this follow the sun model where teams will pick up where when days end here in the US and vice versa. Well-built runbooks can't emphasize that enough. That includes automation, automation and well-documented steps on what your admins need to do in order to debug and address issues. I mentioned earlier, we leverage our clouds as kind of failover instances. When something does go wrong, we've built in a way to quickly shift users to another cloud or another region or availability zone, et cetera. So they're not impacted while we continuously debug where issues do arise because OpenStack is, as all of you probably are well aware, is very sensitive and can go down at any point. And I think the standardization part was also, it's a key point from being able to debug people's, the other environments across the globe that we've had issues with. So if we know it's cookie cutter across the IBM, then it's easier for the teams to debug and fix problems when they arise. You know where to go and what to expect. So usage governance, just kind of helping users be more responsible and giving them the tools to kind of self police, self monitor themselves. Automation, we invested a ton of automation. CBN, making sure that they still need their resources for the allotment that they asked for those resources, kind of pruning and kind of self cleaning projects and cleaning out volumes, et cetera. That's something that we definitely rely heavily on. And we built a dashboard that is user facing and kind of shows them this is what they're consuming across all their clouds, both on-prem and in software and public cloud. What they're being charged for. This is what you're spending. And just simply just having that data and understanding where their costs were and the ability to kind of model out, well, if I shifted 10% of my workload from public cloud to on-prem, this is how my bill will be impacted. Just having that information, that data really drove a lot of their behavior to kind of think about being more responsible and making the right decisions to optimize their cost. And in other cases, where you need public cloud for some reasons, but just understanding what the trade-offs are and what they're paying for really help kind of drive some of that behavior. And then really kind of focusing on enabling these teams to be self-service, to be more empowered to take on more of the IT type tasks, education was definitely key. We have a really well-defined, automated onboarding process. And then we spent a lot of time kind of really consulting with these teams and kind of showing them how to use OpenStack and how to use automation, develop infrastructure as code, enabling these coaches to kind of teach other people on their team, providing them tools. We've got a central Jenkins instance. We've got a lot of Ansible playbooks and heat templates that they're able to use and kind of take off the shelf and then customize and leverage on their own. And really the shift from static to dynamic, that's really the mantra that we wanted to push was get out of this old model of using static VMs and static workload and doing things when they need to on demand and in a dynamic way. Do you wanna add? Yeah, I would say that we've found that the dynamic deployment of instances has really gone up dramatically when a user realizes that they don't need to keep it around forever and maintain it in a lot of the workload automation that runs out there is constantly being redeployed every day, thousands of instances created up and down. So we see a high volume in that area. And so kind of the results of addressing these challenges. So we can do, we can roll out a new cloud and half the time we used to, we can roll out new features and half the time that we used to, we're able to provide 24 by seven near 24 by seven. It's not full 24 by seven, but it's close without having to hire third shift employees. We've enabled users to optimize their consumption patterns and again, in a more self-service way, we've reduced our overall TCO by 30% and there's definitely some savings to be had because of OpenStack and all the things that we've kind of done with OpenStack. So that's basically it. Let's want to spend some time with some Q&A. I think we've got about 20 minutes actually. Just a reminder to, if you do have a question to use the microphones and the aisles. So any questions? Comments? Yes, I have a question. For your dashboarding for the consumption of resources, were you making use of the OpenStack Solometer project for that or did you do something yourselves? We used a combination of Solometer and- Grafana, Gabbana. Data, Grafana, Gabbana. Well, yeah, we used Grafana to display it but it was a combination of Solometer and some of the data that comes out of the Stacklight Monitoring Suite. Okay. We kind of customized some of the HECA pipeline to pull stuff off their queues and kind of transformed the events into messages that we would then display in Grafana. Okay, thank you very much. So I'm assuming you guys do charge backs to your internal customers? Yes, yes we do. So how do you manage them saying you guys are more than the public cloud providers? What is your response to that? Is it you guys have support from the top down saying this is the way to go, you guys can use public clouds or can you guys talk about the experience? We actually want, our company direction is to consume public cloud as much as possible in this hybrid way. Ironically, our public cloud is more expensive than our on-prem charge back. It's almost, and so there's actually an incentive for teams to use our on-prem stuff more so than public, but there's definitely a lot of teams that want to do that hybrid where they're doing their test dev internally on-prem and they're hosting their public SaaS offerings. So internally, basically all the development and tests within OpenStack we do is in our labs which is not on the internet. However, we promote to software which is internet facing and there's obviously a cost when you have an internet facing. So that model, it does vary. As Chino said, there's the cost internally and then there's the premium cost to be internet facing because of the security, the firewalls, et cetera that go with that. And then my other question was, how do you guys bill your internal customers? Do you same as the public cloud per CPU? Do you give them flat fee? Can you guys talk about that? Yeah, it's actually a little bit varied site to site. We've got a couple of different models depending on the geography there. In the U.S., it's all usage-based. So RAM hours, whatever you consume is what you get charged for and that's billed out quarterly. And so just, you can get a view of what you're gonna get, end up being charged but the actual payment doesn't happen four times a year. Whereas like our European team, they're all burden pool-based. So, and they're kind of shifting away from that. So it's not usage-based, it's they basically have this team, this is what it costs to run their cloud and run their services and then that gets split out evenly across all their consumers. But now that we're in this global team dynamic, we wanna shift everything to usage-based. Pay for whatever you use. Thank you. So you mentioned, you made an interesting comment about the count of dynamic instances went up. I'm just a little curious as how have your thoughts shifted on the kind of metrics you're tracking in order to reflect this new pattern that you're endorsing? Yeah, I mean, that is, I think as the people or developers are finding, once again, to go back to, they're enabled, they have a project, they have their instances. We're not quote inhibiting them anymore. As they experiment and they do more work, for example, we have a team that's using Kubernetes to do deployments and they find that it's a lot faster for them to develop these sandboxes that the development teams use. And it's something that they can just pick up and throw away. And we capture that, I think through the stack light and through some of these metrics that we're producing. But I think with OpenStack, we find there's a new level of thinking and a new level of creativity that the development teams are getting the hang of. Just to add on, we do track number of deployments. I mean, just historically, we've always tracked that. I don't know how relevant that is, to be honest, in this new sort of mindset. Another metric we try to really focus on is what's the life cycle? So something was created, when was it deleted, and tracking that as one unit? How many recycled events happened and then measuring the time between? So if it's an average of two weeks, something's not right. They're not the behavior we want to drive. And then there's also just, because the whole goal is to get as dense as possible, as utilized as possible. So then we're also tracking how well are they meeting their quotas? Are they hitting 80% of the quota that they've defined for their project and then track that over time? So we're still kind of playing around with the right metrics, but I don't think we've figured it out, or the industry's really figured out what's the right single way to determine how efficient you are and how well utilized you are other than you're using up by resources and. Yeah, two part question. How did you calculate your TCO? And where specifically did you see a 30% reduction? So TCO is calculated based on infrastructure capital, actual data center, racks, servers, storage, network equipment, and then the people, the people cost. And we were able to kind of shrink our teams and support more capacity, more clouds with what the same number of people. So investing in more automation and kind of changing how we did things kind of reduced our overall cost of people and infrastructure. So essentially in some cases where you have the legacy sand team, network team, Intel team, application team, that's in one person sometimes. They do it that stack engineer, that full stack engineer where we can consolidate all those skills within one to deploy those clouds. So just a clarification question. So the 30% reduction in TCO was largely AWPEX based and not CAPEX? That was a combination.  I mean, it's the CAPEX. I mean, we have what, five year over that? Yeah, I mean, we just tried to go for like smaller, more reusable servers. And hence the, we drove the cost down from that. Some of the networking equipment, going to more kind of appliance based networking, kind of reduce some of that CAPEX cost. But the majority was AWPEX. Thank you very much. So I had a couple of questions related to support and what level of support you provide to the end users. So in our environment now we have some developers using public, we have an internal private cloud, and then we have an environment that's, I don't know, we're gonna call it classic, like a traditional VMware environment where people have long running machines, the infrastructure is highly available. So as we've transitioned more into a cloud model, a challenge that we're facing is related to like compliance for patching and vulnerabilities. So in the older environment, there was a lot of hand-holding. It was a managed service related to that. They just go to a dashboard. There were teams doing that. But as we move towards more self-service, the onus is on them. And initially in the private space, that didn't work out too well. There's more policy in place for the public. So they're mandated more and machines will get shut down and destroyed. But do you guys have that challenge or any recommendations related to that? So I'm doing a talk on that tomorrow regarding the image compliance and how we use the different tools to basically produce compliant images and help them with those challenges moving forward. Yeah, I mean, we can talk after if you like that, be fine. But yeah, it is a challenge in the cloud world to keep these images.  So as we see the usage of all these DevOps, these continuous delivery, continuous integration tools out there, you know, the developers are enabled and they're building up these environments. They're doing their testing. They're spinning it up, they're tearing it down. And you know, but at some point when the long-lived ones are out there, that we have to have that level of patching. We have to have, if it's Windows antivirus and for what business purposes, they have to have certain password policies, et cetera. So that's the challenge we found. Not saying we solved it, but we made a good step into it. So do you have like agents deployed that you're watching the stuff or do you? So in one of the cases, we deploy the IBM endpoint manager, which used to be called BigFix, which will basically check the image for compliance and what have you and then report back to our compliance engine. And when an instance gets deployed within our environment, we have a program called IT SAS, which is our IT security compliance. The image basically gets scanned. It gets registered in the compliance tool. The end user, it gets notified of that. And then whatever patches that do APARS, they basically get flagged. They get notified via email. And also the endpoint manager is sort of the quote overseer to say, hey, wait a minute, we see this vulnerability that just came out. You may want to address this sooner than later. Yeah, so for any image that a user will use, it'll be compliant out of the gate. So we maintain the images. We've got a process that automatically keeps them up to date on a monthly basis. Save the user wants to bring their own image. We've given them a process to go upload them through Jenkins, which will scan it, patch it, then kind of spit out a image that's just as good as any of our own images that we provide. So we give them this process. Instead of just importing their own into their own project, they import it into through Jenkins and it gets pushed out into their project and it's compliant out of the box. And then as Bill mentioned, ongoing compliance, we kind of scan it behind the scenes on some cadence to make sure there isn't like vulnerable systems. And when there are, they get notified and they've got a window to patch them or fix them or they have the option to automate that to leverage our endpoint manager component to do it automatically. So they have the option to do it like every weekend, any time or only when they're notified. So one thing we're trying to implement is to try to have people stop thinking about patching and that they redeploy their infrastructure once something becomes non-compliant. I have a feeling that we're gonna run into some challenges with that. So we have, we debate back and forth. Do we deploy an agent? I don't want an agent out there. Like, hey, use Ansible to do it. All right, then I need Tower and how does it scale? So historically we've had agents. There's a policy now that'll say, after two months, all instances that have been instantiated off of this image should be destroyed and rebuilt using somebody's developing like a cloud custodian type tool for OpenStack. So I don't know what we're gonna do long-term, but I know the agent, non-agent, let people manage their own stuff is something that has challenged us so far. So I'd love to hear more during that session tomorrow. Thank you. Any other questions, comments? I think we're still got a few more minutes.  How do you define your prices? It's all cost recovery. So whatever it costs us to provide the service, that's what we end up charging to our users. Is there like a price list for the client by the sizes of the VMs or is it okay? Yeah, we... It's RAM, CPU. Yeah, I think we've actually broken down to like per RAM hour, because we realized it was not any cloud of RAM is like your constrained resource or your most constrained resource, RAM and IPs. And I think it was a roughly 10 cents an hour or something. So we try to break it down to where it aligns with what it costs us to manage and run the offering. Thank you. I mean it's an internal deployment. How do you get your future demand? How do you know when you have to add and add capacity? So you're obviously not just gonna keep building like some of the accounts I've provided will just continually add. How do you measure that? Do you have to go and get clients to give you the yearly expected deployment or are you just using historical data? I mean it's historical data. We're monitoring obviously the clouds to see where the resource, the consumption is and as needed we add resource as needed but is there a scientific model to it? No, I'd say no. I think it's looking at the utilization across the board. We tend, I don't tend to get too consumed with instances, instant counts. I'm more concerned about the underlying hypervisors and what they're doing, how they're churning away and that's the barometer basically. You get that through the stack light, the monitoring of the base metal, the bare metal. Which even though you try to do is good job planning there's always gonna be cases where you need unplanned resources and this is where the hybrid part of the solution actually works out. And I will try to cloud burst into our public cloud and provide resources that way or we shift resource from one, not just shift resource, but we shift the user to another geo where there may be more capacity. I mean this is where we leverage the multi-cloud approach for those unplanned needs. Thank you. So if you don't mind two questions. This is using a cost recovery model.  And then the next question is, as you've gone through this, have you used metrics for both either utilization or cost recovery that you've later determined to be useless metrics and thrown out? And if so, why? We have revised costs in the past. The more efficient we become, the less costly it takes, the less cost for us to run the service. The lower the cost to the end user, because we're not trying to make a profit internally. Our role is to enable teams and make sure we're doing it at the lowest cost possible. So we have lowered costs in the past. As far as a metric where we kind of threw away, I can't recall one that we've kind of given up on totally, to be honest. We try to look as much data as possible. We used to track CPU, but it hasn't really been CPU utilization. Yeah, I think the metrics were really, I mean, it's the, I think the underlying infrastructure is what we're really, the metrics we look at there. And you go down your memory, CPU, network, some of the key components within the hypervisor, throwing away or looking at other metrics. There could be some things in that area. But typically, we stick to the basics on that. Everything we got, a couple more minutes. Anything you want to bring up or? Just so that we, using IBM Spectrum Scale for the backend file storage that is used for our public clouds or private internal clouds, fairly robust backend storage, use sand storage, clustered, redundant, resilient. I think the thinking and doing that, I come from a VMware background. I wanted that clustering filed system in the backend so I can easily migrate instances to and from. GPFS provides that for us and we have a significant amount of GPFS skills within the teams. And just a quick plug. Again, Bill is going to be doing a session tomorrow with the Sheraton. Yes. It's one of the late sessions, like 5.30. So maybe it'll be a pretty happy hour stop but we'll go into the kind of details on our custom image engine. That's all driven by Jenkins and it's really cool. So if you want to come by then, we'll be there too. All right, if there aren't any questions, thanks for attending. Thank you. Have a good week. Thank you.


IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN IMAGIN Hock's Bay, day two we did them in Monaro and day three we did them in Argentina. But the stages because even the first loop we put in three stages then you come into a service, then another three stages you come into service, then you do two stages service and the final stage you finish. But again if you damage your car service time was limited and then times are coming in online as they come. Obviously when the next day starts at midnight me and Khajum used to sit back and audit results up to two, three o'clock in the morning to see that you know because we don't want any eyes or any cheating going on in the game or hacking or anything. So we actually from the 250 we used to sit down and you know audit each and every stage time by the time we go to sleep was almost four. The first night I think we went to sleep at five o'clock in the morning. But then as the days progressed you know safari is always tough, people tend to break their cars, others retired and all that. Two hours surprise about 130 still made it to the finish. The top Kenyan was 11th, the top Tanzanian finished 16th, the top Ugandan was 12th but the Madagaskan dominated the whole thing. Wow and we are talking about countries which actually love rallying here in Africa, Tanzania, Madagaskan, Kenya. Zambia did not have a chance. Zambia unfortunately they were busy that weekend but we had one driver from Zambia who is actually a real rally driver who rallies in Zambia as well. He was on board. We had a couple of entries from India, from USA, you know all over the world. Just for you, what is your end game from this? Are you expecting to transition from e-racing now to the real safari rally sometime in the future? Yes and from the beginning of the e-safari rally actually because I usually go into every other event as a mindset for fun so I don't really finish them. But this time because we saw how many people were driving, how many people would see the results, Riaz and I we decided that this time I was going to go slow and see where I can place. Was you an navigator in the game? No, I was a navigator. But we normally talk on a personal basis day to day in everything. But during the game did you have a navigator? Yes, the game is navigator. Automatically navigator. So Riaz, you have been talking, I understand you have talked about Jean Todd talking to you guys. You have talked about also the WRC course of the clock having a conversation with you guys coming on to join you guys.  Let's look at it how it is interdependent of one another. What have you gained more from the e-racing that you can transfer on to the safari rally? And what are some of the mechanisms you have got from the safari rally you can bring on to e-racing? That's a tough question. Let's start with the first one. Okay, from the gaming perspective, I would say I was the first ever organizer in Africa to do such a thing.  Obviously my real life rallying experience helped a lot because having played this game I could select the stages that were very close to Kenya as well. And personally I have spent 10 years rallying. And I am sure if someone continues playing this game they wouldn't spend 10 years to reach where I was. They would do it in 3 years because you already start knowing how to call the notes, when to call the notes. What each sign or what each call means if you tell a driver double question, write 5, keep in, line. So a normal person would not understand what that line means. But now having played this game you would know that we got a 6 right titans into dip and jump. And when to call it. You just can't call the notes when the driver is already at that obstacle or at the corner.  So the gaming perspective I'm sure the whole idea for us as e-racing to introduce this gaming thing in Kenya is so that tomorrow we can have a young champion that will evolve from e-racing. It could be Joseph himself that would evolve and go ahead and win the Kenya national rally title. Is that the vision you are for e-racing? Yes for sure. It's just to encourage all the youngsters because most of the people have playstations at home. X boxes and everything. There are a lot of people now that WRC has come back to Kenya. There are a lot of people that are more passionate about rallying. So let's just share this passion. Let's just help the game evolves into better drivers, better co-drivers. Joseph, finally for you, what do you make of your future in e-racing? Well, seeing my results on a controller, considering that I was in 25th position and 8th fastest controller. That's worldwide. Yes, out of all the drivers. 250 drivers. That's a big number. With the 8th fastest controller driver, I'm now planning to see whether I could get a simulator and then from there I would like to be fighting for the top place in e-racing. Please explain to me what a simulator is. So it's an actual simulation of real life rallying. And as Riaz previously stated that they can range from prices of 50 to 500,000. So the ones that are actual serious which the best in the world use is where even when you hit a jump with a rally car in the game, even the seat will jump. So of course I'm not looking to get one that high end, but whatever simulator I can get, I will see what I can do with it. They adrenaline when you are playing the game must go to be very high. It is extremely. As well, the fastest I've already finished the stages, you can see each sector you've passed, how far behind you are or how close you are. So that gives you a lot of pump to be able to see how fast you can go to catch up with the guy. Riaz, what does the future hold for you guys as the organisers of e-racing? Are we expecting a festival to come in future where this tournament is held somewhere people can come and watch, people can come and enjoy and also learn more about the game? The sky is the limit, I would say. There is a huge interest all over. We as e-racing that is Khayum and myself, we are open to any ASNs in Africa or even worldwide that actually want to come and hold competitions, such type of competitions because there is a huge plus point in this gaming thing and everything. So at the moment we are looking to organise the next big race, more details will be shared very soon. We don't know what KMSF will plan and what will be the way for it. But the whole thing is to have ELE championships where different category champions are crowned in real life. Here we also have our e-racing champion that he will be crowned at the end of the year. And work together with other ASNs so that we can not only exploit the talents of here in Kenya but also within Africa. Even to our surprise our youngest player was an 8-year-old kid from Tanzania that he was playing. He wasn't that quick but at least he was playing and he's getting it. It's not that he finished last, I think he finished within the 150 positions so you see that's a big encouragement. Our oldest player was a 51-year-old and this was something that we didn't get much time to advertise about. So I'm sure if we get the next event we'll be even, we are looking at getting about 500 entries from all over the world. Yesif, finally look at those cameras there. What can you tell the young people at home because when they look at you just under the age of 20 years you are participating in some of the biggest franchises in the world. What can you tell the young people? What I can tell the young people is that the sky is the limit and this e-racing will get you very far if you take it seriously and do a limit. Priyas for you, the people now who are discovering this for the very first time, they do not know that this thing happened. How can they get in touch with you? They can get in touch through our website www.e-racing.co.ke. You can see the previous competition what has happened, you can read about the rules there. Talking of live stream, in future we are planning that all the players should do a live stream but at the moment it wasn't the most. You can head on the live streaming section and actually see some of the players as they were tackling the stages. www.e-racing.co.ke, that's where all the information is. We are also on social media, Facebook and Instagram e-racing.ke. You can follow us, send your messages there and we'll surely respond. Wow, we've been talking to Priyas Ismail who is the organizer of e-racing here in Kenya and also a young driver here in the name of Joseph Gasheshe who is also an e-racing driver here on the touchline talking to us about this new virtual game in the country that is all about safari rally bad in the virtual world and that is e-racing here in the country. Let's break some of the videos from the e-racing platform and what they actually do outside there and we'll also be having a profile interview of Lothar Matthews, the 1990 German winning captain. When we come back it will be all about the fan zone.


How is the CIA still a thing? Citing conversations with more than 30 former US officials, a new report by Yahoo News has confirmed earlier allegations that the Central Intelligence Agency not only spied on WikiLeaks founder Julian Assange and his associates, but also drew up plans for kidnapping, renditioning, and assassinating him. These plans were reportedly made in coordination with the Trump White House as then CIA director Mike Pompeo and then Deputy CIA director Gina Haspel raged over WikiLeaks' 2017 Vault 7 release, which revealed that the CIA had lost control of an enormous digital arsenal of hacking tools. These included tools which enabled the surveillance of smartphones, smart TVs, and web browsers, the hacking of computerized vehicle control systems, and the ability to frame foreign governments for cyber attacks by inserting the digital fingerprints of the hacking methods they employ for investigators to find. It was the single largest data leak in CIA history. Normally, we have to wait decades for confirmation that the CIA did anything nefarious, and then people absurdly assume that such things no longer occur because it was so long ago and because changing your worldview is uncomfortable. But here we are with an extensively sourced report that the agency plotted to kidnap, rendition, and assassinate a journalist for publishing authentic documents in the public interest just four years after the fact. Which is about as spectacular a violation of virtually every value that Western society claims to hold, particularly the assassination bit. The authors of the story, who for the record insert their own flimsy spin insinuating ties between Russia and WikiLeaks, say it's not known just how serious the assassination plans were taken at Langley, but they make it abundantly clear that such plans were made. Quote, agency executives requested and received sketches of plans for killing Assange and other Europe-based WikiLeaks members who had access to Vault 7 materials, said a former intelligence official. There were discussions on whether killing Assange was possible and whether it was legal, the former official said, and quote. And that, right there, just by itself, should be reason enough to completely abolish the Central Intelligence Agency. Just the fact that this is an institution where such conversations even happen and such plans even get made to say nothing of the obvious implication that they wouldn't have such conversations and make such plans if they did not act on them from time to time. I just can't get over how this claim was openly confirmed by a mainstream journalism investigation and the public responses, oh wow, what an alarming news story, instead of, okay, well, the CIA doesn't get to exist then. I mean, is it not out of this world bizarre that we just found out the CIA recently drew up plans to assassinate a journalist for journalistic activity and yet we're not all unanimously demanding that the CIA be completely dismantled and flushed down the toilet forever? This would, after all, be the same lying, drug-running, warmongering, propagandizing, psychological terrorizing Central Intelligence Agency that has been viciously smashing the world into compliance with its agendas for generations. It is surely one of the most depraved institutions ever to have existed, comparable in terms of sheer psychopathy to the worst of the worst in history. So why does it exist? Why is there still an institution whose extensive use of torture has reportedly included rape, gang rape, rape using eels, snakes or hard objects, and rape followed by murder, electric shock rendered by attaching wires to the genitals or other sensitive parts of the body like the tongue, the water treatment, the airplane in which the prisoner's arms were tied behind the back and the rope looped over a hook in the ceiling, suspending the prisoner in mid-air, after which he or she was beaten, beatings with rubber hoses and whips, the use of police dogs to maul prisoners. I am, of course, being rhetorical. We all know why the CIA still exists. An agency which exerts control over the news media with ever-increasing brazenness is not about to start helping the public become more well-informed about its unbroken track record of horrific abuses. And if anyone in power ever even thinks about crossing them, they have six ways from Sunday of getting back at you, as Chuck Schumer once said. The date of the absolute last time the CIA ever did anything evil keeps getting moved forward. The CIA just casually had plans drawn up for the assassination of Julian Assange in case they decided that was something they wanted to do, but you're a crazy conspiracy theorist if you think they might be doing other bad things right now. The reason the latest Assange story isn't getting more traction and causing more people to think critically about the CIA is because the US government making plans to kidnap, rendition, and assassinate a journalist for telling the truth is so incomprehensibly evil that it causes too much cognitive dissonance for people to really take in. Our minds are wired to reject information which disrupts our worldview and people who've spent their lives marinating in the belief that they live in a free democracy will have worldviews that are resistant to information which shows we are actually ruled by secretive power structures who laugh at our votes. So to recap, the CIA made plans to kidnap and rendition Julian Assange and to assassinate him and his associates. The CIA also spied on Assange and his legal team and a notoriously untrustworthy key witness for the prosecution in his case has admitted to fabricating evidence. And yet the CIA is not being burnt into the ground and its ashes scattered to the Langley winds and the UK is still somehow proceeding right along with the US appeal to extradite Assange. I've said it before and I'll say it again. As much light as WikiLeaks has shown on the dark inner workings of the powerful over the years, the persecution of Julian Assange by those very same power structures has revealed far far more. The more they seek to persecute him, the brighter that light shines on them, making it easier and easier for us to see who they are, what they do, and how they do it.