All right, well welcome to the book map educational course. This is going to be a series here parts one through four We're going to go through part one today tomorrow part two and then on Friday part three And then next week we'll do it again and then get to part four as well Which will be about more advanced features today's course is going to be intro to basic market mechanics and hesitate to put the word basic in there. This is actually It's essential to understand this information, but it is as well Actually gets quite complex pretty pretty quickly, but this these are the mechanics that move the market okay, so we're going to go over this and in some detail and then you know show some some examples in book map and How you can identify these all right risk disclaimer trading equities and futures involves substantial risk of loss is not suitable for all investors Past performance is not indicative of future results For more information you go to book map calm. I become a member there and you'll have access to a lot of the free resources and then You can reach out to us at support at the locks pro calm or support at book map calm And I want to show a few more resources here so Here is our website We also have a Twitter. You can follow us on Twitter and then We also have a YouTube page And I'll reference this a little bit later because there's a few videos. I want to show you Okay, and All right, let's move on. Okay a little bit about me My name is Bruce Pringle. I've been a trader for 10 years in a variety of markets. I'm a product specialist at book map I lead the education trading here at book map and an expert in order flow and Market microstructure. Okay, I just showed the Twitter and the YouTube as well. So And support at book map calm, right? Okay, so overall this series of the goals here What we're going to go through in this educational course. Okay, we're going to provide you a structure Structured understanding of today's markets. We're going to cover theories And practical uses and we're going to give you something to take away and use All right, so we're going to give some strategies and some setups some training exercises And this is all hopefully going to allow you to With a high potential here To enhance your trading execution All right This is going to be a reference guide for you to return to if needed You will always have it and then during the daily webinars. We are going to Cover this in the live markets Okay, so you'll always have the course to come back to but in the live webinars will go over current Condition of the the live markets using the same techniques used or learned from these courses Okay, and we're also going to introduce you to advanced HFT or high frequency Trading concepts and applications and this is both for futures and equities traders Okay All right today's course what we're going to go through we're going to start off with basic terminology It's important to understand that that we're all in the same page here And then we're going to get into the market mechanics and in these mechanics visualized Why price moves price sweeps? Why price trend stops and price behavior? How it moves and then we're going to get into some of the training exercises later Okay, who is this course for right? So this is for Retail and professional traders alike prop traders a dome or price ladder traders And because we can show the historical limit order book and order flow. This is also applicable applicable to swing traders and Spread traders right so for the HFT environment a lot of the quants and HFT algo traders are especially going to Understand this today's lesson But there is still a lot of good information in here For for the quants financial engineers and students and this can also apply to Compliance officers Yeah, so terminology we're going to start off with liquidity. Okay, and we're talking about liquidity here Obviously in the market places. We're talking about the the limit orders. Okay the the depth of the market Where traders are lining up to be buyers or sellers? They're bidding and offering in a market and they're providing liquidity. They are making the market without them price would be Very very hard to define. Okay the BBO. Okay. This is the best bid and offer. Okay, that's The inside market exactly where a price is currently trading Hitting the bid. Okay, that's where we're going to talk about aggressive volume that Takes liquidity off of the the best bid. Okay, someone hits the market sell button and they'll take liquidity Lifting the offer offer is the opposite. They'll hit the market buy button and they will take liquidity off of the best offer Okay, the LOB the the CLOB and the dome okay limit order book centralized limit order book and depth of market Okay, they're all basically the same thing the the club is kind of important to understand though because The centralized limit order book is the Really what we're talking about here and and taking the data from there and then Transposing that onto the chart historically All right, we're going to talk about aggressor of volume classification. That's the market buys and the market sells The intent of trade that is the the traders lined up on the bid or the offer in the depth of market Okay, the current order book is the current state of that order book right now What's going on in the order book the depth on the offer the depth on the bid? the Best bid and offer the last traded volume and and the spread Okay, and then we're going to get in the historical limit order book and order flow Which I'll define it we'll see as we go on because we record all this data In that current order book and then extrapolate that and transpose it on to the historical chart Okay All right Let's see How can the order book and order flow data help you right well as I was just explaining the current state of the market any dome Will do this all right? There's no lag to it. It's showing you the liquidity at price levels is giving you the the best bid and offer and spread The current price and the last traded volume. It is the current state of the market Okay, and then it gives you an understanding of where price might go looking at high liquidity that you can target that's going to be on the bet on the depth of market in the on the on the bid or the offer Okay, and this gives you an advantage over the competitors. You can start to understand their activity Recall that this is a zero-sum game a structure within the marketplace Okay, and we're going to integrate this information within the historical limit order book shortly Okay, so market mechanics the we're going to go through some basic examples and Now this this course is about education. Okay, but we're going to show book map And and why that's because it visualizes this behavior Very very nicely. In fact the story of book map We came from the HFT environment developing algos trading in the high frequency Environment and needed some sort of visualization of where those trades were getting filled and Software was developed to understand that comprehend it and then Thought that was a pretty good idea and that led into book map becoming a product Okay, so that's why we're going to be showing book map here is to visualize these mechanics and you'll see exactly what I mean in just a minute Okay, so I need to show book map. I need to go over it here What are you looking at? In in the user interface this whole area here is historical data Okay Here is your current data here. Okay, this is your best bid and offer here Your last traded volume here and you'll see that this is the depth of market I'm going to show you book map in just a moment here, but this is the live market is a graphical representation of The depth of market. Okay, the current state of that market. All right, so here's your your best bid and offer here your depth on the Offer and your depth here on the bid Okay, all right, so let's let me show you book map and we'll get it up here. Okay All right Okay, so here's book map. We're looking at the S&P e-mini and Let's see. I'll start off here and we'll just work Backwards very very simply. Okay. I'm going to take off all of the the data here So that we have something very very simple and straightforward to look at Okay, and Indicators. All right Okay, so most of us are Very in tune to understanding a candlestick chart. Okay, so here it is in book map. All right and No further explanation is needed. You can see that between each vertical dotted line here. I have 15 minutes worth of data Okay, I'm going to start layering information on top of this Okay, first I'm going to add the best bid and offer Okay, now what we're looking at is the historical best bid and offer. Okay, we can let me zoom in a little bit here and so You can see this move to the upside here. Well, this was the best bid and offer within this candlestick period. Okay, so this is a one-minute chart and and you can see the The the closer of that candlestick, but here's where the best bid and offer was during that time Okay, the red line is the best offer. The green is the best bid Okay, now let's add on some volume dots Okay, so now what we're looking at here is the volume traded Within that best bid and offer. Okay, so this candlestick that you see here this one-minute candlestick chart Well, you can see the where that volume took place You can see the type of volume it was. It was a lot of buying that took place and You can see that we're giving you the overall Delta of this information as well So there was some selling in here, but not as much. There was more buying in fact I'm going to zoom in here to this area. I'm going to take a quick closer look here So as I start to zoom in we can really zoom down and and show exactly What unfolded in these markets? Okay, we can see the algorithmic activity here at very Subsecond levels and we're down at the microsecond level here. Okay, all of this data is recorded But you can see as I zoom out. This just becomes a bigger green dot Okay, and then you can see as I continue to zoom out We give you the overall Delta because there's so many so many trades that took place here that We need to Give you we only have so much screen space to give you something that is useful So this this data is aggregated only visually or graphically. Okay, and you can see now What comprises candlestick? Okay from the previous one here? So this is very much like a footprint chart you can start to understand where the volume took place how much or what type and Within how much of a time period here? Okay, so that's the the traded volume now we have that on the chart and Now we're going to add the heat map here Okay, so let's add that Okay, so now what are we looking at here? Okay. Well all of this this heat map is The historical limit order book. It's all derived here from the dome Okay, so as I was explaining earlier on this just go right back to this current market This window here We're giving a graphical representation of the liquidity in that limit order book Okay, so like right here. We can see 1347 contracts. Well that that area is painted bright white in the current order book window here So we know right right away. There's a reference here very high liquidity on the offer Okay, so that's what the it's just a graphical representation of that limit order book Now where this really gets interesting is that's the current market this window here But we we take this data and we transpose it onto the historical chart Okay, let me zoom in just a little bit and you can start to understand the behavior of these traders here on the bid Okay, look how they're adding and pulling liquidity in this area Okay, so we can start to understand their intent to trade at some of these levels Do they really want to be buyers or not? Okay, so that's the book map interface in general and We'll we'll look more at it a bit later but I do want to compare this to a dome just so you guys Really get this down. All right. So here's here's our dome. We have our best price here Well, let's go through the price ladder here as you can see in the dome and here it is in book map Okay, the depth of offer Okay, here it is in the dome these numeric values here And you can see that those numeric values match up here in in book map now I also included the graphical representation of these numeric values here Okay, that is the offer here on in book map Okay, here's the depth of bid Okay, so this is the liquidity here in the limit order book in a dome and then in book map Okay, and then here's our inside market. All right our level one data our best bid and offer our BDO Okay, so we just have our best bid and offer and you can see they match here within the dome Okay, and then finally our last traded volume this number here matches with the last price And here's your last traded volume with your last last price here Okay All right, so now let's get into the Integration of that current data. Okay the going through the order flow Data integration here the current data the real time in the dome is fleeting You know, it's you'll see those numbers Display very quickly and then they'll be re-displayed with and refreshed with new data So you'll have to remember those areas that may have been high liquidity or low liquidity And and that can be a little challenging to do because you have to remember specific areas And then when price comes back to those areas, are they still bidding or offering? Do they still show interest? That's where the historical limit order book and and data comes in very very Handy, okay, so we record all that data And then you can see and understand how we're looking at book map We can understand how it unfolded in detail in specific areas Okay, and it's very easy to see it and that gives us context to those those areas as well Okay, so like I like I mentioned that let's say we have a double top pattern Well, they were bidding there before or are offering there before With high liquidity and if we return back to that area, are they still interested? We'll get context from understanding the auction in those areas Okay, this gives you a nice advantage over your competition. All right, so now let's jump in here and and Yeah, here's our historical dome our current dome in the book and then Here's our current dome in book map Okay, and jump in here and that why does price move? Okay, we're going to cover aggressor volume Okay, market transactions and the intent of trade. Okay the a centralized limit order book auction Okay, so why does price move? Okay aggressor volume explained here. We're talking about the the limit orders are they're passive They sit or they rest Within the depth of market. Okay, they provide liquidity. They want to be buyers or sellers within those specific areas on the price ladder Okay, market orders. This is the aggressor they cross the spread and they consume the liquidity on on the in the depth of market Okay, they'll consume the limit orders Okay, so most of us are familiar with this but this is the Classification of the volume that we'll be looking at here is the aggressor classification the market orders. Okay, the transaction, right? Price trades where this aggressor is matched with the liquidity in the best bidder offer And then now let's start to jump in here and we'll go through some examples. Okay Here's current price trading on the best bidder offer. Okay here the last trade that just took place here was it was a market Buy with a volume of one right here. Okay. Now. This is just illustration We we can see the spread here. We have the the liquidity within the Best bid and offer here we have 12 contracts on the offer and on the best bid we have 16 contracts Okay, this is where it last traded here. So that is the current price Okay now a very very simple market Sell order. Okay, the aggressor hits the hits the bid With a market sell order. Okay, they consume the liquidity here. So we we did have 16 contracts while they consumed one and now we have 15 contracts and price has now changed Price has moved. Okay one tick And this is how the market Moves the aggressor is the one that that can move the market Okay Now here's an example of what that looks like in book map All right, you can see the the aggressor here these little green dots here our market buys Okay, and price was trading here at at 52 89. We're looking at oil Okay, and then you see the aggressor here the market sells with the red dots on the best bid Okay, so it's just going back and forth here now you can see Something pretty interesting already And you can see the complexity we're going to get into with just this very very simple binary example We're recording here algorithmic activity. Okay, I mean very very clearly you can see you can see the time And the orders and the size of the orders are all equivalent here So these these two algos are battling back and forth Okay, and you can start to understand That this this is really how these markets trade today Okay, there's all these algorithms that are trading back and forth and we can understand their behavior here within The historical limit order book. Okay, all of that record which would be rather difficult to see in the dome Okay, here's another example as well, and we're going to see a lot of this kind of information and data displayed in book map. This is an algo here that is Lifting the offer, but it's not really lifting price here. Okay, it's trading On the best offer Okay, and you can see it's very very clearly with the the mechanical movement here or of the buying and selling That they are consuming liquidity here, but they're not lifting price against them Okay, so this is they're accumulating a position here over time Without moving price against them Okay, so Now let's get into next. Why does price move the imbalance in the intent of trade? Okay, so what we're going to talk about here large imbalances in the order book That skews the auction All right Now the size of these limit orders is going to affect the best bid in the offer All right, so They may pull liquidity. They may add liquidity. You know, there might be a big spread now when the Mechanics mechanics here operate And you get our market sell order to move price. It hits the bid. Well, we might see a big move in that price without Much volume it's because they pulled their liquidity. There was an imbalance and They they pulled their liquidity on the on the bid and and the transaction occurs at a new lower price Okay, let's go through the example. All right, here's our volume of one Okay And and then they hit the bid here with another volume of one All right, so 12 contracts 16 here on the bid one is consumed that becomes the current price now We have an imbalance here in the depth of market on the on the offer. Okay, you can see previously we had You know pretty equal Book here. All right, rather equal. I think there was a bit of a skew in the on the bid side, but We can see this is rather balanced, right now we have an imbalance Okay 120 contracts versus it was 16. Okay 24 contracts and 32 they turned into 85 and 72 so we have a very heavy imbalance here In in the limit order book. Okay, they're they're offering here with a lot of With high contracts a big contract size how that affects price Okay, well we can see here these 15 and 18 contracts here on the bid these guys that they get scared They don't want to to trade any longer at these levels and they'll pull their liquidity Okay, so our last trade still occurred here with that volume of one Okay, but the best bid has now shifted down a couple of ticks Okay, so now we're down here Two ticks lower at 22 contracts. Okay All right, so with a volume of one. Okay sell market volume of one. They've moved price now One two and three three ticks here. Okay, we consume one Contract here and that becomes the current price and this is how the intent of trade can Effect and move price. Okay when in periods of high liquidity, you're gonna see this all the time okay, and I'm sorry of high vault volatility so Fundamental releases or economic data releases as well as just a skittish market there's a lot of volatility because there is a lack of Liquidity and in any imbalance with high liquidity You'll see pushes and polls of markets very quickly Okay, that's this is what this looks like in book map Okay, we have high liquidity here that stays in the book, but we come up into this area here And they get very very aggressive. We get an imbalance in that book Okay, and you can see that how it of how price is affected here Okay That is is pushing price down into an area and You can see we're gonna get very advanced about this We're talking about potential spoofing here into Liquidity here on the bid. Okay, but there's an imbalance in that book. Okay, so Advanced concepts the potential spoofing here in balance to a drive price lower and maybe get off bids filled In at lower price levels Okay, there's also You know strategies that you can and we're gonna go over later with momentum looking for momentum Or spoofing you can start to look for that or layering Icebergs in ignition ignition algos. Alright, so let me cover the ignition algo here. I you can see the example With the imbalance here in the in a limit order book on the offer. We see it once They come in again that algo is still working here and then finally you can see this one here And it finally does drive price lower Okay, so now we're gonna start to understand and comprehend this data Within the historical chart. Okay, because it's all recorded here and you can see the You know, the you know, we're not we're not talking about just this is not just Milliseconds of data where you know, this is 10 seconds between each vertical dotted line here You know, so we're looking at You know like a minute here of Price activity a little bit more Okay, but you're gonna be able to utilize and consume that data and look for you know a potential Order Execution here that's going to be enhanced Right. Here's another example. We have very high liquidity here on the Best offer jumps into the book very quickly and I'm going to show you a sequence here Okay, so we can also see them down here on the on the bid this 24 20 level and Let's how did this unfold? Okay, so here's that same action is here again And we can start to see how it affect price Okay, it affected price and drove it lower Into some of these lower areas here Okay, we're gonna we're gonna talk about this concept a bit later, but I'm gonna introduce it between short-term high liquidity Skewing the auction. Okay, and then longer term liquidity here that remains in the book Okay, so this longer term liquidity is already already understood by the auction All right, but this new information that jumps into these areas and then pulls It needs to be digested by the market Okay, and then and you can see that in balance that heavy imbalance has an effect on price Here's another example. You can see this is the the open and 9 9 30 open here we see an imbalance here driving up into high liquidity here longer term high liquidity It was basically in the market from the get-go of the 9 30 open And then here's our imbalances with shorter term high liquidity Driving price up into some of these areas Okay, so next concept. Let's go over sweeping of the order book So what we're talking about here is just not moving price back and forth. We're trading through one or more price levels This is an important concept to understand. This is typically how price trades into a new range All right, and we're gonna witness this with a combination of In balance in the order book and very sizable aggressive market orders Okay, so here's an example. We'll start off again here. Here's our market Buy with volume of one, but now You can see here. We have a market sell with a volume of 50 Okay, so what occurs they're hitting the bid with 50 contracts here. We have 15 15 contracts On the on the best bid at this at this point Okay, well it sweeps through that 15 so 15 trade that is the Last last trade that took place here is still the current price Now what what remains of that 50 lot order? Well, it's still still market sell But it already swept this price level, but it traded 15 so there are 35 contracts remaining In that big Market sell order Okay, so what what occurs next price level still hitting the bid It sweeps through this price level here with the 18 contracts Right, and and you can see we swept it and now there's 17 left still remaining in that 50 lot order And and it's still hitting the bid here, but we have 22 contracts here. Okay, so what unfolds? All right Okay, it takes 17 of them, but there's still five eight five remaining. Okay, and that is our sweep of the book Okay, this this 50 lot now is filled Okay, and and you can see we swept down, you know a few a few ticks here into lower levels All right Important concept to a lot of times and it depends on the market Thinner markets you'll see this a lot more often the ES you will rarely see this But you can see the spread has widened out here All right because they swept through all these levels here, but where's the best offer? Okay, it's still up here at this at this level with these 12 contracts Okay So there's a vacuum here Within there's a bigger spread the spread widens out between these two Okay, a lot of times the ES though very very quickly will fill in right What does that look like in book map? All right. Well, this is a fundamental release and We can see the Just massive Red dots here sweeping each price level as it goes lower Okay, you can see the vacuum effect that we're talking about as we return almost back to where we dropped from here Okay Here's another example, and this is a market Market buy okay sweeping sweeping up to new levels and we see the This is the initial release. You can see that's Here's a 10 30. This is oil is the oil inventories Actually, nothing really occurred for a few seconds, and then all of a sudden they really lifted the offer here Okay Okay, let's look at some of the advanced concepts and some of the sweeping here all right Like for example looking for pullbacks start to enter if you if you believe that the sweep here Was We're gonna start to accept down to lower levels. Well, then you can start to enter some of your limit orders in some of these areas here Okay, if we're looking for that pullback into some of those areas because there's been a vacuum All right guys. I see your questions here. I'm gonna go through all the questions later, but I Want to I want to continue on and get through the presentation Okay, so You could also play momentum looking for that sweep and then joining in Or you maybe you're looking for rejection and I'm gonna show an example of that You're also gonna see book flipping. You might see sweeps into icebergs and then those ignition algos as well okay all right, so here here we are with an example in Oil again and and you can see we swept down through to a lower level here And it looks like price is starting to accept down below this lower level here Here's our pullback to it and we get another continuation All right, we actually see another sweep to the upside. Okay, and it and this one it sweeps up into Basically where it dropped from up here But it's this is a little different here and I'll explain in just a second. All right We see yet again Another sweep okay price starts to accept above this level and we sweep through it We get our pullback here and we sweep on down yet again And we can see very nicely and cleanly we get our pullback right to where we drop from so this concept of Sweeping although the mechanics look very simple is very profound You can start to see we're gonna lead to a very nice setups to understand Looking for those vacuums, or maybe you want to join the Momentum on the way up Anyway, we can start to Look at some of these levels here and then also how they start to affect the volume profile We're gonna cover volume profile tomorrow, but you can see as I drew a line across here I'm gonna have our point of control up here basically for this range. Whoops. Sorry And and we that's where we come up and test Okay, now the sweep down through this area here is gonna be your low volume node And you can see it here and yet again Here's where we swept down and broke from again here and that is your low volume node here So now you're gonna start to understand the sweeping action and moving to lower levels or higher levels within the volume profile Okay, now here's an example of Rejection okay, and we can see that this is again oil that we have a range situation Developing here. We sweep down into a lower level, but we turn right back into the range okay, so You can you can also play it that way if This is a lot of the times what you'll see in this kind of behavior or stop runs Getting traders You know stopped out running the wrong way Maybe buying or I'm sorry selling the breakdown here and then trading back into the range And then you can see they actually traded to the opposite side here and grab all the stops On the other side. All right, so there's the potential here for understanding this and trading it as rejection Okay, here's the concept here of a flip of the book So here's our sweep as you can see And then here's the the limit orders on the on on the bid here. Okay. We swept through it and Yet now what do we return back to okay? We you know, I actually I would start to anticipate returning back to this level here But now we're starting to understand a flip of the book because high liquidity here on the on the bid Has now flipped to the offer and that's where we come back and test All right, not only once but twice and three times here Okay, so you're going to start to extrapolate and understand this data within the historical limit order book chart All right, so that's Sweeping let's get into why price trend stops. We're going to go through absorption and exhaustion Okay, absorption is the limit orders that that take up and absorb all the aggressive buying or selling Okay, it could also be iceberg orders, but we're going to cover that in the advanced Session and let's go through an example. Okay start off again with our market buy volume here of one and That's where current price is trading, but there's a distinction here Okay, we have longer-term high liquidity down here in the depth on the bid Okay, so 125 contracts and Compared to very very high compared to all the rest of the book Okay, now let's just speed things up here. We sweep the book lower into some of these lower levels here that 50 lot is You know there were 22 contracts here takes 17 Now there are just five left and that is the current price Okay, so we still have now. We're down at the one tick away from our 125 Contracts, okay, so they sweep it again here sell market order volume of 50. Okay, what happens? Okay, you hit the bid those five trade and now we have a volume of 45 Trading into these 125 contracts Okay The 45 trade now that becomes 80 contracts here on the on the best bid that they absorbed all of those contracts Or those 45 okay from that that 50 lot Okay, they hit it again here. Okay market sell with a volume of 50 what unfolds? Okay, so hitting the bid we have 80 contracts here Okay, 50 of them trade and now they're 30 left. They absorbed all of that Order at one price level okay, and So now that this this one trader or let's say it's one actor one trader They they came into the market very aggressively with 150 contracts one swept the book lower one Swept the book just one price level and then was absorbed and then that last 50 lot was completely absorbed at that price level Okay, and they're 30 contracts still remaining at that price level Okay, so let's say someone jumps in now And with a market buy volume of just one Okay, well if they're if the spread is still had widened out after that sweep And remains that condition just with a volume of one they've moved the price up three ticks All right, so what this can allude to a lot of different things We can start to understand trapped volume and some of these areas Or you know, maybe you're trading in down into an iceberg order here on the on the best bid okay All right So as mentioned the aggressive buyer lifts lifts price or lifts the offer with just one contract And that becomes they take one liquidity one contract of liquidity off of the 12 here and that now becomes the current price okay, and Let's go through the example here in book map. What does this look like? Okay? Here's our high liquidity here on the offer Okay, we see the aggressive market buys Trading into that area and they remain in the book Okay, these guys up here at 44 20 they want to to be sellers and you can see they continue to the aggressive market buys continue to trade into that area and they and the Limit orders on the offer absorb all of that aggressive buying Right it finally dries up here, and then you can see that they very aggressively then Hit the bid with large market sell orders. We trade below that level Interestingly enough just like the sweep we we trade now below at at a new level here Okay, and you can see some same same concept here down on the bid They're they're starting to absorb it down here, but they actually overpower the limit Buys here and they sweep through that level. Okay, but this is the absorption part up here Okay, another example trading into high liquidity here. You can see the aggressive Market sells taking place here on the best bid and they just don't take it any lower Okay, so any of that aggressive selling has been absorbed and and then we can see the Price they start to lift the offer with aggressive market buying Liquidity polls here and we continue on up Okay, let's go through a few advanced concepts V bottoms V bottom reversals pullback strategy that we covered earlier You can look for stop runs trap volume and book flipping as well and Let's take a look Right. Well, here's our sweep down to the bottom And then you can see look at how they very aggressively come in here. This is this is gold And they come in here with 149 contracts at this price level here of 1244 and a half And and they remain in the book. Okay, the You would maybe start to anticipate a move back to where it broke from but this information here Understanding the depth of the of the market Gives you that insight that We're not going back up to here because these guys want to be sellers at a lower level All right, here's an example in Apple You know we Bookmap was also available for for equities in the US And let's go through this a really nice example here of absorption Okay You can see the aggressive selling into some of these areas here and finally down here we see 2557 contracts trade on the Best bid you can see it's all selling here. Okay in our in our profile All right, and you can see all of the selling here. Look at the buying here. There's very little All right completely absorbed by the larger traders with their limit orders. Okay, and this is going to be our example with the V bottom here, but the All absorbed here. We do actually get that retest, but we don't go all the way down to the to the bottom We get we can start to anticipate those retests to Maybe where we start to see some buying come back in All right, and and this is what it looks like on the higher time frame. Okay, so a real very quick sharp drop into an area here on the On the bid completely absorbed and you can see the reaction that it had in the V bottom Okay All right, so that's it with the absorption. Let's go over exhaustion. Okay, what is it? It's the lack of aggressive volume activity Okay, so now you can see here We're gonna go through the market The buy market order here volume of 50 Okay, and that had already occurred so we still have 12 contracts here and that is the current price Okay on the best offer Okay now they they come in and they sweep the book lower lower here 15 contracts and and then And then 13 and then there's there's still hitting the Hitting the bid here now. We have a sell market order volume of 5 occurs here into these 10 contracts. I do need to Just mentioned here look at the lack of now. It doesn't have to be lack of liquidity for it to be exhaustion It's a lack of aggressor Volume that makes it exhaustion But a lot of times you won't see very high liquidity All right, so we come down into and now we're hitting the bid with five contracts into 10 On the on the bid so it trades those five And you and you can see that becomes now the current price Okay, next example. They continue to Hit the bid we have another Cell here of five what occurs? Well, they sweep that level Okay, that's your last traded volume now. We're trading down here on the best bid into these eight contracts All right But that's it. There's there's no more buying There's a lack of you can see that it started off as pretty big but It started to dry up in some of these lower levels here and instead now They don't come down and test the the best bid here these eight contracts and instead the Market buy with a volume of five Lifts the offer into these 10 contracts here and that becomes the current price Okay All right, this is what it looks like in bookmap and you're gonna see this all over the place in bookmap, right? You're gonna we can see we come down into an area and they're pulling liquidity In this area here, but look at the the the aggressor Okay, there's nothing no trades that took place here here here We finally get a little bit of market sell here But we test a little bit lower and there's complete lack of trading one tick lower Okay, well we rotate back up We come back down again and complete lack of trading no one's interested in trading at this level Okay, so the the mechanics here are that if no one it wishes to trade at this level Well price is going to trade higher Hey, it's going to look for liquidity now on the on the best offer Okay, now it's looking for For sellers and where are the sellers? Well, they're up in some of these areas, but there you can see them pulling their liquidity All right. All right as mentioned a lot of times what you get with this Absence of the aggressor is In these trending markets, you'll see the pullbacks and you'll see very little aggressor Volume take place at some of these areas. Okay, so you can see a complete lack of We have one two three four basically tests here and into this this price level in gold and And and no selling. Okay, so we rotate back up and we actually sweep the book one hire We get a minor pullback here And and you can see there's there's no one interested in selling. Okay, there's the sellers are out of the market Basically, right? We can also see look at the limit order book here. We see in a skew in that auction So where do we come back up into? Okay? We trade back up into the it's searching for that high liquidity on the On the best offer and we start to trade into that area We get a pullback again, and we can see lack of aggressive selling All right another sweep And then and then you can see we get the nice pullback here, but a lack of lack of selling all right, so Start to to piece these together into some strategies looking for exhaustion points after a sweep all right Okay Advanced concepts here starting to understand that lack of activity well One concept. I just wanted to to go over here was that it doesn't necessarily mean the that there's a lack of high liquidity Okay, that may exist right and this in this example It does and that it looks like they're starting to absorb it here, but then there's just a lack of Aggressive buying right we get one two three tests here And no interest at all. We start to rotate lower Okay, and I also want to integrate this into the bigger picture since we're looking at You know microstructural stuff here in the bigger picture. This is what occurred, right? We we can see the aggressive Behavior with the limit order book wanting to offer at lower price and then no one's willing to really take them on in these areas here all right Okay, and again the same concept of You can see there's a little bit of trading that takes place here, but look at the overall All right as we sweep higher here into a new price level And there's just a very very little Aggressive selling compared to the aggressive buying okay a lot more green dots here All right some sideways action here, but now you start to see in the trending areas Lot of green dots up in these areas very little trading here on the pullbacks Okay, and you can see the trending environment higher and where do we go? searching for high liquidity that you find here on the on the best offer Okay, all right so That's some of the basic market mechanics but And this is essential stuff to understand But we also want to integrate into this how it not just why it's moving Or stopping but how? Okay, so the volatility the depth of liquidity thinner markets versus thicker markets All right thinner markets like gold for example You're gonna see a lot of volatility you're gonna see a lot of price movement backwards and forwards because there is a lack of liquidity All right thicker markets like the S&P or the bonds are gonna be slower moving And you're gonna see a lot of pullbacks and retracements back to areas where they broke from They start to comprehend the behavior of the price movement and You're really gonna gain a lot of insight With some of these basic mechanics Okay, looking for flurries of activity. Okay within the auction Or the volume or within time cycles like the S&P cash open Okay, or in the NASDAQ as well Start to understand the speed of the markets How quickly is that occurring or was it a slow movement that took place? Okay, it's gonna give a lot of insight to some of these basic mechanics All right Yeah, the fast slow retest liquidity shifts, etc. Each market Has its own unique characteristics, but these basic mechanics are all the same All right, so let's end up here and Part one some of the training exercises Okay, so go back and start to identify these basic market mechanics Okay, that we just covered and Start to mark up your charts the more the better Okay, look for the variations in how price moved within these examples Okay, you can consider using the book map replay mode Is an excellent way of seeing this data. You can replay it again and again within that replay file And then you can start to draw your own conclusions from these examples Okay, noting the different times the different markets the varying liquidity the speed that it moves, etc all right, so Once you start to comprehend that you can start to anticipate these kinds of mechanics occurring in real time Okay, so understanding these basic market mechanics are critical Okay, this will lay the foundation for the next Few few lessons that we're going to cover all right Okay, so Tomorrow what we're going to go through and part two is we're going to take a step back and look into the bigger picture Historically and start to understand order flow within structures. Okay, micro structure and even Maybe a bit bigger Okay, and we're going to we're going to go over auction theory and and volume profile All right Okay, let me get to your questions and then we'll wrap it up and and call it a day Okay Yes, it's being recorded recording will be up on the YouTube page right and let's see here Algorithmic activity Michael. No, it's not all aggressive market orders But that example I showed that very basic example of accumulation is clearly an algo Okay, but most most the algos are you see Shifts in liquidity in that limit order book, but it can be a combination as well All right. Yes, our our what this is recorded Is the sweep in the book a stop run it could be But not necessarily whatsoever and we're going to go over that a bit more tomorrow within some of the structures Okay, looking at micro structures Okay Ashton you're talking about looking for a pause Yeah, well, I mean you're going to start to you're going to notice that you know Let's say you get you see a very aggressive sweep down into an area Well, we're going to cover it more in the setups starting to understand that aggressive sweep I did it auction correctly on the way down or way up And if that is the case it will lead to you know, you know higher probability of of you know looking for exhaustion on the way back up and Yeah, and then that that's where you can be you know starting to place your your limit orders Gunther no FX futures book map will work with but not forex and not the spot market. The reason being is there's no centralized limit order book Okay When exhaustion becomes induction to the opposite side Well, not not really You know, I mean it did Exhaustion is just the lack lack of activity So the market needs liquidity and and the aggressor to trade to be matched For that to take place Maurice Yeah, we Know no no think or swim platform at the moment Action. Yeah, I'm sorry.  This is go-to webinar. You don't see the other people's questions here Let's see John Yeah, the dots in book map are the That's the aggressor, right? They're taking liquidity Yeah, action Well, I mean you read that sweep, you know Understand that sweep and how it's auctioning and then and then start to anticipate and and like again like go through the exercises here You know to see it again and again In in replay mode potentially here and then you'll start to get an understanding of what you exactly what you're looking for You'll be an expert at it Absolutely, Maurice. This is Something Maurice is asking about swing trading And finding volatility for option trades as well Yeah, absolutely. This is what is is distinct and Unique here is that now with the historical limit order book. Let me take the candlesticks off here Okay, so let's look at the S&P right now Okay, well you can start to understand You know in because it's all recorded Even for swing traders very easily you can start to Incorporate this into your your trading I mean you look at how we came down into and that and we see the buying interest down here on the bid And then where did it come up to? Okay? Well, you can start to target these areas start to understand these areas of high liquidity here at 2430 in the S&P Okay Let's see afton more about exhaustion, okay I'm not I mean, okay, so exhaustion. Let's just take a look at the current market, right and Here let's look at some of this trending action. Okay, so The Look at this. I mean, it's not you know these these areas here I mean, it's not complete exhaustion, but look at the amount of trading compared To the higher highs. Okay, these are higher lows. Okay sweeps up Okay, and this is you know, we see it every day, right? We see a sweep up and a return back here, and we see a lack of Selling activity look at look at the overall buying here in this area And we can see that it's uptrending. We see more volume in green Aggressive buying at higher highs on the pullbacks. We see very little volume Aggressive cells. Okay, it might be complete exhaustion. This is complete exhaustion here We see nothing that traded here, but look at some of these other little areas here There's very little here it exhausted here. We got a retest though and We can see the there's just really a lack of selling activity All right Okay All right a few more questions here, and then let's wrap it up Maurice if you're talking about you know, you're talking about the Greeks in in options and You know, I don't know I mean how those are going to be valued in your You know looking at your IV for example, okay That's that's something a little different Right, but you I mean you I think this is you're still going to see this the same type of behavior here and I don't know if the IV is going to go down on some of these pullbacks right potentially, but maybe not right So it's a derivative and that's that's a little little more challenging There's another layer of information there. Okay? All right, and let me see here just a few more questions, and we'll call it a day well Option okay, so here's an example of the sweep of the book here To the you know in the S&P you're talking about this 1030 area Very aggressive it actually starts right here And there's a little bit of selling in some of these areas, but look at the majority right? and This was so aggressive And such a quick charge up Well, you know, there's there's a complete lack of of interest here We're starting to look at you can start to see a book flip here as well Start to materialize They're buying here on the they want to be buyers here on the bid But this was aggressive enough that we don't even get a retest of the area Okay, so we just have a higher trading range up here Right So that's that's how you're gonna have to start to comprehend by looking at your examples and studying and understand like you know You don't get that pullback right look at this look at this sweep here to the higher side You can start to understand that well, this wasn't as aggressive right it didn't take As many ticks to the upside here we get a pullback to where we actually broke from here All right, so that's that's how it's gonna help But you're gonna have to you know start to put those pieces together yourself You know, we're covering the market basics here and then we will go over more in Later in some of the other educational sessions oh SJ I mean on average what's the Approximately a monthly return using book map. I mean that's gonna very you know tremendously different trades Traders different styles of trading You know, they might be trading once or twice a day or they might be trading like hundreds of times a day or thousands of times a day Yeah, actually the stocks are look a little different. There's a lot less liquidity for the most part Compared to the futures Well, yeah, thanks for coming and tomorrow we're gonna go through part two and Just that review again here Part two is going to we're gonna look at some of the micro structures and the same market Mechanics within the the structures right and we're gonna start to get into auction theory and volume profile within the order flow Okay All right. All right guys. Yeah. Thank you very much. Yeah. All right Hope it was helpful and we'll see you tomorrow. Okay. Take care


Let's get into the big topic, open source, something that we actually didn't realize. This is so awesome. We are an open culture that is actually putting some space in that process that a developer or, let's say, as the communities of the system really bring them. Welcome to another episode of In the Clouds. I am your host, Stu Miniman, and still coming to you from our home offices, things are starting to open up a little bit here in the United States as well around the globe. Earlier this week, I actually went to the Boston, the global EBC for Red Hat, which was the first time I'd been there this year, and got to see, actually, we're working on studio there. So we have a temporary setup, got to see the space we're going to build, you know, a more permanent setup. And I'm looking forward to the day where I will be able to sit down with an actual guest in person for this program. But until then, happy to bring the guests in remote, it makes it easy. We can just go meeting to meeting to meeting, and just some of them get broadcast out to the world. So really happy to welcome to the program Mike Barrett, who leads the product management on the OpenShift team, which I'm a part of. Mike, it is great to see you. We've got some exciting things to talk about here. How are you doing today? Great, and thanks for having me, Stu. I love this program. All right, awesome. So, hey, just for our audience, you know, could you just give us a bit, you know, how long you've been at Red Hat?  We're going to put a link up in the chat there. Your team actually does like a 90 minute deep dive. So if people want to know all the wonderful features and all of the things that are there, they can go watch that. We, of course, are going to up level a little bit, talk a little bit more about the cloud piece. But yeah, why don't you do your own introduction, please? Yeah. I mean, a little bit about myself and how I got here. You mentioned Boston. We have a Boston Connections, Stu. I lived in Boston for 14 years. I went, I was in Chestnut Hill, Brighton, Chelmsford, Watertown, Medford, Lynn Shore. So I bounced around quite a bit. But yeah, you know, it's interesting enough, I got into computers through finance and marketing. I was a finance and marketing major at Boston College. And I realized very quickly that in order to excel in those studies that I would have to do some coding and models, stats, predictive analysis, all that good stuff. And then when I started to get in the computer science areas, I sort of fell more in love with them. And that brought me into Sun Microsystems in the late 90s. And so I'm at Sun Microsystems during the internet boom, during the dot com bubble where everybody's talking about how we're all going to be millionaires, right? And I'm working on servers that are more important or more expensive than my apartment. I'm working with like these industry huge names that have gone out now and started major companies. And it was sort of a time of my life back then. Then I, you know, I get into Sun through tech support and that is stayed with me, has an experience and it still stays with me here at Red Hat, how you have to be very connected to the customer. And during that time in my career, I was taking probably 50 support incidents a day. You would hang up the phone, you would pick it up, you would work 25 whip. You know, you have that case load always in your queue turning. But that really brought me to an understanding that I wanted to get into product management. So it was, how did this happen? How did that, how could that fall? How did somebody not think about that, right? And so I gradually went from support to sustaining the fine fixed, to ISV partnerships, to field enablements, to technical marketing and then into product management. And that was my sort of trajectory into product management. Yeah, it's interesting, Mike, you and I have some parallels there.  So when I joined EMC, I worked there for 10 years from 2000 to 2010. And it's funny, you know, Sun, Sun hardware and all of that stuff there, you know, we got to talk about that and everything. But as like the junior product manager, they were like, Oh, hey, give Stu the stuff that nobody understands and we can't really figure it out.  If rel existed, the job would have been easy. But back then it was, Oh my gosh, how do we support that? We only had like one engineer doing the integration testing of how that worked. And when Red Hat came out with Raz and then rel, it made our lives a lot easier because at EMC we were like, Okay, enterprise production workloads. You know, that's what we're all brought to the market. And so it's interesting to watch that journey, something I'd watched Red Hat for a long time and of course joined a year and a half ago. But it does tee up, you know, my background's infrastructure. And one of the questions we've had for the last decade, you know, or more is with cloud, you know, does hardware matter?  It's only $350 million. I mean, you know, 350 million is that big?  So 350 million is not an insignificant acquisition, but it has had a large impact on the cloud because Annapurna labs is the chipset that is now the Graviton servers. What I've heard in the market is the, you know, might be the largest volume ARM server in the world, and that brings us to where we are with 4.10. So, Mike, you know, ARM servers in the cloud with Amazon, you know, tell us about, you know, what we have and why we think this is a pretty important thing for our customers. Yeah, I mean, I'll sort of really high level and then we'll dive into the actual release and what it does for hardware. But yes, to answer your question, yes, hardware still matters. And in fact, that's probably the only lesson I learned when Oracle purchased on microsystems. We were tasked with how do you accelerate application patterns and application benefits with operating systems with virtualization and with hardware sort of accelerators. And what I realized for the first time in my career was that the application stacks have a lot of RAS, reliability, availability, scalability. They have those features and they almost try to duplicate what the operating system and what some of the platforms are trying to provide. And so the paths, like this paths that came to be years ago was a good battleground to consolidate an application in what it wanted out of the hardware. It was a new way to vocalize how do I get CPU? How do I get memory? How do I get another instance of myself? How do I make sure that my persistence is there? And Kubernetes really helped do that for us. And so now we have that layer and we want to bring back hardware. And I got to tell you, when we first started this project of bringing hardware attributes into Kubernetes, there wasn't necessarily a lot of partners or friends. There were some like Intel and Nvidia and companies like that that were like, yes, let's double down on that. Let's go after it. But a lot of the Kubernetes ecosystem were primarily really focused on clouds and virtual machines at that time. So we coined a phrase, Kubernetes native infrastructure, where what if we could take a step back and we could take some investments in some other areas of the company like our virtualization stack, our rev, our KBM, our QEMU knowledge, our ability with open stack and everything we do with network interfaces and IPv6 and pneumo awareness.  How do we bring that into Kubernetes? How do we potify them? How do we get them to run in a way that would be Kubernetes native? And the project took a couple of years to really get off the ground. And 4.10 is really a declaration. 4.6 was the first step where we had really features that customers could touch and feel in production. And it took a couple of releases to round off some edges. And now in 4.10, we're really hitting the home run. So in 4.10, we announced the support for ARM. And I got to tell you, it wasn't an easy decision as easy as you would think. You would think everybody loves ARM. This would be an easy decision to go invest in ARM and do it. But you really have to know your customer base and you have to know how they're going to be using ARM. And that has a lot to do with there's no one ARM. Like when you get into the world of ARM, there's a lot of different server specifications. There's a lot of different ways people build those ARM servers. And you really have to focus on very precise investments. We decided to go out with AWS ARM first. So in 4.10, you have AWS support. You also have some bare metal on premise for a server specification, not the cool stuff in your office. Let's do the more expensive ARM servers are what we're supporting right now. But that has a lot to do with our Edge journey and where we're headed there. Azure will most likely be next on the roadmap that we'll declare support for. And right now with the ARM support, it's a homogeneous cluster. So everything in that cluster and that Kubernetes cluster is going to be ARM. And our releases at the end of this year will allow you to mix those in a heterogeneous way with other X86 workloads. We do that because a lot of the feedback on these use cases for ARM right now are QE, just massive cost reduction in your QE spend on a lot of these clouds as you move to ARM. And that was a driving force there.  Can I just run it on that? Well, no, there's there's a amount of resources we need underneath. There was all the work that our Linux team needed to do. So, you know, rel support for ARM.  You said we started touching it in 4.6. Here we are with 4.10.  And then, you know, we've got a robust roadmap going forward. Is that right? That's it, exactly. So, we enter into this multi-chip world, first supporting power, IBM power, then we added support for IBM Z. During that time, we sort of built our chops on how to do a sort of multi-arch engineering team.  You have to do a lot of heavy lifting there. So, we were doing that heavy lifting. We were bringing on those. And we were lucky enough to stand on the shoulders of rel. So, rel had been doing this for a decade previous in terms of multi-arch development practices. So, it was a great combination of standing on rel, bringing those features in and getting that pipeline out. Outside of ARM though, when you talk about bare metal, bare metal brings with it a lot of stuff that you have never really considered. And 4.10 has a lot of those other features in it as well. When you talk about bare metal, you have to have a way to land. So, you're adding bare metal to a distributed system, right, where everything is supposed to be the same, where the end user is not supposed to have to carry the burden of understanding this box as a GPU, but not that box. So, there's a lot that you have to add to the Kubelet in terms of having it discover those features and sort of broadcast those up to the scheduler and getting those engineering projects into upstream Kubernetes and then downstreamed into the product itself through our node tuning or NUMA topology awareness in the scheduler. We support precise time protocol, which is timestamps on hardware and clock time in the APIs that you're calling out of the kernel. Device manager, being able to compile drivers for Intel cards has your deploying the workload, like mind blown. These are all the things that build on top of each other. I mean, SRIOV throughput, being able to talk to a service processor on a server. There's those nuts and bolts features, and then there's even philosophical differences. You hear a lot in this world that devices or operating systems or nodes, members of this distributed system should be ephemeral and they should be able to be rebooted whenever you want to reboot them. A very big design premise in Kubernetes and in OpenShift is that you design your cloud native applications and you can bring your nodes down and it should be absolutely no problem to you to reboot your nodes. You should repave them when you reboot them and so on and so forth. With Metal, you don't necessarily want to reboot them as much as you're rebooting your virtual machines. That was a big thing to put in the product. From 4.10, we allow you to do that. We allow you to have more control and awareness over when your nodes get cycled and how they get cycled. Michael, a lot there to unpack. Actually, we've got Coder Grammar has been watching. We're really excited to get their hands on 4.10 and actually set us up for an issue you want to talk about. They asked about the Sandbox containers, Cota containers. We have some updates in 4.10 as well as we've really seen a maturity in the OpenShift virtualization. Maybe explain those two topics because those tie into the things that you were just talking about. You have your container on one spectrum and then you have your virtual machine on the other spectrum. We cater to both of those with OpenShift virtualization, which is a Kubbert project. Then you have the obviously rail containers. In between, you have Sandbox containers. These are what a lot of people in the industry will call micro VMs. REL sort of invests in QEMU and we have a more sort of slimmed down QEMU that's multi-purpose. We feel that's a very robust solution for this middle ground where you want some isolation from the virtual machine, but you also want some of the performance and some of the management of the container. Lo and behold, you have Cata containers as the interface. It's going to help us a lot on build strategies. Anytime where you were faced using a privileged container or having this need to put root into a container, before we would mitigate that and deployment practices, making sure those only landed on certain boxes. Now with Cata containers, you have more of a distributed nature. You can really fulfill those use cases cheaper, if you will. We're super excited. It finally went GA. It's been tech preview, I think, for two releases now. So, stable and ready to take your production workloads. Yeah, it's always interesting. Mike, you and I both get to talk to a number of customers and we've reached a maturity level that early days of Kubernetes, was building new applications and modernizing everything. I want to use all these wonderful new workloads. We announced this at the NVIDIA to highlight some of the AI and ML workloads we're doing. Well, there's some workloads that it's going to take me longer to modernize them. So, we need to give those pathways. Can I manage them in a new cloud native way? And that's where things like the OpenShift virtualization built off of Qvert can help with. And, of course, security, huge concern. Everybody wants to make sure there's there. I remember when containers first came out, it was like, oh, my God, is there any security here? Let's just line up. Every container is tied to a virtual machine. Well, it's matured a lot. There's so many pieces throughout the entire stack that we do. So, can you speak a little bit to customers, some of the use cases that they might have and that maturity of the entire space? Yeah, I think, I think you hit it perfectly. With OpenShift virtualization, which is a Qvert open source project, we have a lot of people that are sort of lifting, shifting virtual machines. These are people who had virtual machines that hold them in production and they want a new way to launch them. They want a new way to consolidate them back to that API we were talking about before, where I have a consistent way to ask for CPU memory disk and IO and routes and IP addresses. That was the point. When we designed OpenShift virtualization, we could have totally taken the path where we take OpenStack and Rev, and we sort of put them side by side next to each other and put a user experience on top of it. And one of our competitors went down that path with their virtualization technology. We felt that we needed to do some heavy lifting, right? That if you truly believe that you're into containers, that you're going to have more containers and virtual machines over the next eight years, then you probably want to bring the virtual machines into the same sort of dynamic, the same distributed system, right? It should be able to scale up and scale down in the same way, the same YAML template. It should be able to ask for CPUs and memory in the same way. It should be able to get an IP address, a route, a URL. These all need to be the same in the system for you to be successful mixing these old virtual machines in with these new containerized workloads. And that's what the design premise was around OpenShift virtualization. In this release 4.10, it actually picks up support for service mesh, which is mind-blowing, right? A layered product is now sitting on top and bringing these products together. So yeah, it's been very successful for us and we're happy we made the investment. It is a very successful upstream project as well. You'll get upstream projects. You look for multi-vendor contribution and Qvert is one that does have a lot of multi-vendor participation. Yeah, absolutely. It's something that, you know, I remember first hearing hearing about it, Mike.  Right. Do I want to move things forward, be more modern, you know, containers and Kubernetes? Is that the experience that I want to build around? Or do I want to try to backport things and be, as you said, more of a sidecar with, you know, older environments? So it's a little bit of work for customers to move to a new learning environment. But overall, that's going to be helpful for the business. Everybody needs to be able to move faster. Kind of leads us to our next topic of conversation. You know, we mentioned the AI ML workloads. That's a big focus we've had for a number of years. The automation that's really needed for the scale and, you know, changing of those environments. It really has been a nice match for, you know, what we've seen in Kubernetes and OpenShift. So, you know, what does 4.10 enable that I might not have been able to do before when it comes to those sorts of workloads? Yeah. So when you start talking about bare metal, I got to say bare metal, although it's not the biggest population, when you look at all the possible environments that are running on OpenShift, it is the one that's growing the fast year over year. And a lot of that growth has a lot to do with intelligent applications and this need to allow more and more people to have access to GPUs. You know, this era where only data scientists and only the most privileged in the company have access to the best hardware is at the sort of the tier point of going away. And so now we need a way to have pipelines for the use of these GPUs with PyTorch, with CUDA containers, with a lot of the NVIDIA stack. And NVIDIA, at their conference, released this wonderful suite of tools that if you just add the platform, the OpenShift, and you load these tools on top of, you now have an out-of-the-box experience that allows you to really add security, allow what an enterprise would need in terms of their compliance, add pipelines to bring people in and start mixing those coding patterns with the results of a lot of the intelligent applications that only data scientists used to have access to before. We have a lot of customers sort of building that themselves, and that's a successful project as well. We helped there with Open Data Hub, which is a reference architecture that allows you to plug in a lot of other peoples, other vendors, our ISV partners, solutions into that. But this NVIDIA solution that just launched this week is incredible and we're proud to have them qualify on OpenShift and open it on OpenShift. If you want to see it, they also have something called LaunchPad, where you can go to the NVIDIA site and for free, launch it on OpenShift and get that experience to that tool set. Along with that comes support for, you know, another one of their cards, GPU sharing, GPU utilization is now shown in our user interface, where we used to just show the cores in the user interface. There's actually GPU support on ARM in 4.10, so you can sort of mix the two new features together. Yeah, a lot of incredible partnerships. And I got to say it's been great working with NVIDIA over the years. We first created Node Feature Discovery and special resource operators and device managers and a lot of automation in those areas. NVIDIA was able to bring those technologies together in the NVIDIA operator. And they supported on everybody's Kubernetes, but we had a really great partnership bringing that into the market. Yeah, so, Mike, we got an interesting question. I think that one that tees up, you know, that customer journey. So when I think back to the early days of PAS before containers and Kubernetes were a thing, it was really kind of narrow as to what applications we can put on it. It was, you know, okay, I want, you know, microservice 12 factor applications. You know, that's it. And I'm like, well, I'm going to have some of those. But the question says, you know, many customers aren't even ready to do lift and shift. They want to move slowly, you know, to paraphrase what Ockman says, you know, how do we meet customers where they are and move at the pace that they are ready to. So how does OpenShift help there? Yeah, I would say OpenShift, you know, going as far back as even pre-Kubernetes just coming into Kubernetes. We were one of the only vendors that felt you as a user had the right to say, I want it to go at my own pace, that we weren't necessarily ever going to force you into a felt 12 factor sort of position. And what that means is we were very concerned about persistent storage. We were very concerned about how you get your IP addresses. We were very consistent with placement, with scaling practices, making sure that horizontal scaling wasn't necessarily the only scaling possible. And a lot, you know, I want to say it was education or sort of awareness that drove us there, but we were in our, you know, an operating system company at our heart, right? And we are trying to bring workloads into a platform. And so we're going to go out of our way to make sure that you can run complex applications inside our ecosystem. And so we were one of the first to really invest aggressively on stateful sets in Kubernetes. We were one of the founding leaders in custom resource definitions. We were, you know, being able to control a lot of things that our clouds could care less about, but more legacy applications will break if they don't have it. Those are a lot of the projects we were investing in and Kubernetes is right at to really allow customers to go at their own pace. So it's something we're definitely proud of. Awesome. Yeah, Mike, that's great. And something I think people maybe aren't as aware, as we said, you know, when we learn a technology at first, that's kind of how we think of it. So, you know, Mike, I know in the last year and a half that I've been here, one of the toughest conversations is, you know, customers that, you know, did a lot of work on OpenShift 3. OpenShift 4 is almost a completely different product. There's so many things that matured in the Kubernetes space and that, you know, your team learned a lot. And as you said, made some important decisions as to how to build things. So this space moves so fast, as we know, we've now gone from four releases to only three releases a year, but there's so many pieces in it. So I did get, we got one question, want to open it up to you as to some of the other cool things that you're excited about in this release. The audience question was serverless, which is an area I've spent a lot of time watching and was really excited when the eventing capability is now in, you know, Knative, which is the container-based serverless, and that's there. So maybe, you know, if you talk a little bit about serverless and then some of the other pieces that you're excited in the new release. Yeah, well, serverless, and this is going to go down at KubeCon as well, in Amia, in Spain, I believe, right? And next month there's going to be... For once in May, yeah. Yeah, they're really going to celebrate the fact that Knative goes to 1.0, right? And so this release in 4.10, it's a different release number for serverless, but we graduate and we move it to 1.0. We also have a nice roundout of run times that we're supporting from Rust to Go to Quarkus to Spring. So just a lot of content is now available to you there. Some of the... there's some UX changes in our user interface that really help develop our experience around serverless. Somebody interested in an API-driven topology is important and definitely there. But yeah, a lot of stuff in 4.10 that we're proud of. 4.10, you know, 10 releases of 4.x. And there's that movie GrossPoint Blank where it's going, 10 years, 10 years, man. And it's hard to believe that we did 10 releases in like four years. I think since we... this will be year number four, since we released four. And early on in any product, you're going to be building windows and doors and floors and foundations, big items. And then as you graduate into these higher numbers of the releases, you get to go back and put in the trimmings and make things extremely nice. And that's where we are, right? We were able to fix like 45 RFEs in this particular release, which are requests for enhancements coming from actual end customers, which is a lot to get into a minor release. So definitely proud of the team. There's a lot of... we talked about the bare metal, but there's a lot of stuff happening in infrastructure support, right? And don't get me wrong. OpenShift is Kubernetes. You can run Kubernetes anywhere. The difference is what automations you want with that installation that you're experiencing. And when we looked at what we wanted to do with 4.x, we wanted to realize what infrastructure you were installing in and add automations around that infrastructure. And so it's taken us some time to go through every infrastructure on planet Earth and put a lot of those automations in and a lot of those Kubernetes on by default, right? And in this release, we do it with Alibaba. And we do it with IBM Public Cloud and we do it with Azure Stack Hub on-premises. The Azure Stack Hub kind of exploded in requests around the time of the big government bid. I think Microsoft got a lot of the attention there because they had an on-premises solution and a lot of the government agencies wanted support for Azure Stack Hub, so we add that in. So when you take a step back, now we have just about every major cloud and every major infrastructure provider on-premises with automations out of the box that drive you through using the most you can get out of those infrastructures. So that's it.  That's a great proof point, you know, globally where we're pushing there. My understanding, Mike, that is tech preview, right, from the Alibaba piece. And it's still the IBM platform. Yeah, and there. But the other one, Azure Stack Hub. So, you know, we've had OpenShift on Azure for a long time. And the way Microsoft positions it is Azure Stack Hub is we're extending the public cloud to your data center. I'm curious, you know, what's the nuance there of, okay, we could support OpenShift in Azure. Well, this is just, you know, a rack of certified, same software. So, you know, it's great that we can extend and cover the hybrid solution for Microsoft. The question always is like, the devil's in the details is like, how hard was that to do?  And therefore, that's why it took us a little longer. It's definitely different. And it's, you know, slight on Microsoft, when you look at all the infrastructure providers, there's literally differences between regions even. The APIs change on you and they're not necessarily documented. And when you're doing the sort of low level automations that we're trying to perform for the customers, those things are big hurdles to get over when they are different. And so, APIs are definitely different in Azure Stack Hub that we were looking to call. We even had to go into our cause, our operating system, and make some changes on how we sort of inject username and password and networks at time of boot. So that needed to have some tuning, how we do networks, how we do DNS, how we do load balancers, a lot of changes in those areas. Well, I mean, Mike, that really proves that, you know, that that's one of the key value propositions of OpenShift is if I'm a developer, I don't want to have to think about the fact whether I'm deploying an Azure on Azure Stack on VMware. Oh, great. OpenShift lives all those places. I'm not going to have to think about that, you know, from a development, from an operation standpoint, we take care of that for them. And that proof point, it's good. I know, you know, we work with a lot of the cloud providers, as you said, and as they go more hybrid, we should be able to live in those environments too. Yeah, that's our problem to solve for you. Yeah, so no shortage of things for your team to work on going forward though, I'm sure. Yeah, definitely not. And there's going to be another infrastructure that pops up that people want that's completely different. We'll have to go work on it. You know, another area of the release that we're really proud of and it is the combination of our advanced cluster management and our open data foundations projects coming together. What could they do together to solve a big customer problem? And it's around disaster recovery. So when you look at disaster recovery and you look at these projects that we were invested in, we found a sort of a pattern and a picture that we could bring together. So when you look at the projects we were sort of investing and moving forward last year and the year before, we have something called ODAP, OADP. It's an OpenShift API for data protection. And this is being used as an API on OpenShift by a lot of backup vendors in our industry. So third parties outside of Red Hat are calling this API to help them discover what are all the application components. So you want to back up an application. Kubernetes doesn't really have a good definition of application and it's got all these bits and pieces and labels of different secrets and routes and all these other components. It's got a project called Valero that helps you scoop those up to find them and scoop them up, but also you want to be able to call a snapshot interface for the CSI plug-in and Kubernetes at the same time. You want to get the persistence and all the guts of the application. And through this single API call, you can like snapshot it, you can back it up, you can restore it, you can schedule it. And so we have all these people entering sort of the OpenShift experience through a third party vendor, a backup vendor calling that API. We also have a project called a ramen of all things, the noodle dish. But this allows you to sit outside of a cluster that you're caring about up at the ACM level and have operators that you're asking to help maintain the sort of deployment of an application in more than one location and backing up and restoring. So now I can deploy an active-active application and I have something that's intelligent enough to look at not only what we just talked about before, all the application bits and pieces, but also at the Ceph layer, the underlying storage layer using something like Ceph Georeplication. And having these two clusters use that underlying Ceph Georeplication to replicate that data across those two locations and have a consistent way to automatically migrate through maintenance or migrate because of an outage. So all that comes together in OpenShift 4.10 and ACM 2.5 and ODF 4.10 and that releases next month when those layered products release. But something that we're really looking forward to getting customers hands. We have always been asked for disaster recovery for OpenShift and we're finally delivering it. Yeah, I guess I'm sort of a related topic, Mike. We talked about hybrid and edge, but one of the things that we have a lot of experience is not just the customers in their environment, but for many reasons often customers will need to run in a disconnected mode. So very different from the cloud providers. I've always got that heartbeat. I'm going back to so what's the latest when it comes to, you know, disconnected or any, you know, pauses in connectivity. Yeah, disconnected has been a hard egg to crack. When you look at the container technologies, they all have a prereq that you have a container registry. So if you're going to have a container, you need a registry to stick it in, but if I'm the one giving you the registry, how now what are you doing?  And so there was a dynamic that we needed to help customers work with and we we decided to take our quay investment and create an all in one slimmed down quay. Internally, it was project baby quay and and this allows you to not only have a place to pull things down and now have a command to help you pull those things down. When I say pull down, it seems like an easy task, but if you just blindly pull down, you're pulling down like 400 gigs of software in the OpenShift ecosystem of all those CNCF projects that we're invested in. So we needed to give you a filtering command so that says, hey, I only want the latest of those operators or I want only this channel of OpenShift so you can really filter in on what exactly you wanted to pull down. And then how do I stay up to date? So the biggest problem with a disconnected customer isn't necessarily the first install. It's how do I maintain that investment that I just installed that is disconnected. Will something in the product tell me that I'm out of date that a new version is available. So we had a through our core West acquisition for the connected customers for years previous we were providing this update service that allows you to connect up to Red Hat and in your console we show you that there's a new version available and that you should upgrade and then you click an upgrade button. We were not providing that in a very clear consistent way for our disconnected customers. And so now we have a way for you to put that metadata about new releases into that baby quay and allow your your clusters to connect to it and have that same in console experience that says hey, I'm out of date there's a new version. So a lot of niceties went into it and we were lucky enough to have a very strong public sector in terms of our employees that work there. That really helped us even into some some coding practices to get what their customers wanted in terms of a disconnected experience to start showing up in the product itself. So it was a definitely a great project to be a part of. Yeah, awesome. Well, and I'm glad Mike thank you for helping clarify at least your pronunciation of q you a why I've heard it pronounced key I've heard it pronounced quay. So, you know, always those debates as to some of those things so we've been putting in the chat in the comments. There's links to hear more. There's so many pieces apologize if we didn't get some of the questions you have, but Mike, I got one last question for you, you know when we look at the last two years. You've got a large organization.  I'm sure you've got way more slack channels and workspaces than I would want to know about. But, you know, there's changes you've had people that have never met any of their peers.  Yeah, so T shirts are important in this industry stew. Like when you celebrate and it industry you have to get a T shirt. So we do a lot of swag in those areas.  So if you're, if you're in G meets as a team, if you're in Slack as a team, you need to have time for happy hour over G meets right so virtual happy hours. We share that with our engineering teams in different locations. And that's a great time to sort of unwind and have a conversation that you would have called a water cooler conversation. So we've tried to do those things over the pandemic. It's definitely helped us, I believe. But we're also very excited that things seem to be returning. We're excited that sort of travel to shows and whatnot are starting to turn on. And I think we're, we're willing to experience a road again. I think what we need to be conscious of and probably a lot of people are going through this is making sure that we're visiting customers before we're visiting ourselves. Maybe it's been a it's been a while since we've seen some of our best and most friendly customers. So definitely looking forward to getting out there and shake hands again. Yeah, no, Mike, absolutely. I mentioned at the top of the program that I got to go to the Boston office that is our global briefing center. I'm excited. I've got some, you know, upcoming meetings with customers and yet to your point working in tech. It's not just a job. It's also a wardrobe. I'm sporting the Open Shift Commons, you know, North Face from some of the Commons events. Quick shout out to those people attending. QCon EU, as Mike mentioned in May, there will be a hybrid Open Shift Commons event. You can definitely, you know, look online as to how to join that. So, Mike, 4.10, so many things in there. Super exciting. Again, in the comments we posted, if people want to dive in deep, there's, you know, the blog, the press release, the 90 minute, you know, session that your team did. It is great. Thank you for joining us, sharing with the audience and look forward to talking to you more in the future. Yeah, thanks for having me, Stu. It was a great time. All right, and really appreciate, you know, this topic, you know, lots of interest from the community, you know, do reach out. Mike and I are really easy to get in touch with. Online, happy to answer your questions. Hit us up through the social channels through the websites and you can get this. And we've got lots of great programming coming up every two weeks. We try to bring this program and thank you so much for joining us on your journey in the clouds.


Hey guys, how you doing? This is your boy Rich from RichTVLive and you too can join the club at richpicksdaily.com where you can learn how to win and trade. Hi, how you doing? I'm your host Rich here on behalf of RichTVLive with our very special guest, the president of Benchmark Metals Inc. Jim Gregg, how you doing today Jim? I'm good Rich, thanks for having myself and Benchmark on your program. My pleasure. I'm really excited to have you on the show and have our community learn more about your company. Jim, can you tell us a little bit about yourself and how you got involved with Benchmark Metals Inc. Yes, so Benchmark is a gold and silver explorer that's rapidly moving to a mining decision in north central British Columbia, Canada. My team and my partners that are not only on the board, but project managers have worked together on some exceedingly good metals ventures in the past, and we all convened and combined here in 2018 to launch Benchmark Metals. And over the course of four years, our technical team and the financial experts have vaulted this company very, very quickly with great results and a three million ounce gold and silver resource. Fantastic. Really excited to learn more about your management. So can you tell us about the management of Benchmark Metals and especially their past success in the public markets? Yeah, absolutely. So our senior chairman and CEO of the company is a close personal friend. We've worked closely on many endeavors together in the past, but I suppose one of John's flagships endeavors has been in the Yukon. And so John was an original founder and director at Caminac. And Caminac sold their coffee project to Goldcorp, one of the largest gold mining companies in the world, in excess of $500 million. So this was a large win for shareholders. I've been involved in multiple other endeavors, but in recent history, one company called Keegan Resources and Keegan is a stock that ran from 25 cents to close to $10 in a very short time period. Over that period, we went from zero ounces of gold to in excess of 5 million ounces of gold and put a mine into production. So it's not just John and myself, but there's other senior members on the board and on the executive, you know, rearrange in age anywhere from about 30 to 60 years. So we've got some younger blood in the threshold, but we do have a compelling history of making money for investors in the metal space that could be copper, gold, silver and other metals. But we have an exceedingly good track record of finding new discoveries or finding existing projects that need a new technical eye on them. And, you know, the board and the management at Benchmark are also big shareholders. So we're not about salaries, we're all about moving the share price with results. I love to hear that and I know our community will as well. Now the company recently announced new results from seven infill and expansion drill holes from the northern portion of the Cliff Creek deposit. Can you tell us a little bit about this drill program and what it means for benchmark metals? Yeah, absolutely. So we put out some exceedingly good numbers. Actually every week we've been pushing out some good numbers for the past month. The drill numbers there that you mentioned are all about expanding the existing resource. They're infill drilling that is filling in gaps and also pushing out the thresholds of the pit shell. But I think more exciting to those drill numbers is something that we've just put out as we speak. Near 102 meters of 5.8 grams gold equivalent. And that begins under foot from surface. So this is another infill type number, but it fills in the gap where we lacked information. And what it's doing is providing more data to increase the current resource and perhaps even increase the grade. These are stellar numbers. There's very few companies that have 100 meters of over 5 grams from surface. 5 gram material is underground, mineable material, but this is in an open pit. So it will provide some big benefits in the economics. Jim, can you talk about today's press release regarding the company's best drill hole? I would say this drill hole is probably in our top five, if not number one. But near 102 meters of 5.8 grams starting from surface is something to be proud of and will have a big impact not only on the share price I think over this next week, but certainly will have an impact on the updated mineral resource estimate that's expected probably early March. Fantastic. If benchmark metals were to compare itself to its competitors in the mining sector, what would you say sets you guys apart? We're in a tier one jurisdiction. Canada is a politically risk-free, safe jurisdiction. You can build a mine in Canada, you can get it into production and you don't need worries of losing your license. We're road accessible, you can actually drive vehicles straight to our site. And in December of last year, so just over, let's say roughly two months ago, the company completed a brokered financing for $40 million. So there's $45 million in cash sitting in our treasury and that will pay for all of 2022's work. We do not need to go back to the market to raise more capital. So we're in an enviable position with a very good gold and silver product. Absolutely love hearing that you have cash in the bank. That's extremely important. Can you go through the capital structure of benchmark metals for our viewers and how you plan on attracting more institutional investment alongside more retail investors? Sure. So there's approximately 200 million shares outstanding. We trade on the Toronto Venture Exchange. As I mentioned, there's $40 million Canadian in working capital in the treasury. We've already have investment from some major institutions. That includes the likes of Vaneck, Franklin Templeton and Merck Capital out of the US. But in December, we also inserted a major mining company. So there's a gold miner called Yamana. Yamana invested and owns 4% of the outstanding stock in benchmark. And this investment from Yamana provides a couple of things. Validation of the project, that it is certainly a world-class endeavor, but also validation to the management operating and moving this project forward. And look, having a major company invest in your company also opens the realm of possibilities of perhaps a takeover. At this point, it is an investment. But companies like Yamana Gold only invest in companies that they see value in. So there's lots of opportunities moving forward here in 2022. Jim, if there was one thing that you would want shareholders and potential shareholders that are watching this interview in this video to know about benchmark metals today, what would that be? I'd say there is an opportunity to invest now, soon, and watch share appreciation grow. We will be putting out continued drill results that will feed into an updated resource estimate. And that will be followed by a preliminary economic assessment. And this PEA will show the economics and the engineering to build a mine. This is all within a three to six month timeframe. So there's a lot of big milestones and news events here to move the value in this company. We love to hear about those catalysts that can make the stock move. What is the best way for investors to get in touch with the company if they have any questions about benchmark metals? So I would go directly to our website, www.benchmarkmedals.com. There's access to my email address and a direct phone line to me and also the colleagues that I work with closely here at Benchmark. We communicate often, we do respond to emails and we do respond to phone calls. So we welcome any interest. Super excited to do this interview today with the president of benchmark metals, Jim Gregg. I must remind everyone that Rich TV Live is strictly for information and education purposes. Please do your due diligence, do your research before you invest in anything we talk about or discuss here on Rich TV Live. In saying that, we believe that this is a company that is grossly undervalued, underappreciated and underexposed. Put BNCH on your radar in Canada, BNCHF in America, put it on your watch list. And thank you for joining us today, the president, Jim Gregg of Benchmark Metals. Thank you for joining us today, Jim. Rich, a pleasure. Thank you. Always a pleasure. Love to invite you back on the show if you ever have any big breaking news or anything you want to discuss. We love to invite you back onto our show so that we can break that news to our community. And for those of you guys that are watching, if you're not winning, you're probably not watching because we bring you the winners and we bring them to you first. If you liked the video, smash the like button, comment down below, share the video everywhere and subscribe. This is Rich from Rich TV Live with the president of Benchmark Metals. Jim Gregg saying, have a nice day everybody. We'll see you soon.


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