Okay, we're back, this is Dave Vellante with Jeff Kelley. We're here at the MongoDB Days Conference at the Marriott Marquis in New York City. We have been going all day. Miles Ward is here. He is a tech athlete, we like to say in theCUBE. We love the sports analogy. He's Miles of Solutions Architect with AWS and great conversation off camera and welcome to theCUBE, excited to have one on. Thanks, I appreciate you being here. Yeah, so, well, let's start with why you're here at the MongoDB Day. Sure, Amazon Web Services listens to customers.  You guys really believe that, you know? You know, Bezos says it, Andy Jassy says it, and when we talk to you guys, you always try to really emphasize that piece of it, but so anyway. I mean, I can tell you, I sat in NASA facilities at JPL Pasadena while we powered the live streaming of the landing of the Mars rover. And if helping that kind of company take data from Mars and store it in S3, that's the line. It goes from there to there. That's not changing the world, I don't know why. If you didn't watch the re-invent keynotes, go back and check it out. Go just Google re-invent keynotes and you'll see that Mars rover keynote was fantastic. These guys were pumped up. You know, the big celebration was awesome. That's the thing about Amazon. You guys got the deepest customers. You got the proved points. But anyway, so you started to tell us why you're here at the Mongo event. So we, in this sort of ecosystem of change, we're watching a whole new set of technology tools that break the standards, that have altered the baseline of what you can squeeze from a performance standpoint out of hardware. And MongoDB, as a really, we think the kind of leader in the NoSQL open source space is doing things that other technologies are not able to do and making it so that businesses can entertain use cases that were just impossible. So what kinds of things can Mongo do that maybe some of the others don't excel at or are struggling to do? Sure, as a document store, that's different than say a key value store or a graph database or more of a MapReduce system like Hadoop. Document stores speak the same language as applications. They interact using exactly the same data structures that your software and frankly that your websites use. So as a developer that has to learn, I think the new soup de jure is the full stack. You've got to be great all the way across from the front end of the back end, being able to interact with a data storage system that speaks to application developers that's actually storing data the way applications use data is a game changer. So we've heard the term polymorphic a few times today and shout out to David Scott who's the former CEO of 3PAR, a company that got acquired by HP. He coined the term polymorphic storage and everybody laughed at him. He said it's going to stick and interestingly enough we've been hearing it more and more today. Okay, so let's talk a little about your role at Amazon. I mean, Amazon has just been exploding. We've been tracking it. You guys started the cloud. You're bringing the cloud now to more and more places, really driving hard after the enterprise customers we notice obviously, but talk about your role at AWS. Sure, Amazon, I think it's important to recognize we built this series of products that add value from my mom's blog of pictures of her goats that costs one penny every nine months because that's when the S3 charges round up to a penny to shell oil biggest, you know, giant, giant business deploying millions of dollars infrastructure, right? We add value and differentiated benefit for businesses all across that continuum. So my role as a solutions architect is trying to figure out how our tools work at that broad continuum. I go work with startups. I work with our partners. I work with very, very technical businesses to businesses that don't want to be very technical all trying to get them to learn the best practices for extracting value from the cloud.  I actually wrote a piece early this year called the Amazon gorilla attacks the enterprise and somebody pointed out to me, you know, they're the gorilla, they're the large incumbent but for the first time ever in the history of the industry, they're also the disruptor, the cheetah. So that's interesting. We've never, I could, I try to think of another example and I couldn't in this business. How are enterprise customer requirements different and how is that, you know causing you to change your architecture and the way that you guys respond? Sure, it's a great question. We have, you know we hear from enterprises on the one hand that they want to earn all of the same value that those little startups have earned. They want business agility. They want lower time to market. They want lower operational cost. They want no capital cost. They all operate in the same kind of constrained business environment that, you know, mom and pop shops or garage startups or what have you are operating it. So part of it is about learning from these nimbler younger, smaller businesses and making sure that they can get the same values that they did. Another part of it we're learning from enterprises is that, you know I think Amazon.com is a massive business. We've learned a lot from it in trying to make sure that we met its needs.  And so we're continuing to invest, you know in frankly that part of the market that has the biggest needs we think for disruption, right? I think Redshift as one system for, you know, scale out MPP data analysis, you know, that fits a different market niche than say your MongoDB does, but, you know a kind of product that's really, you know a love letter to your average enterprise and incredible cost savings for that workload. So from the enterprise standpoint I've always said we are not always but recently I've been saying we're sort of entering a new phase. You guys started it all in 2006 and it was like, hmm that's interesting. And then when the economy went south a lot of people said we got to get the variable expenses as fast as possible. It's like, here take my problem. And then when the economy starts up ticking again you start to see lines of business spend. So you had this so-called shadow IT phenomenon emerge. And a lot of CIOs were saying now Amazon not on my watch. And then yet, we don't use any AWS, we don't use any public cloud and you go, yeah you do, I was just down talking to you know the marketing department and they're all over this thing. Really? And so that sort of woke I think IT up and now what we're seeing is I think in many instances the CIO saying okay here's another arrow in the quiver. We're going to try to embrace this thing as opposed to fight it like we did distributed computing because we all know how that ended. So I wonder, do you sort of agree with that? Sort of those phases, those scenarios and what are you seeing in the marketplace in terms of adoption? Two different things. So one, if you look at those sort of different you know kind of phases beneath that is this undercurrent of change in the status quo of what it means to be successful in IT, right? The inside of those years is the kind of birth of this idea of DevOps, of businesses that have decided that the infrastructure needs to be so nimble that it is now its own kind of software product that you'll be building automation that builds your business. So that infrastructure is code. Yeah, yeah, yeah, my data center lives in my source control, right? And so the bring your own data center movement where now marketing and these other departments can build on their own because they have developers on their own which developers is all it takes to get to a place where you have a massive amazing data center when you're using the cloud. That transition I think has changed the status quo enough that enterprises are in our experience moving from cloud. Interesting, that'll be a six month proof of concept. Maybe we'll examine it for a couple of our workloads. We've closed data center 17, 19, and 22. We have 90 days to evacuate. Let us know how you move everything. That's the kind of stuff that as a solutions architect I go in and say, all right, let's try to figure out how we make that work. So that talks to just much deeper business integration as opposed to my problem for less. Yes, yeah, once you're approaching, once you realize that the problem that the business has is not its ability to spend the costs of the infrastructure that it delivers, but its ability to move work through the pipeline more quickly. It's ability to execute against business goals more nimbly. When that's the inhibitor to growth, then you start to invest in any way that you can in things that give you more flexibility. And AWS gives great flexibility. You talk about DevOps, you guys early on in terms of DevOps adoption, the whole hyperscale movement, you think of Amazon as, again, an earlier adopter. And over time those concepts are seeping into the enterprise. Open source is another one. I wonder if you could talk about Amazon and open source a little bit. I mean, MongoDB, open source, you guys host a lot of open source products. What's your role in the open source community? So it's interesting. Mongo is a successful open source product, I think is another great example of places where businesses that earn value from the open source ecosystem, that's a part of the way that that code of culture or culture of code work. One of the great examples of that is the S3N extensions for Hadoop. That's kind of a weird technical thing to say, but we've made it so that all MapReduce users everywhere can interact with S3 storage systems and other storage systems that expose the S3 API to interact with storage remotely at an efficiency that is totally impossible given the normal bring the code to the data sort of MapReduce model. So that process where we're taking tools that everybody finds useful and figuring out how to extend, maybe to make them scale better, maybe to make them more cloud ready, maybe to make them easier for folks to use. Another good example is Bodo is an open source Python SDK for AWS. The Bodo system does an amazing job of making it so that a smaller number of developers can manage a bigger amount of AWS because it's such a straightforward CLI. So that's another open source project where we're working together with folks from Eucalyptus, folks from other sort of teams that are working in the cloud environment to collaboratively build great software. So talk about elastic MapReduce, Redshift, I know Glacier is another one.  These are some of the fastest growing services in the history of Amazon. And you guys are, he talks about the flywheel, the flywheel effect, the idea being that you've got this sort of self fulfilling motivation or prophecy where the more function you add, the faster, the more ecosystem partners you get, the more customers you get, you can spin that flywheel faster and innovation comes out faster. Mike, I want you to talk about from an architect's perspective, how do you architect a platform that doesn't break under the weight of all that function and all that speed? How much further into the future can you take this? And how do you do that? Sure, well, it's one of the most basic sort of amazing things, you know, when the data center is something that you manage with screwdrivers and ethernet cables, the maximum scaling point gets to a place where so many people have to be trained to do the right thing at the right time, that it becomes kind of a personal management issue. You have to really build a functioning mechanical business as much as an intelligence business. With AWS, when you've built a system on top of a programmatic infrastructure, that code, it's durable. And that sort of durability of innovation is this incredible boon where, you know, if Bill leaves the company but he leaves his code behind, Bill's innovation stays. And so we're also watching a lot of a creative development where people are taking, you know, for example, I've built a great Amazon machine image that runs a more efficient version of Hadoop. And then I build a cluster of Hadoop using cloud formation and then I script sets of clusters using Bodo to ensure that I can deploy what I want. And I package all of that as a Bodo library and use Bodo to call sets of libraries, right? Or that you do that with Chef or you do it with Huppert or these other kinds of systems. As people build these packages that work, they open source those. We're starting to see open source data centers because the only definition of the data center is that control software that manages it. So we're starting to see businesses that are saying, it's not just enough to open source the software package that runs on one computer. I want to open source the design of my whole data center. Let's talk a little bit about Obama for America. You're very much involved in that project. As an architect, Obama for America raised a lot of dough for not a huge investment, relatively speaking. Take us through sort of what your role was there and tell us a little bit about that. Sure, we started about a year before the campaign, met with the CTO and the technical leaders and decided to volunteer for the remainder of the campaign and serve the same kind of role as a solutions architect, help them design storage infrastructure, high performance web infrastructure, their application deployment process, their dev and test and staging methodologies, a lot of their high-scale data analysis tools, those systems got used to build 200 distinct applications, served millions and millions of concurrent users on election day, had 100% uptime on election day. It did what it was supposed to do. It was pretty amazing. And from the business value standpoint, the ROI equation, it was put in a million on one end and a billion comes up. Yeah, and the fundraising component is important, but if you look at how much those software tools were used to coordinate the volunteers, to coordinate legal representation for disenfranchised voters, to do all of the work around canvassing and call voting, the real measure is very binary. Like you either win or you don't win, right? They put it in a million, I'll come get the president. Yeah, that's a different thing. So can we dig into how Mongo, so Mongo on AWS, what are the real, help us understand the, compare that to, deploying Mongo in your own data center. What do you offer that makes that a more compelling offering in your opinion? Sure, so I'm the author of the MongoDB on EC2 white paper. So you're the man to ask. I wrote the best practices for this. But it's really convenient, even though that's a 25 page paper that you and I could read and we can sit in front of your computer and you can deploy a great cluster, it'll take you about a half an hour. And we've reduced that to software, right? So there's no reason that once we've described what the best practice is, that we can't capture that as code. So we use a system from AWS called CloudFormation. CloudFormation allows you to deploy as a single atomic command the entire infrastructure that you want.   So that's a pretty compelling case. That's pretty easy. You press the button and then there you have it. And if you need it to be 10 times as big, you put a zero at the end and you hit enter. And then you've built a 10 times as big cluster. So what are you seeing customers really doing with Mongo on AWS? What are some of the killer use cases you're seeing? Sure, again, if you look at a document store as different than these other kind of no SQL strategies as different from sort of relational database strategy, one of the big things, just sort of right off the top is data use cases that are just too big or too fast for your average relational database system, right? You need inserts under a certain number of milliseconds. You need to be able to do millions of those inserts. That becomes multimillion dollar problems in a relational database environment. It becomes multi-thousand dollar problems in a no SQL kind of environment. So part of this is just about picking tools that are cost efficient. Another dynamic of that is we're seeing a lot of businesses as they build more and more sophisticated geospatial applications. They're very rich geospatial systems inside of Mongo, rich data types for that that differentiates them from other no SQL systems. And also a lot of very interesting work in these sort of end to end deployments across the software stack where you're writing what the applications need to read directly to the database. So let's take it kind of a step back for a little bit broader picture. So we were at, I don't know if Dave mentioned earlier, we were at the GE event earlier this week. I announced their kind of industrial internet platform that they're building with Pivotal. I was on a panel with AWS among others, but AWS, a partner of GE in that effort. So the idea of all these industrial grid equipment are just creating more and more data and it's being outfitted with sensor technology, et cetera. So clearly data volumes are going to continue to grow both from more of the commercial internet, if you will, social media and other things, but also now the industrial internet we're seeing a lot of data growth. How is that impacting or how does AWS approach that on a high level? I mean, is that kind of what's your strategy to deal with that growing data volumes and not just the growing data volumes but especially in industrial internet situations where the goal really is to orchestrate processes through analytics across a large ecosystem. How are you, how are you going to support that? So a couple different parts to the answer to that.   We built a cloud, it's pretty powerful. We have the big one. So that seems like a natural spot for us to play in that role. We built a system that's distributed globally today. So no matter where in the globe you're deploying these kinds of industrial systems or sensor based systems, we have systems that are close enough that they can deliver the kind of analytical value that we want. We've also invested quite a lot in, we think some of the most efficient to use, some of the highest scale, big data analysis and storage systems, right? So some of the big work goes into kind of extracting value as the data comes in. Some of the work goes into archival for later retrieval and offline analysis. So we've built things like DynamoDB that can catch the data in two milliseconds and process away at it all the way over to Glacier where we can store it for a penny a gigabyte a month and at the same durability of S3. So you have all of this rich ecosystem of choices depending on the skills of your developers, the specific needs of the data set that you bring in, whether it's tiny little bits or video or what have you and a whole range of tools to address that. And that's the video and that kind of video related content and image content, that's going to really, I mean, that's a huge source of massive data that's really just going to continue to grow. When Netflix peaks in the late afternoon, they're a third of the internet in the United States. Wow. So that's not small. And we don't think Netflix is anywhere near the last or the biggest or the most voluminous users of computer storage or database or network infrastructure. They're a great example because they've been a partner with us for a long time. But I think you're going to see businesses like GE and like Shell and these others do things, many orders of magnitude bigger than we do. When you project out where we're going to be even five years from now, it's just mind-boggling. We were at Riley Velocity earlier this week and one of the things that developers, I mean, everybody's talking about mobile obviously, it's like mobile, mobile, mobile, mobile. One of the comments was two years from now, I've always been talking about mobile. Everything's going to be mobile. But the challenge that people brought up was it's like two steps forward, one step back. We go into developing mobile apps and all of a sudden things get slower, they get more complicated. So I wonder if you could talk about that a little bit, what you're seeing in your customer base, how you're dealing with some of those performance issues generally and maybe even specifically with Mongo. I know you're doing some stuff with SSD and performance tuning, maybe talk about that a little bit. I mean, this device has roughly six times the compute performance as was required to land the space shuttle, right? I mean, we've gone a long way, they're a lot better. And the downside of that is that expectations have gone crazy, right? I want to have a map of the entire planet at incredible fidelity. I want to have all the music I've ever heard. I want to store every picture and show them to my buddies, right? So those super high-scale data uses in some ways more data than you even want to get to with your laptop because it is so useful in situ. It has to come from somewhere centralized. And many of the application developers that we talked to, you know, they're good at building captivating interfaces, they're good at building user experiences, but they need a lot of support around making sure that that little cloud that goes in the middle of the drawing with all the zillions of phones, that it scales, that it grows, that it does all the things that it's supposed to do, when it's supposed to do them at a price that makes sense for their business. So, one of the biggest things we've seen that's interesting in the sort of mobile spaces, mobile performance, right? It's not just enough to have the big cloud in the middle. We built this system called CloudFront that shoves to the edge of our networks closer to the cell carriers, closer to the individual mobile devices. The video and picture and audio content that's so popular on them so that when you do things like streaming audio or streaming video or this kind of streaming webcast, that's the sort of thing that CloudFront could accelerate for mobile users. Frankly, the push of another button, right? You just sort of turn that feature on. It's not that tough. All right, Miles, well, listen, thanks very much for coming by theCUBE. As we say in Boston, you're wicked smart. We'd love to have you on here, and we hope they have you back sometime. Maybe see you re-invent and... Perfect, looking forward to it. We're really excited about it. Thank you for taking the time. You're welcome. Keep it right there, buddy. We'll be right back. Jeff, Kelly, and I, this is theCUBE. We're at the MongoDB event. We're live at the Marriott Marquis. We'll be right back.


Okay, welcome to the Bookmap Platform Details webinar. This is Bruce at Bookmap. A risk disclaimer, trading equities in futures involves substantial risk of loss. It's not suitable for all investors. Past performance is not indicative of future results. For more information, go to bookmap.com. You can get a free trial there for 14 days and that will allow you access to the advanced order flow analysis webinars and other resources as well. We'll cover that in about half an hour, the advanced order flow, and then reach out to us at support at Bookmap with any comments, questions, or issues, et cetera. Let me quickly show you where you can find Bookmap if you wanna give it a try at bookmap.com. Here is the basic and the advanced versions. They're the 14 day trial for each. The difference between the two here, the ability to trade from the chart and these proprietary indicators that we have for order flow. Okay, you can follow us here on Twitter and you can also subscribe to our YouTube page, all sorts of videos here, features and components, order flow video snippets that go through phenomena that we usually cover in detail, a lot of detail during the advanced analysis. So this is how to use Bookmap, what Bookmap is showing and uncovering for you. We just finished up the ProTrader webinar series, you can watch these here from recordings from last week. And if you want to take a look at some of the selected webinars here from the advanced order flow analysis, you can watch them here. There's also the platform details here that you are attending right now. Okay, so I just wanted to go through that because, quickly because here we have the fundamental release in crude oil, okay? We have the oil inventories, all right? And why I want to cover this, okay? Is because look how the liquidity, right? At this area here, okay, before 1030, okay, the release is at 1030. And look how the, a lot of the liquidity dries up here, okay, right before. So, you know, three minutes or four minutes beforehand, you can see that a lot of traders start to pull their liquidity. They don't want to take risk in this market because they don't know what the news is. And where does the market go? Well, when there's not liquidity, it's a lot more volatile.  Okay, we see these wippy price action movements here. And where is it going? Well, it's pretty obvious. It's going to where there is liquidity. Right here at 5185, you can see it came down and tested this area here of liquidity. There's more liquidity down here at 5180, as we can see here. Now look at these guys come in here at now 52. Okay, the figure at 52. All right, now they're starting to pull as well. Okay, the initial move up here, well, this was before the release, but then the release, there's liquidity up here. These guys pulled. It's kind of curious to see that it didn't come up there and it really just failed and then went to the downside. So I imagine the news here is bearish. Let's see what the news actually is. I don't have that information right in front of me. Let's see here, what were the inventories? Okay, so it's, yeah, it is bearish. We have a negative 1.8 million barrels where expected or forecasted was 2.9, right? So that's probably why we saw the double top here and then the sell off. But we're right back up there now as well and just testing above the figure here at 52. So it's still really just bashing around here and trying to find some direction at the moment. If all of this is confusing, well, that's no problem. We're gonna go through in detail here what book map is showing you and then how to read it. And then we can come back and revisit this economic release and see what kind of flushed out after the, we start to see it settle down here, okay? And what kind of direction the market might take. Okay, so let's start here with just the basics. And we do this every day, but we start with a candlestick chart because most traders are very familiar with this and we wanna take off all the other layers here of data, okay, and let's zoom out, okay? So we are looking at a, are we looking at a five minute chart? Two, three, four, let's see, I believe this is five minute chart, hold on just a minute, yeah, five. Okay, all right, here's our five minute candlestick chart. Now most of us are very familiar looking at a candlestick chart, okay? So we understand this open, high, low, close of a five minute period or whatever period you're looking at. And we can start to read some of the buying pressure and selling pressure here in the market. For example, we can see some sideways consolidation here before the figure at 52. And then we see the breakout here at the crude open just after nine o'clock, okay? And pretty strong move to the upside and we get a retest to where we broke from here. Now we're gonna cover all of this in the order flow and the liquidity. And then we see we accepted above this area here. So a pretty important area that price in the auction is accepting above here. But we want a lot more transparency into all of this data here. And we're not getting it with this candlestick chart. It's a problem, it's lacking transparency. We don't have any understanding of the volume here. We have a volume sub chart, but we don't know where the traders, what kind of traders they are, what type, aggressive buying or selling. We don't know where in that five minute period. That's very significant. And then we also want to understand how much exactly where. And then we also want to look at some of the micro structures in within this five minute period. All of that is lacking here. So first level of data we're gonna put on here is historical best bid and offer, okay? And this allows us to see some of the micro structures. So let me click on the hand tool or the move tool. We're gonna zoom into this area here. So here's what really occurred within these five minute periods. We can see that the consolidation here back and forth, initial move to the downside, probably a little bit of a liquidity grab down in this area here. And then we can see that the very quickly price moved to the upside, okay? And real nice breakout here to the upside. We see some micro structural areas start to emerge here, but really up in here, this pretty good range, okay? And you can see that price is accepting above in this area here. That is lacking in the candlestick chart. We really can't see that in the candlestick chart. We don't understand the commitment of the traders here with their aggressive volume either, okay? So that's the next level that we're gonna add to the chart here is the aggressive volume, okay? So let's zoom into this little area here where we saw that micro structural pause, okay? And we can see the initiated buying that took place here. We see a little bit of a pause as we went sideways and then initiated buyers came in, stepped it up and we moved up out of that area, okay? So we'll just focus on this little area right here. What we're looking at here on historical best bid and offer is the aggressor, okay? If it's a green dot, it is an aggressive market buy order. They hit the market buy button. They crossed the spread, they took liquidity off of the best offer and a transaction occurred, okay? They met with the limit orders on the other side and then we can use this rollover tool to see exactly what occurred here, okay? So we have the date, the exact time down to millisecond in this case and then we have the liquidity here on the ask, it's 188 contracts at 5209 and then the volume, okay? This was a four volume of one, okay? We can move over here and we can see that there's more volume of one. I can hover over this dot here and I can see that it's bigger and it's a red dot and it's taking liquidity from the best offer, our best bid, I'm sorry. So this is an aggressive market sell and it's for quite a bit more. It's for a volume of 43, okay? So that's what we're displaying here with the aggressor and where it takes place. Now we can continue to zoom into this area here and I'm just gonna do that and we're gonna start to break apart all of this trading activity and we can see exactly what occurred here, okay? So now we're down at microsecond level. We can continue to zoom into nanosecond level as well, okay? And see every single trade, okay? Bookmap, it's complex event processor can handle all of these data points, okay? So we can really understand exactly what occurred in these markets. Now most of us, we're not trading at these levels, these very low frequency levels. So what we've done in the user interface here is I zoom back out, we consolidate just visually and aggregate this just visually into a bigger dot. So we have the overall understanding of what took place here very, very quickly. Now as I continue to zoom out, note how I compress the timeline here and then we start to see so many events that took place that we give you the volume in the overall delta here. So for example, if I hover over this big dot here, you can see that is for a volume of 503 contracts and the majority of it is aggressive buying, okay? Because the pie display is showing us that, okay? It's more than 50%, all right? So we have a good understanding of exactly what took place, how much and where. And if you want more details, we'll just zoom in, okay? And you'll start to split apart all of that trading activity you can understand exactly what occurred, okay? All right, so that is what is lacking in that candlestick chart and that is where Bookmap is giving you insight to a lot of that activity that can really lead to much better trading decisions. And why do I say that? Well, because here, for example, initiated buying comes into the market here. This is where it started right here, okay? At this level of 5204, okay? We get a pullback here and we get another pullback, one tick below actually at 5203 and the buyers step in again. This is giving us insight. Buyers are supporting price up above this level, okay? We understand where the buyers are, okay? That is completely lacking in this candlestick chart, okay? And we can see we bounced along sideways here and the buyers still stepped in, okay? So this is that little microstructural area and understanding of the market mechanics that took place there gives us this insight to this area, okay? There's half of the picture here though, understanding in just the traded volume in Bookmap is basically just half the picture because we can understand where traders are lined up to or where they're committed with their trading, okay? With the dots, we know that. But we don't understand what about the auction? Where are they lined up to bid and offer? And that is an important part of order flow, okay? So, and the order book. So that's where we'll go to the order book and most of us will consume this kind of data by looking at the dome, okay? This is the current market here now in Crude, just bashing around back and forth. And here's our dome, the COB column, current order book. Okay, so that's the dome in Bookmap. And you can see here the depth of market on the offer here and on the bid here. These are traders lined up to trade at these levels. They're providing liquidity. They want to deal at these price levels and they're providing liquidity with limit orders, okay? This is where they want to be a buyer. So we can see very quickly the current order book and we understand, okay, at 52 I see there's 136 contracts. Down at 5180, there's 193 contracts. This is good. I like the dome. I think for most of us, it gives us a really good picture of the current market. The problem with the dome is that these numbers change all the time, okay? Liquidity is added and pulled. And we're getting insight here just before 5181. And we're starting to see more liquidity come in to the market into this area here. So buyers are starting to get a little more aggressive, okay? But what if they pull? How long were they there? You have to memorize all this. What was the behavior like in this area? That is difficult because this data is fleeting. Once it refreshes, you'd have to recall what that data looked like, okay? And that's where book map gives you the historical limit order book and it'll solve that issue for you. So let's turn on the limit order book historical view with the heat map, okay? So what the heat map is showing you, let me zoom in here, is we take the data here in the dome and then we'll paint it in the heat map, okay? So let's make this area a little bit brighter for the moment just so we have a better example here. So areas of high liquidity are painted bright white. If it's a lighter or a little darker shade, there's less liquidity, okay? So, and you'll see this in this, this is the current market window, is this is your visual dome here. And we have our best bid and offer here with the dashed lines. This number is the last traded volume. And you'll see the heat map is changing all the time, okay? It's reflected by the numeric values that are changing here in the dome, okay? So we gain insight to where the majority of these traders are lined up to provide liquidity. Where this gets really interesting is we take this data and then we transpose it onto the chart historically, okay? So now we can start to understand the intent of these traders at these levels. We can see where they're providing liquidity, how long, what the areas around it look like, where traders starting to front run that high liquidity, do they really wanna get into the market, or did they pull as price came down toward them? Like for example, look at this little move to the downside here and these guys pulled their liquidity. So did they wanna trade here at 51.90? No, they did not, okay? If they wanted to trade, they're gonna stay in that limit order book. So these 150 contracts here right now, let's see if we get a retest right now. And we'll see if they're, I'm assuming that they're probably gonna pull because they pulled once before, right? But okay, we just came down and we see a little bit of that activity here. Okay, let me bring up the cutoff here. Okay, you can see they started to pull some, but actually it's looking a little more bullish now. They're starting to add in even a little bit higher, okay? It's a little different than it was over here. So now I have insight to that intent of these traders here. Now they're actually looking like they wanna trade, okay? Look at these guys up here at 52, 350 contracts, okay, at the figure, okay? Looks like they want to absorb as much as they can, all right? And they're staying in the book. So far, we're one tick away or a couple ticks now, but they're staying in the book. This is giving us insight as well. Now it doesn't mean that just because we see all of this liquidity, doesn't mean that it's gonna stop the market and we're gonna reverse down. It just means we've identified where the sellers are, the majority of them. The aggressive buyers can take them on and they can trade through these guys, okay? And we're gonna witness some of this right now. Here, their intent to trade is obvious. It's confirmed. We see they're trading into 52 and they're staying here in the book, okay? All right, so their intent to trade. This is not fake liquidity. We've just made that distinction, all right? So for those of you who always hear about the limit order book, you can never tell if it's fake, if it's real. Well, here's an example. This is real, all right? At this time, it was real, okay? If we come back up and retest in these guys' poll, well, maybe it's not, okay? But at this time, what we do know is this is real liquidity, all right? And we also have an add-on here called the large lot tracker, which is showing me. It's actually, add-ons are showing a few different things here. We have the iceberg that went off up in this area here and we also have large trader. This little white line here is showing me that the majority of this, about probably around 300 contracts here is one individual actor, okay? We have an algo that can determine that by the way that these contracts hit the book, okay? So let's just turn on the indicators for just a second here because here's our 178 contracts here that was a iceberg order. And then we see nothing here actually in terms of icebergs, okay? So these guys got their fill and they're content. All right, so that's the historical limit order book and how to start to read it now, okay? And we can gain a lot of insight by understanding these traders, just like we're doing here at 52, okay? We understand that these guys want to trade, okay? And we also know that the news is bearish, okay? So maybe they're just trying to get on as much as they can here at the figure and it doesn't mean that it can't trade through but we can start to gauge their intent and that is the insight that we're looking for, all right? Okay, so let me take off the candlesticks for a moment and I want to zoom out here and I want to take a look at the bigger picture after this fundamental release, okay? What has kind of shaken out of this inventory release here? Well, actually pretty interesting stuff. In fact, let me turn the candlestick back on for a moment because this range here and this breakout from here, well, we can see, like, you know, pretty wicked action because coming down to the low here, hitting any of the stops, looking, the markets looking for liquidity, it's gonna find the, any of those aggressive buyers, you know, they're gonna be probably stopped out in this area, we go to the back to the other side and bash the other side of the range up here, the recent high at 930 and then it's right back down into the range, okay? So this information here that we looked at earlier, you can see how this volatility here basically knocked a lot of those guys out. Anyone who put their stops in these areas here, okay? Searching for liquidity and looking for those stops as well, okay? All right, so let's turn that off now and let's get an understanding of the shake out here, okay? So now it looks to me like we're seeing some decisiveness, those guys at 52, they stayed in the book and we can see now the market is taking a direction here, okay? All right, well, let's see now, this is a phenomena that we cover in the advanced analysis all the time. Look at the, look at how they're hitting the bid really hard here, okay? The aggressor has come in, the sellers have control here, there's no question about it, okay? Looking for pullbacks now, probably the first pullback, I'm gonna look at this 5180 here and I wanna see if the sellers get aggressive with their limit orders. The other than that, I'm looking up here where we broke from, okay? And if they're gonna provide liquidity again, the sellers and they are, they've already jumped into the book here and you can see 189 contracts up here at 5190, okay? So they're supporting this move and this breakdown to the downside, okay? We don't get our pullback yet. In fact, they just continue to hammer the bid here. Let's see levels to look at. All the way down here, 5160, 5155. Here's our half figure at 5150, so it looks like they're trying to absorb before that and let's just watch this play out here. It looks pretty good to, I don't see aggressive.  So maybe we'll get our pullback right now, okay? Yeah, here they come, okay? Broke a little structure here and maybe we'll get a pullback up into this area here, our 5180 area that we're looking for initially here, okay? 5190, those guys are still up here and we'll see if we get our pullback or not. Okay, first stop, yeah, right around this area here, 7880, something like that. Okay, here comes 80, so you just notice how the liquidity is starting to get a little bit brighter up in this area here, okay? Maybe I need to adjust my heat map a bit. Might be good. Yeah, that looks a little bit better, okay? All right, so here's 76 liquidity and it looks around that 80 area, they're adding and pulling here, so they're not a little bit shy up here at 80. Okay, here come the aggressive sellers and let's see if we see them really lower that offer in some of these areas here, okay? Coming up, all right, here we go to 80, okay? That's our first area, right? Okay, so that area has been hit, okay? 5190, looks like they want to come up and test 90, okay, and now these guys pull at 90, and they're supporting price now at interesting area, right? Understanding the order flow, understanding that this 5180 was important. Now they're providing the liquidity on the bid at 79, okay, just one take away from 80 here, okay? So maybe we'll see a move back up into 52 now, that's possible, okay, and they're supporting price at 85 as well. Okay, 52 looks, well, now let's see, now we're back here now to that initial question of this is where it broke from, are sellers gonna jump back in here around this 5190, okay? We saw them provide the liquidity, but then they pulled, okay? So we'll see if we get a little follow through. The sellers are back in though, as you can see, okay? Now let's see if these guys at 79 will pull, and maybe we'll get real nice move here to the downside. Nope, sellers starting to dry up here, okay? So anyway, you can see what we go through in the process for the advanced analysis webinar. We started to note buyers coming in down at this area here, we noted the structure starting to get broken, we noticed them lifting the offer and we started to place our targets, looking at 5180 or 81 being the first area and then 90 being the second area, that's exactly where we've come back up to, and now they've kind of flipped their supporting price here at 79, okay? So anyway, that's what Bookmap is showing you, and you guys have any questions, you can always reach out to us at support at bookmap.com, happy to help you. If you wanna give Bookmap a try, go ahead and you get 14 days free trial, and that'll also give you that access into that live order flow analysis in the webinar that starts at 11 Eastern, okay? All right, guys, yeah, thanks for coming, and we'll catch up with you tomorrow, bye-bye.


Pat Wells brings her dog to visit people living at the Armed Forces Retirement Home in Washington, D.C. After 9-11, I wanted to do something to give back. At first, she went alone. Then she learned about the healing effect that animals have on people. So she started bringing her dog, Rika. We saw one lady that hadn't come out of her room for two weeks because she had had a stroke. But when we walked into her room, she stood up, she talked to us. They said she hadn't been so happy in weeks. We visited with people that were getting amputations next morning and were scared, but they smiled when we walked in their room. And I mean, sometimes it's staff that's had a stressful time. We used to have a doctor that would stop everything he was doing and sit down on the floor and talk to each dog when we went to his floor. Volunteers and their dogs visit the retirement home three times a month. I like all dogs. They're a good friend. Recreational therapist Stephen Briefs says the dogs help the people he cares for. Certainly the ones with arthritis that have lost the real function of their hands, it gives them a chance even then to pet as best they can to hold and to share with the owner of them. It definitely helps with hypertension, less anxiety, more socialization for the residents, some of them anyway, more feeling a sense of companionship, less loneliness that gets them out of their room and coming down to the recreation center here. And all those things work together to brighten their day just at least for the one day. Volunteers like Tracy Bites say the visits also help their dogs. He loves being petted and he loves being around people and it calms him down. It just makes me so proud to be able to share that aspect of his personality and to be able to witness the effect that he has on others. The American Kennel Club says there are more than 100 animal therapy groups nationwide. I'm Karen Leggett.


has declared a state of emergency on infrastructure in the state and approved the demolition of all illegal structures, including doze and waterways in the state. Speaking to Newsman at the end of the state's executive council meeting on Wednesday, the Commission of Works and Housing, TISA, Emojime said the council also frowned at the collapse of a church building in the state capital and the attendant death of a pastor in the tragedy. We talked about the collapse building, how for? That's the name of the church somewhere in North Island. The day before yesterday, I went there physically for assessment which I wrote. He mandated three ministries, the Minister of Works and Housing, the Minister of Monetary and the Minister of Lands, and the Minister of Urban Development to look at the remote courses of the collapse which we did and the investigations are still ongoing. And in the ex-school, the ex-school concluded that every building in the state that lacks structural and interpretive tests should be taken off the way, especially buildings found on waterways.


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