Man of the hour, for 30 minutes. 30 minutes? Oh, well, an hour. So what do I do with the 25 other minutes? I almost had a bad job, about five minutes jobs. I'm going to do a quick introduction into IBM Bluemix. That's IBM's play on software's platform as a service.  Marriage as a service, software as a service, business process as a service, also called BS as a service, you know. Infrastructure as a service and platform as a service. Just to clarify the whole thing, infrastructure as a service, is your server not sitting in your basement anymore? Platform as a service is your server with the admin tied to it not sitting in your basement anymore? And IBM has entered that market very late. So we started only last year in July with the official availability. We don't have the Singapore Data Center up and running. That's coming somewhere this year. It's my job to push for it.  We currently have the platform as a service running in Texas, as well as in London. And to be scheduled up and running is Melbourne and Singapore. The big thing is, so what you see there is, that's the web UI. There's a command line as well. We do Cloud Foundry, so we decided not to reinvent the wheel, because we got the patent for the wheel anyway. IBM is old enough. And we also have containers. So we're not allowed to say Docker, but this is basically IBM's version of Docker. One of the things what we did beyond what standard Docker does is like, say, you check in your definition in a version control system and the backend builder builds your Docker image for you, including a vulnerability scan and said, you haven't patched it properly, I won't deploy it for you. And then the other thing is like, say, if you have to run a virtual machine because you want to have some of this funny operating system, like Windows or so, or BSD. So what I'm going to show you quickly, like I say, what the whole platform is about. I'm pretty empty. I just have one IoT demo, which I'm going to use later. It uses a Cloud and Database. That's a NoSQL database, also known as Apache CouchDB. And I haven't any other stuff. So when I want to create an application, this is really complicated. I say, oops. I say, create an application. And then it asks me, hey, what do you want to do? Web or mobile? I don't understand mobile, so I do web. And then he says, OK, pick your poison. So we currently have from Java, Node.js, go PHP, Python, Ruby, ASP. And that's a nice little thing is if you have a build pack, heritage of Cloud Foundry, you can deploy your build pack. My favorite build pack is the null build pack. The null build pack doesn't do anything, but it just copies the file you have. You have Linux binaries. You can use a null build pack to run it on Bluemix as well. OK, I will refuse to do PHP. Pick your language. Potentially hazardous programming, PHP, Python. So I said, I want to do Python. And then he says, a Python application gets you up and running, quickly and blah, blah, blah. There is one interesting thing is, down here, 375 gigabyte hours free each month. Last time I checked in the manual of physics, there is no such thing as a gigabyte hour. Patent pending IBM, we invented a new physics measurement. This is size of the runtime times hours run. And if you're really good in math, who's good in math? OK, so that's basically a 5.1.2 runtime, or two 5.6 runtimes a whole month free of charge every month. Other than our friendly competitor, the big one with the A, we don't charge any network. So there is no network transfer. There's only, like, say, runtime for the runtime, storage for the storage, and API calls for the APIs, depending what you use. OK, so we use Python. So then it asks me, how do you want to name your application? I already was a nice boy, and I preconfigured a few domains for myself.  This is why I use DragonTamer. My boys are born in the ear of the dragon, so this is why I DragonTamer. How should I call it? Come on. I need to ask you, huh? Ralph. Ralph? OK, Ralph. I paid him for that. No, they are Ernest and Anthony. So as I finish, in that very moment, a Cloud Foundry build script kicks off in the background, and if I'm very lucky, the application will actually run, which usually it does. So then it says, OK, what are the two options you have? Since it's a Python application, it doesn't offer you Eclipse, but real Python developer use what IDE? Notepad, command line, huh? Whatever. VR. VR, yeah. That's good. VR is less painful. No, it's as painful as poking yourself in the eye. If you know the colon, you know how to get a colon cool. That's all I ever learned. OK. So we have two ways. So we have the command line interface. All the CF commands are going to show that in a second. And my personal favorite, we have a full Git integration. OK, so when I look, go in the overview, and the overview now says that you have one instance of Python running, it has 128 meg of memory. Python is actually quite frugal compared to the other languages. So excellent choice. And it says, your application Ralph is now running. It tells me here the Ralph Dragon tamer. I have the activity locked. And down here, I can say, estimate the cost of the application. I come back to that in a second. And up here, it says, add the Git repository. I said, OK, add the Git repository. IBM runs as part of the Bluemix environment under the name hub.js.net, a full-fledged Git server with a few little extras. And that's the build and deploy capability. And it says, OK, you want to do Git repository. And said, oh, yeah, I love a Git repository. I click OK, continue. And bang, off it goes. And create copy C. Just before the step. Yeah. What did we have? Did we have a Django framework? Or did we just have a Python proper? Just we got to look. This is why I copied in the Git repository. We're going to have a look at the source. What it just did right now. If you have something ready-made code, you can use it as well. But before you copied from Git, did we have anything? There is. Yeah, OK. So let me just show you the running application. Ralph, Dragon, Payment, and that's the Hello World one. Let me open that up. That was a copy to Git, not from you. To Git, to Git. So that's basically the Hello World application. There's, to my best knowledge, no framework in there. We do have boilerplates with Django. OK. I covered the boilerplates in a few minutes. OK. So now I go back to my dashboard. I have now the Git URL and straight away the ability to edit code. So since I'm supposed to speak faster, this is how the repository looks like. So it should, OK, I need to reload that. Otherwise it doesn't show it up. So these are all the applications I have in there. I can then invite different people to participate. Where is it, Ralph? There you go. Yeah. And one of the things is, like I said, what we did, all I said, when you look at standard Git, it's just version control. What we added is the, does it run? Yeah. It's the one of the things track and plan that's a little bit like our little bug tracker. And then my little favorite one is build and deploy. I'm going to show you that in a second. So we used the Eclipse Orion project, which is a browser-based editor. I'm not sure who would do that in his right mind. But like I said, if you are in need somewhere and you bloody need to fix that two lines of bug, what you found, you can anyway go in there. And it will actually check out the complete repository. There's no live editing of some code involved. And then build and deploy. Let me just show you that quickly. And there you see, there's just a server pie, so there's not much in. So we have build into a build stage and a deploy stage, and you can add a test stage. Where I said, once I stuff something into a Git URL, typically in the master branch, go run the build. If the build was successful, deploy that. And then for the build, let me just go for you to the thingy, configure the stage. And it says, okay, where does my input come from? I said, okay, it comes from the repository. This is the URL where it came from. When anything goes into the branch master, please trigger the build. And then for the jobs, what you can see, okay, what are the builder types, and that's the interesting part. So we have basically the who's, who of building and Gradle, Grunt, Maven, NPM, or Shell script. And then what I mentioned earlier, the container service to build a docker container in the background. So you check in your docker definition in, let's say, this will be a docker project. You check in your docker definition in the version control, and it gets built and deployed in the background. You don't need to wait. So these are the capabilities. So whatever your fancy is there, like I say, there's always shell script if nothing fails, okay? And that makes things very, very easy. So you happily deploy it. Check it into the respective branch, and you push it out. You also can have different build stages that you said, if I check into the dev branch, please deploy to the dev space. If I check into the master branch, please deploy to the production stage. So, but the real fun is, that's our hello world. I think you believe me if I would edit the source code that it runs. Let's go back to the dashboard. A Python server that runs and does nothing is not a good Python server. So you need services or APIs, and this is where the strengths of Bluemix comes into play. So all the Cloud Foundry-based implementation, so you got OpenShift from Red Hat running on AWS. You got Herdoku from Salesforce. A few smaller ones. I always forget them. No? Hadoop. No? Hadoop. Hadoop is not Open... It's not Open... Cloud Foundry. Okay, so, I'm in my application, Ralph, and it says, what would you like? And then you have here the categories and the level of support. Is it an IBM supported one, a community one? Is it still better or is it third party? And then the first one, of course, that I'm very proud of is, like, say, the Watson, the cognitive computing. I call it the teenage computing. You ask a question, you get an ambiguous answer. I asked my boy something, have you done your homework? Daddy, what exactly do you mean homework? Something, like I said, there is when you Google Watson personality insights, what you should not do is load the personality inside, remove the sample text, and then, like I say, stand in stage in KL and paste Mr. Najib's last speech in there. It's not good. Luckily in AI, I cannot be sued for libel. Okay, so you get all these funny things. I like trade-off analytics quite nicely. This takes away the necessity to make your own head while you buy this phone or that phone. There is one hard-coded, so there is a soccer game or a romantic movie you want to go with your spouse. Do you go to the romantic movie? One of the interesting things that we were discussing about trade-off analysis that's really for single-oriented is housing HDB. One of the things that I was probably going to play around with is to create a demo on how to get all the different parameters for your HDB housing and essentially, based on your parameters, which HDB house or which condo? Estate, condo, landed housing, anything. So that's something that trade-off analytics can actually help. It goes beyond got money, need condo. Yeah. Okay, then the more interesting thing is, like I say, for mobile services, we got the push notifications, the iOS 8 had it a bit special because you have the push notifications that are actionable, so the API got different. Twilio is a third-party service that lets you send spam. No, SMS. Why do I say spam on this? And my personal one, what I like is mobile QA that allows you, that locks for you which of the APIs were called, what happened in your application. You can have, like, say, a module, you shake your phone and give a feedback straight away to the user. And little secret one, you can use it as a mini app store bypassing the whole public process. So for 50-odd users. Little DevOps. Also one of my little favorite auto-scaling. Your application is popular between 11 and 1, not before and not after. So before and after you run one instance and between 11 and 1, once the demand picks up, you start new instances and since we only bill you for running instances, you can tailor the bill towards to what actually is the consumption. That's my, so this is one of my little favorite.  They're quite popular in terms of monitoring and load. Web and application. From MQlite to SessionCast, the workflow, the scheduler, they can say some tasks, once every two hours, each third of the month, basically what you can do in a good, a cron task, you can schedule there. Then we have a lot of third-party there from Memcached, the geocoding from Pitney Vowels. I haven't checked how good they are in Asia. Send grid. For geocoding? Yeah. Nope. I was guessing that. Send grid for sending out all your SPAMs. SessionCast, that's quite a bit of a thing. When you start developing cloud-based, this is probably not relevant for you guys because you're cloud-born, but I see it's an enterprise developer. They're so used, I have this one-step big web-server. And then I use a singleton to keep track of all the sessions. But when you have multiple instances, all that doesn't work anymore. So you need to have a service that keeps your sessions alive because you never know where the user's going to hit. It's almost like Kung Fu. You never know where you get hit. Okay. So down there, integration. This is one of the things where we are pretty strong with cloud integration, CQGate, with API management. API management is my current favorite because my boss wants it to be my favorite. This is a layer between your application and your clients where you can throttle, measure, and build your API usage. Especially, let's say, our enterprise customers are very fond of that. They said, hey, hey, what is... If suddenly I have 10,000 requests per second, my backend can't handle that. I said, don't worry. We put the API management in front and said the open API can be called 10 times a second, not more. You're paying customers. They can call it 1,000 times more. And you're super special customers. They run their own hardware so you can define what they're going to do.  Which application, with which key, and all that stuff called it. You know, you code all your REST APIs to properly do application keys and all the stuff. No, you haven't. API management puts that layer on top of you and you just need to do... If it's a REST call, you're good. And then data management. Starting from SQL database, which I find very amusing. They didn't dare to call it what it is. A DB2. Then we got Cloud and NoSQL, my little favorite because, like I said, I know Damian Cuts. Damian works for Salesforce now. But she's crazy. XIBM, he wrote. Cloud... CouchDB in Erlang. Not Erlang. That's a city in Germany in Erlang. And if you write Erlang, you need to be crazy. But it runs. Okay, then we got... Mongolab, that's quite popular. Elephant SQL and ClearDB. So that's... So we basically have all the bases covered. And then big data. So for somebody who, like I said, pretends to know something about data, DashDB is pretty cool. That is a database for analytics. Works nicely with R. Or big insight, you know? If you can lift your data, it's not big data. Time series database, the artist formerly known as Informix. Insights for Twitter, that's kind of a mix because it's data storage and it links out to Twitter straight away. Then got a bit of security and business analytics and Internet of Things and custom... And this one, I built myself. I built myself. That's for one of the... That's with the API management. So I define in the API management, I define a constraint, and it surfaced back into Bluemix. Okay, but database. Let's add the database. I said, okay, I want a database. It tells me, okay, you want to be in the space development. You want to do it for the application wealth. It gets a fancy name and it tells me 20 gig is free per month and 500,000 reads and 100,000 writes more or less. After that, 1,000 calls is 3 cents, roughly, US. I said, create, bang, the whole thing creates and adds it to my project. So then the big question is, yeah, and how do I then get to that database using Python? And he said, okay, I add something you want to restage. I said, okay, restage it. And now I see here, down here, environment variables. There's a wonderful environmental environmental variable called vCAPS services. And there, you can read that. It's a JSON string. It tells you where is the host, what's the URL to get there, what's your username, what's your password. So you shouldn't flash that on screen. They're going to delete this application after the show. So it doesn't really matter. Fine. You read that into Python. How to do that? I don't know. I don't speak Python. At least I pretend I don't do. And then it's under environment variables. So you can actually get it from any Python and just environment variables. By the way, it's under if I'm not wrong, it's vCAP underscore something. If you read this thing, vCAPS services. There you go. That environment. Okay. So let's have a quick look at the cloud database. I could actually steal the URL straight away. Should I steal it? So the cloud database runs on its own infrastructure and allows me to does it? Looking up. Just the and then allows me to go and have basically JSON documents as a team fit with a nice little map reduce mechanism to get to the data. And we have an internal server error also sweet. Okay. Never mind, like I say, but you know TV kitchen. Here's the cloud and database. This is actually if you look very carefully runs a local host. So I can go and have it on my machine. It replicates sorry, synchronizes with any one of it. My little favorite feature where's my Russian friend this one runs on a Raspberry Pi as well. So we did a project where we used a bunch of sensors locally deployed sending the data to a Raspberry, stuffing it in a couch database and then synchronizing it back to the cloud. So we then can go and do all the analysis in the cloud so everybody can see that, but I don't have it. And then when you look into that like say let me just open one of them. Let me show you the including the documents. And you see it's pretty straightforward a JSON document. The funny thing is you need to have ID and REF is mandatory. That's what they use for conflict resolution when synchronizing. And then you can have it could be whatever. This one is quite interesting. This is a design. This is the underscore design. This is a map function. I said give me all documents where the document type is question there. So this is lovely. Just show you I have a view by ID and that is No? Okay. Oh, I don't have queries inside, sorry. But that's basically what's in that design. What's in that design in there. Very optional. Yeah. When do we get to the IoT stuff? We get to the IoT stuff in about 90 seconds. So rough overview. Now the interesting thing is IoT. So I was a bit lazy, so let me close this. I created an IoT already. So since my hardware didn't work because you sparkle I have one little sum. So I have an IoT sensor at 38 degrees right now virtually 36, 35 and then I have created an application as was the IoT demo. We don't need that. Where's my IoT there? To create this, I just show it. Where is it? That was the arrow. Go back to the easy one is just go to Google Mix. That's the fastest. So to create what IBM is using for the IoT cloud is we have a tool that's called Node Red. It sits on top of Node.js escaped out of IBM research. Somehow they must have made IBM legal drunk because they allowed them to publish that in Apache license. And the tool is called Node Red. So when I go to the catalog and then I have what we call the boiler plates. This is basically ready-made menus. Coke fries and a burger. And one of them is the IoT starters. They don't call it boiler plates anymore. They call it starters. They just deployed a new version last week. Yeah, I know. I suffered that. The Internet of Things Foundation starter, I click on this. It tells me what it is. And then I can go and say, yeah, credit card amounts. Hey, I work for you. I don't want that. So it says it's the SDK for Node. It's a cloud and database. And then it's here Node Red. Anybody heard about Node Red already? A little bit. Okay, no. So Node Red basically looks like this. This is wide open. I haven't closed. Well, here we are. Looks like this. I can go and have a series of elements on the left-hand side. I can drag and drop them as I need and connect them to each other. And then when you look at this you see I inject this basically just send data in there. I can connect to MQTT, HTTP, WebExpress, TCPIP, MQLite and IBM IoT. This is going to spend on this a little bit more. And then it said output from debug, HTTP response functions around a function, around a template. I have switch and change and range and what have you. I can input, output, email, Twitter, whatever, storage and all the usual suspects. I have the sentiment analysis. I have all the Watson tools in there. This one you will not find when you install your own version of Node Red. So this is specifically to Bluemix. And then just to make it more fun. For instance, this one is Node Red running on my local machine. And there I deploy it when you leave it down there. You see this is a little hardware device that talks Bluetooth. And you can say, okay, I run it on a Raspberry Pi, I stuff a Bluetooth shield on it and then I can use that to interact with this type of stuff. But okay, back to our little example. So how do you get the light blue beam extension in Node Red? You just define it as a dependency. That's it. In your package JSON file. So what dependency is it? Light blue beam, contribute whatever. It's on the light blue beam page. Let me show the sample application first. So I have D, IBM IoT. They have one mechanism, Quick Start or the proper one with using an API key. I use the Quick Start. I only need a device ID which I copy it already from the other one. Of course, to make things a little bit more complicated, we have a bug in the software which requires that the colons go and that the letters are lower case. It took me two embarrassing shows where it didn't work. B and F. Where does this device ID come from? Is it given to you by this? The device ID comes from the device sensor. It's basically a MAC address. With the MAC address. In the production environment you use an API key. You don't just use the device address. This is for demo purposes.  And then I said, okay, and up here my deploy screen goes up. I said, okay, deploy this. It then goes and starts and now I should be able to see messages from the device. Because then I go and say, okay, take a function and extract from the payload the temperature. And then I said, okay, based on the temperature I have a temperature threshold. I said, okay, is it below 40 or above 40 or is it exactly 42? I have three entry point and then I can say, okay, here I have a moustache template to output the data. And then I simply, in this case for demo purposes I simply use a debug window. And then when you look at this oops, I've played a little bit already and you see temperature 35 within safe limits. Let's play a little bit 35 sub, sub, sub, sub, sub, sub, sub, 42. I go back to my application as a, one thing is all questions of the universe are answered. That's here. This one. And since I said evaluate every condition it also said temperature is critical. So I immediately have, without great ado if I have a sensor that can connect to the IBM IoT user in Bluemix to process my results. Now you can say, oh, this is funny virtual sensor is no big deal but I have real sensors. How do I do this? Any data size constraints on this transmitted IoT data? Of course, if you want results fast you should keep your data small. What if it's a once every minute? It's not a problem. By the way, there's one of the things you might want to do is you can then pump it into the alchemy API and it will tell you back which people were on the picture. Alchemy is within this. Within Watson. There is also a visual recognition API for Watson which is another thing that you can do. My favourite example is they have a wonderful picture of a tiger and Watson goes and looks at it with a 78% probability that's a tiger. Do you know I put in my picture in there to ask Watson, what is this? You know what it says? I'm a shoe. A shoe?  Not quite embarrassingly enough when I was presenting in public, you are a shoe. This is why I use not your speech. Okay, on developer IBM.com or IOT foundation both URLs are the same. There are all the ready recipes for IOT devices and what I was using was simulated device but you look, we have the arm and bed in the little gallery. I was in Penang last Saturday so I had a little chat with the Intel guys. It just took one out of the box plugged it in, deployed the library and it just worked. Which is pretty cool because you can use the device simulator to try something. You can even create a page which emits data play with it even if your hardware is not ready you already can program. The Raspberry Pi Arduino UNO the TI stuff and and and. Spark is an Arduino.  So pretty much when you can simulate and eventually you can actually replace it directly when you have the device already available. So you can do all your testing and everything with a mock hardware device. I think from a software development perspective it's pretty useful. You don't have to build your hardware first and wait for it to be built before you do your software. The other thing is there is a Node-RED extension for the Spark car directly from what they now call ParticleIO. I didn't get my bloody Spark to work so otherwise I would have shown it. So basically these are all the stuff so when you said this MQTT stuff is okay but I really don't want to really go into the deep things you get the readymade libraries there. Of course another example you can always is able to do HTTP get or post. You can connect it to the IoT device as well. There is a question here? Well, so I have seen that for example if you simulate the Raspberry Pi you will have some graphical representation in some way to see the GPIOs and see the outputs and then simulate the... Sorry! It's not what I say. What he meant is not that you simulate the Raspberry Pi but I say you think about building a piece of hardware you know what it will send out and you can simulate the signalage already not the device itself. We're not in the business of... We just simulate revenue. So I have a question. So if I have the actual device why get the actual device to connect? Click here and it brings it to the download page. There is a there's a small library for that you just add it to your project and then you need it with network connectivity with a Wi-Fi shield or network shield. So this library will assist us in transmitting the data? Correct. Is there any data types that are already defined? No. Of course you have strings in there so basically at the end of the day when you look at MQTT payloads most of them are string based but like I say nobody stops you from transmitting binary data. MQTT is perfectly capable of doing that. Based on your network capabilities. The message in MQTT is up to 125 megabits. 125 megabits. That's a standard. This is there. SD card Linux image content to the micro SD card connect your board off you go. The funny thing is the Galileo uses the Arduino IDE. I find that quite amusing. So quickly back where is my oops no here we go. Then I use another example. This is Trine. This one. Trine can't do MQTT. Trine only does HTTP. So you see here temperature let me switch off the simulator data first. So this is like switching on and off the debug. And I got the twine here so I shake this a little bit and eventually you see temperature 25 degrees orientation was right and then message a sacrifice over. That was like say when I put the twine flat this is the message the twine network generates and when you look here as an example this is basically simply said okay I want to have a post and to the URL slash twine on my IoT demo and then it will automatically take a standard HTTP post and transfer that into a string for me so I can process it. So that's another example how can connect with an IoT capable device. The libraries that we have the recipes that use MQTT so use the IBM IoT cloud if you fancy to talk to MQTT directly it's available here as well. HTTP get and post actually knows the more get post put delete. And then the last one so you don't really need to you don't really need to go through the IoT IBM IoT platform right? Only if you want to. This is like the advertisement when Next we will tell you about price and how expensive it is. When Daimler Benz came out with a navigator they had this wonderful lawn with a beautiful lady and with our navigator you never have to ask for the way anymore unless you want to. Same with the IoT cloud you see down here I have open weather so I went in here and said okay I have this is just a trigger that goes and repeats in an interval every one minute and then it says okay please pull out the Singapore weather for me and then just send it to the debug so and this one was one of the extensions that is available for Node-RED to so you don't have to go okay I need to make a HTTP call to this and then get things back you can really encapsulate functionality into this modules and this is one of the things I would like to show you there is red-nodes.org this is the registry where all the extensions for Node-RED are published and the installation is really really complicated for most of the packages you just go to your packages file and say I depend on this package and it will show up in your editor that's all and then you see LDARB and MQTT and AT&T, MX2, M2X whatever that might be so there are 14 pages of additional modules that can make your interaction with the Node-RED environment much simpler and last last not least where was it this one that's my little there is the the thingbox.io and that is for our Raspberry Pi fans for the Pi-1 and Pi-2 with the Node-RED installation running on it if you said okay, I got my local little exercise running I go and collect my data for instance using the Bluetooth devices the punch rubines I collect data locally and then either I do from there HDPOS to the cloud or use the cloud and database run it on the Pi the cloud, that's up to you so you then have like say one level of environment where you very rapidly can assemble your stuff at the end of the day the source code is all open if you said okay, I'm outgrowing the Node-RED stuff you always can steal the source code the engine that is running under the graphical UI that processes all the data that was roughly okay so was that okay, now that was a block entry, that's not saying about installing HDB on the Raspberry you're gonna compile the links and put it on the side let me know all the links and I'll put it on the meetup.com okay, so recipes sample sensors Node-RED, this is local and he has a light blue beam I said okay, I wanna read like say, I wanna whenever the acceleration kicks in, please light up the beam as simple as that and then when the beam I just need to go and say okay, which of the beams is it and get the idea of the beam in there whatever and voilà, and this as fast as it can go and program with the stuff little faster than the other stuff you can actually process and output it to an HTTP post so that you can actually put it all your data and all your processing can do it here and you can post it to your website I can go outside and go to HTTP and say okay up to HTTP, off you go or to MQ or WebSocket or let's say, I probably would today rather use WebSocket than HTTP but up to you and you can actually say I also wanna put that into WebSocket oops wanna put that into WebSocket and while I'm on it let me let me tweet it of course let's say this is not magic so you need to have like say you need to have your Twitter credentials so you authenticate with Twitter and say it posts on your behalf so there's nothing irregular there can you sort of decompose them particularly large, complicated things so you see here you saw that on the other side already so I use different pages and then there is also the latest one where we added is the ability to somewhere I said what are you looking for? subpage subflows create a subflow then you have a subflow and just press the plus button that's a so that subflow can then be called by an input an output and then I can go and call that subflow from one of my main flows I think it should show up here where is it there you go subflow and my weather source should go to the subflow first and then from the subflow goes back to the output how many models 10,000 sensors when you go that's an excellent question if you go and look at the IBM IoT let me just drag this one over so you would not go and use the quick start you use the API key and then in the API key you say okay you group them by types for instance I say you have 10,000 sensors 5,000 temperature, 5,000 pressure so I said okay the device type so you say tempxy whatever you however they identify that and then they said all of them and then you collect them in one go so you have some attributes exactly device ID event type you can say what format maybe some of the devices some of them send plane text so you have this ability to group them up so you don't end up with 10,000 inputs that would be a little silly when I deploy the sensors then how does the sensor know about these is it something that I've provided through the API configuration on the sensor that's one of the stuff what the libraries that we provide help you to configure so what I see in a practical way this idea that I have I have a single sensor that straight away talks to the network that's nice for simple use cases if you start deploying armies of sensors you have a collection hierarchy that's very clear and then you said okay maybe you have the raspberry talking to the internet and then you have a bunch of Arduino talking to the raspberry and then you have the analog ports on your Arduino then serving a bunch of sensors that's what would be a very typical hierarchy where you easily have a few hundred sensors which end up with a single internet connection from a local aggregator like the raspberry so this would be something I would provision when I deploy before I deploy it or while I deploy it correct any questions more questions so I understand you will save all the coding of the low level stuff but I still think this is all the fun of coding something but you still have to go you can go to the boiler let's say give me go and then IoT I totally agree with the approach I understand that probably I can connect to it I can easily I can create an API to connect to it if I have to do a more complex logic based on let's say Python or Go and I just connect to an API but there's no way to once I create this logic here to actually connect natively with it I mean like I said to somehow if I want to run this in the actual Raspberry Pi and I want to create I want to use all this logic without having to to actually go out to Lumix that one runs on a Raspberry this thing is actually running so that because what I see there that's not on the local machine so this this one is on Lumix and that one that one is on local so I have two installations so I can have it running all locally and save all the all the hassle of coming to create to write all the low levels but then I need two models one for the Raspberry it's not one model exactly what I'm thinking is my background is in the auto industry and what they sometimes do is they create models across different ECUs and then say they deploy them afterwards and say this one is here and this one is there actually they're called node packages so you can the same node package with the same logic can run on two different devices so what you do if you said normally reusable modules you create one of these yourself and this is a very simple node package so even I could read the code that is very interesting but it's not what I meant I meant that you already have an end-to-end model and then say this part of the model runs here and this part of the model runs there you can do that how can you push how can you push updates to in the context of one node server exactly yes you can yes you can you just need to make that one leap of faith A running node server is part of a bigger system so you orchestrate that using a set of APIs I have a scenario it might be what you just answered a node server by itself doesn't spend across node servers but nobody stops you that a node server it goes to an API to a fellow node server so you can orchestrate that so you I can't build a model in one screen here that has pieces running on one node and pieces running on another that's right but you could do that and say you model it in one screen deployed on both ends and the ends know which part to run so if I have 7e run but in 5 is enough to relate that's not the kind of thing that's being answered for the concern we're talking about do you have a tool here that deals with one instance I go the question is about a tool that deals with a deployed instance so you see it like I say I got these four tabs in there I can take this model and deploy it to all instances so I have one model that I deploy everywhere but as long as I use the input from only one then only that one page will run because the other pages don't get an input they won't process anyway still answering a different question because it's closed which this one yeah, Node-RED is not a DevOps tool that's right so that was being asked I think it's already so yeah so I have a scenario if I deploy 7e Raspberry Pi in a mesh, in a village anyone or many of them can break down their connection to the internet can I still converge all the data in this blue mix depends on how you design it I'm not so user space a programmer can I converge so there's two things that come to my mind yeah the first one is like say MQ is designed to have a reliable message delivery I would have a little bit how long can it work how much buffer would it have before it breaks down I probably because I have a more background in databases than in networks I would probably go and put a couch to be on the Raspberry because like say you put a 32 gig memory card in there you can store a lot of data and that one can say okay if I have a network connection I do a synchronization transmit the data and if there's no network connection it just collects the data locally so using a couch to be you can do that the occasionally connected network the occasional, no? that's basically the scenario described so my thinking is in a place where the net can break down in one point but we can store and forward by machine can the data still be all converged I call that the occasionally connected network the network is always available except at the moment you need it you have the right to use as sources or you can use them as consensus either they can be the source of information or they can be collectors also so the Raspberry sits there collects it's peripheral but it also takes in the data from over there and gives it around there storage so I don't see a problem with that it's just when all the Raspberry Pisces gets all the data now the question is where do you want to send it to and how that's the question whether this modeling programming environment can support that kind of store and forward messaging system so this really is a case one so are you doing any processing to the data in the pie there might be some pre-processing of the data because you don't want to send out all the data you want to send out the unfiltered data which is going to be like a mess of a lot of information so what you want to do is probably you want to use this on the Raspberry Pi each of them is gathering the data break down the data, analyze a little bit I don't do something with it pre-processing the data make it a little bit smaller maybe in the bytes and then start sending out kilobytes kilobytes rather than in the max and the multiple max I see the pictures coming my consultant it's very important that is if you have a rough idea of what your connectivity is that will limit how much data you can actually transmit that will decide how small, how much you want to compress it or how much you want to process it it's just an internet connection by any one of these Raspberry Pi's might not be reliable one for many of them but also what does it mean not reliable 90%, 95% 30% or the occasional connectivity I think because it's okay I'm not sure I understand the concept because if you said that this is an internet connectivity this is IP transit how do you mesh them supposing I had a river I had to deploy 70 Raspberry Pi's along this river line so it's not an internet connection there are not many villages with internet connection along this river line how do you mesh them I mean the Raspberry Pi's have one storing forward I never mention Raspberry Pi oh okay sorry I only use the word Raspberry Pi because they have used it as a concentrator gateway if you have a mesh then what's your mesh it'll be computers like the Raspberry Pi just a different computer what kind of mesh network Wi-Fi so we have 300 meters maybe who knows sorry I have a question I'm sorry I want to monopolize the question but your first part of the session you show about a session of Python I think somebody asked about whether the framework is in place or not the question is how do I get libraries into there how do I get my libraries to be in there so there's two parts the easiest one is the very moment you add it to the version control system you will clone the repository pack everything you need in there and just deploy it back I can just understand the repository so I'll write that on my own and then get it there and then whatever I run there I will pick it up from the repository there is a little bit more esoteric mechanism there in the documentation a certain set of standard libraries you can define as dependencies and then the build process will add them to you the reason I ask is because could be pretty dangerous right if you don't sanitize that this is a big problem but you have the challenge where you sanitize whatever I put in there so what is it that so what are you concerned in terms of sanitization it's not going to be I assume it will be your concern over your siege of CPU well I assume it will be more of your concern of mine in terms of sanitization what I put in there you're paying for the CPU time no you're not paying for the CPU time so essentially how Blooming's works is you're only paying for memory usage of your instance so CPU time networking you're not paying for it we have a standard fair use so to answer your question there is a standard fair use if you actually become a rogue application so say for example your application starts using lots of CPU starts sending out lots of networking and stuff like that alright so we do have an internal kind of mechanism in order to identify which one becomes rogue and we'll shut it down sorry every application is a sandbox every application is a sandbox so say for example he didn't show you in the way below that we actually have an experimental MySQL server so MySQL server you cannot connect to the MySQL server except within the Blooming's platform so everything is all sandbox the only thing that's not sandbox is your API or other your application that's exposed to HTTP import AD but all database connections and everything unless it's a cloud service say for example like cloudin it's a different cloud provider which is under Blooming's too under IBM also so that's how it is but everything that's like MySQL that's installed locally on the instance itself it is a firewall within that sandbox within that instance see the whole magic under cloud foundry do isolation monitoring limiting instances so everything is sandbox and runs on a virtual CPU basically which is quite interesting it's like say how is it different from a container because it's almost the same technology at the end I have a way to deploy that if I decide to put that into into a virtual machine into a container or virtual machine so I have another choice for what containers and virtual machines and they say what's interesting is when we started was cloud foundry only and then we realized that the distinction between infrastructure and platform is kind of an artificial one because like say where does it stop if I have a pretty configured container that's almost as good as a platform so that's one of the reasons that then only in January we added the containers and the virtual machines they're still in beta which is quite nice because beta means we don't charge for them yet and so what will happen over time I would say give it five years every single IBM software offering will be available as a service and blow mix including the ability like say to even provision bare metal virtual servers what you do today do in IBM's infrastructure as a service offering software and so the idea is to have a single interface where you can pick and choose all your compute needs hopefully it's not so depressing that's that green brown I think one of the things is they're trying to change the color scheme and everything so really yeah they are what do you mean is this a complete separate approach from your infrastructure as a service so it's also dependent it's a software right so infrastructure as a service software they're two different offerings there the funny thing is I say when you buy a virtual machine on blow mix you can buy a virtual machine on software you can buy a virtual machine on blow mix and the difference is where the bill comes from you can get into the software infrastructure so we make we call their APIs there and this is why I say I teach my software colleagues and I said you're you're doomed because you're going to be blowmix in half a year so the next question there will be does blowmix allow me to use other APIs can I talk to Amazon yes you can so I can use blowmix to ask Maria anything that you know REST APIs everything all of that stuff it's all right and the beauty of that is you're not paying for the network cost whereas if you're having on the AWS you're actually paying for the network cost you still have to understand the API and Amazon API something on the back end of this so you already have built in let's say for Amazon they are our competitors we will not entertain them there are sufficient libraries from Amazon available Amazon has APIs for all the different languages right to get your job I'm talking about the infrastructure service if I'm going to deploy something as a platform here I'm going to use the platform here but I want this to run on an instance in Amazon so you need to sort and then we have to be a little bit more specific you go to Amazon you're talking about infrastructure this is platform so the overlay is that okay I can deploy containers in the Amazon I can deploy containers into blowmix you then have to go and say okay you need to have the container deployable when you go and use the Amazon platform as a service so you have what's it called the database they're using Elastic Beanstalk DocumentDB now that was Microsoft what is it full storage? SG? so Elastic Beanstalk would be the equivalent but they are all proprietary APIs they're not compatible to anything I thought you had some sort of abstraction with your connector that's what you had all your not yet that's not going to happen it doesn't have to be Amazon or not Amazon forget about Amazon let's say I run it in my data center my own open stack I don't want to go and implement all this if it's open stack you can deploy it Cloud Foundry sorry Cloud Foundry I promise that Amazon won't implement let's I mean Amazon provides the APIs they're open APIs as long as you implement the abstraction you can launch I'm running out of follow-up you can plug in now implement Amazon and Amazon is not going to be able to implement the APIs just have a question one of the models is a bigger board do you have a hardware with the same Texas instrument sure take that live pretty much that alright so next up we have Nikolai if you're saying Lee because it's a LAY LAY yes actually


Hi. My name is Henry Castro. I'm from South America. So this is my first experience here in the LibreOffice conference. So I'm happy to see the community here. So we're going to talk about the make-fi, why I did that change for bundling JavaScript on the M4. Let's go a little bit for history. We're going to check about the jack-fi. It was the original JavaScript bundling. Then some rules for a make-fi. Just an example of what I did. The M4, microprocessor, low leaf left, and the HTML how to generate the file. Let's start from the beginning. Leaf left is the main component of library for JavaScript. We started with version 0.8. This was the original package. And left left is library oriented or designed for maps. So we are starting to change this, adapting the code to handle the types of the documents for collaborative online. At that time, we had to use the bundling. The original bundling was the jack-fi. It's similar to a make-fi, but it's the make-fi for the JavaScript. They have several tasks. One of the tasks was just to bundling all the source files of the leaf left. You can see this in the original code. The jack-fi has a built task. We'll see the next one. That starts to concatenate all the source files into one big file, and that's the bundling. After that process, they follow with the ugly-fying just to compress the file. This was the original. As you see, this was the normal process for bundling with the original left-left library. Then you can see that they have an older list of files, the source you can see here. These files have some organizations. Then every file has a specific order because JavaScript has a prototype definition. If you change the order, maybe you can break something in the bundling, building the library. So it was based in that file with all the definitions of the files. This task was the previous, just only grab all that list and start concatenating one of them to have just one single bundled file. That's the bundling process. We were not so smart at that time, so we were more focused on adapting the code. We have so many problems. The browser just automatically split in files when you want to debug. For example, for me, to debug, it was really painful. You can check the original left-left package library. They have a debug folder, and the debug folder, we have several examples. That's the samples. They have a script tag that we can show how to debug. This was the best environment debugging at that time because it was easy for me just to see an inspector in the browser inspector of the source files when I can check the break points. So easily unfollow what line of code I did and what is the file location. So an example, if you run that file example, it will show you every script tag with every source file, the location of the source file, and if you had to modify something, you know exactly where what's the code you can change because at that time we were more concentrated and just adapting the patches. So you can see this is the same list here. So basically, this debug sample just lists all the files. So my problem was just when I tried to do the changes, so I had to do my local changes and adapt this debug example file to change it to call our own line and start debugging. Locally, I had to do the changes by myself and start debugging when there's some problem that happens because the boundary for me was one big file, it was difficult to find. I don't remember what was the code. They had to look by myself, I had to search the code, what's the file I modified, so it was really complicated to debug in that occasion. So what I did, okay, to summarize, they have three components. Four components are important to build that leaflet. There was no package manager, just dependencies we already need. And the linting utility, just like my co-worker say that we need to, for checking the same test of JavaScript, we have the jake at that time. We need that utility just to bundle the leaflet. And after the process of bundling that, we create an ugly file to compress the file and deploy the result. So what was my idea to not start to change all my local changes by my side? So the idea was just grab the sofas, and if I just create a build with the debug symbols to build the server, the callable server, just I need to copy the files, the sofas, and generate the list of tags for every sofas what I need. Just like an example that I showed you before. If we want to deploy to our production, then we can just go for the release build and do the same process while they were doing the jake file, just concatenate the files, and once the component aglify, and just generate one single tag with one file bundled. That was the idea. How to do that in the code? Unfortunately, I just talked about in the other packages, I couldn't find a way to do this. So the natural way was just to use the mic file. I just did the mic file. If you can check here, I just add two rows here, and if it's coming with the configuration with the debug symbols, just I need to copy the source file to the destination folder. That was the simple step that I do if I want to debug. Then in the other case, of course, if we have a release build, just we need to concatenate the file exactly the same thing with all the list that dependencies, with all the source files and also the leaflet. So we have one big file bundled. After that, of course, there's an aglify process. Two simple rows, no dependencies, I remove the jake file, just to install that, and use the natural mic file with two simple rows. Then how to generate the only problem I have is only generate that single tag. If it's a release build, just generate one single tag to the bundled file. If it's a debug, with the debug symbol, I just have to generate all the list of source files. So I use the natural command, which is including in every GNU Linux distribution with the M4, and it's come with the make files. So the M4, this M4 is a macroprocessor, which is just set the variables and expand these variables according to the conditional. So I got two inputs here. I have to pass the variables and something like a template, the little leaflet template, so the M4 process is processor, the input file, and the output will be the final little leaflet HTML that is used for my collaboration online. The collaboration online, this was the last step we need. So I have to add a new rule, just last rule, and last rule, as you can see, we can pass the definition of the variables, and if it's debug, we have all the list of all source files of the little leaflet, and we call the command M4, just to process these two files. This two inputs, sorry. Then let's see about the leaflet HTML M4. I just need one simple conditional way if this is debug. We'll just generate all the script for every source file in the leaflet, and in case this is a release build, just one single tag, which the bundle, this is the result. That's what's simple. As you can see, there were added more macaworkers that did for, if this is a case for mobile or for Android, this was useful for them to create the proper script tags to generate the final little leaf HTML. Well, the result was, what must you make run in your command and start running in the bug, just like say, Macaworker, you open your browser, and you will see all the files of the little leaflet. You can set a bug point, you can check it's result very fast. You can have a better experience debugging in that way. Of course, this was for the normal browsers. At that time, we are not thinking about the mobile, but it's amazing how it's adapted to attach a remote and do the same result. Okay. Well, at the end, the result was the not package manager. We need just that ability, but we had to download it from the packages, and the make file is not dependencies. We already have, so no problem. And the ugly file, the two main packages needed to bundle the little leaflet right now. Of course, there are the additional libraries we use for toolbar, context menu, that are already included in the bundle process. So, the in another way, this is a bounding, it's not complicated like you see. Well, that's what the result I did. Hopefully, the little leaf packages, of course, the new version are changed. Of course, the bounding time and the tools, too. So, at that time, we cannot upgrade that packages, because we did so many changes for Color War Online that revasing that for the latest source code, it will be complicated. But, okay, I think that's it for me. Do you have any questions? That's what I did for just simplify my debugging process in JavaScript. Thank you.


we are going to do an unboxing video first unboxing video on the channel so let's see how it goes i've invited gearston gearston co-colleague at the studio so we've got a package here on the table creative clues you have no clue what the creative clues are right no so this is a surprise um i'm going to hand this package to you and then the unboxing will be yours creative clues i'll include the links down below it's uh you'll see what it is but it's a Kickstarter project started by andre carrol from berlin and then we have the unboxing and it's a set of stickers stickers can you show me what kind of stickers do we have a set of stickers and these metaphors and symbols devices and technology so a lot of stickers this is like the uh Kickstarter edition the full bundle i think it doesn't come in a bubble wrapping anymore but in a different packaging but i was one of the first ones who supported this Kickstarter initiative so i got the exclusive set there are so there are a lot of stickers like people what all devices and technology there's a lot there's a lot needs and value needs and values industries and objects what ah i like this one emojis it's printed they have an index and they should be reusable stickers we'll try that tomorrow in the session and see how it goes so the idea behind the set from what i got from andre story was that you can use these to enrich your workshops let people work in a more visual way rather than just words yeah um we're going to do a session tomorrow right we have a workshop so the idea is to actually prototype this yeah any ideas on how this might be useful and the thing we're going to do tomorrow yeah i think it would be nice when i see this for the brainstorming because that's often a lot like with words and now you can also maybe get inspiration from these first and then get ideas i think that would be something i'd like to prototype and we're back yes we got the opportunity to prototype creative clues not once but twice yesterday what did we do kirsten well we used it together with the team to fill out a project canvas and i used it together with a colleague yesterday and how did the creative session go the workshop well it went well the people kind of got to get used to it um but they visualized words they already wrote down on post-its and there was one lady that used it as a metaphor to explain something to that basically to tell a story right yeah in in within image yes uh and the other way we uh prototyped it you prototyped it how did you use the creative clues there well that was more to make the poster richer i think first we thought oh we have to fill out stuff and i'll make some drawings and then i thought it will go faster if i just use these stickers so this was like a poster with a project plan a lot of words right something like that in this you use the creative clues to make it more yeah visually appealing yeah right what's your experience um when how did they work and when would you consider using them um i would consider using them myself if i have to speed up i think you can work very quickly with it you yeah and with uh teams or groups i think it's best if people are not really used to work with visuals or to draw that might be a step too far for them and then using these stickers is more easy who do you think would benefit the most like who is the target audience are are are they people like us service designers or um i don't really think so because my thought was immediately how can i create this myself and make it more personalized or how we would very specifically use it um but i think for people who start with service design or want to work more visual start with making customer journey maps for example for them it would be really great to enrich them and to uh yeah work with these visuals yeah we had the conversation like a lot of designers probably get the urge to create this themselves well probably a lot of the let's generalize here and use the word managers like managers and all the meetings the boring meetings where you use the flip overs and you don't get further than bullet points right those kind of meetings i think those are all occasions where creative clues would be really helpful yeah right yeah in the in in settings where people are used to bullet points the bullet point sessions yes so um what what would you say did you find any things that you thought well this could be improved or here are some opportunities for version 2.0 yeah i think so first of all uh like when we first unwrap the package there was a lot on the table um and there are categories written down on top but it's all in black letters and you it's not really visual you still have to read it and to search what what belongs together it's a lot of categories also so for me that could be quicker maybe um maybe less categories maybe four and just a very easy visual overview of what yeah belongs together that's one mm-hmm anything else um we also we we also talked about probably we have we have the full bundle like we have the Kickstarter edition with everything in it and that's a lot and what we already saw yesterday is probably it's like the golden 80-20 rule probably you'll just end up using 20 percent of the images that are in this set and but you'll use them a lot yeah so probably after using this for a while you'll figure out which images you fit your niche your your audience and then you probably want a lot of those so this is good to start out with to get an understanding of what's possible um it's that one other thing yeah i just came up um i was thinking i would like to choose the colors maybe of course you do but that's uh the designer kind of thing um to make it fit uh with the the style with the branding yeah yeah so now it's a lot of colors and uh maybe it would be nice if you could just choose okay so creative clues recommended and when to summarize what would you say um buy this if you yeah if you want to work more visual and everybody needs to work more visually absolutely the link uh to where you can order the creative clues is down below in the show notes uh if you've tried them leave a comment let us know what how did you use them uh what do you think our pros and cons uh love to know thanks for review kerson bye


Hello everyone, welcome to Options with Doug. Streaming live daily on Bookmap Discord and the Bookmap YouTube channel at 1.30 p.m. Eastern Time. Okay, JEC says audio is good today. All right, great. Yeah, I accidentally had muted my microphone yesterday, so thanks for the confirmation. Appears that everything is good, so again, welcome. Before I get started, I need to go through the Disclosures, General Disclosure. All Bookmap limited materials, information, and presentations are for educational purposes only and should not be considered specific investment advice nor recommendations. Risk disclosure, trading futures, equities, and options involves substantial risk of loss and is not suitable for all investors. Past performance is not necessarily indicative of future results. The focus of my presentation today as every day is options, order flow, the impact of options markets on stocks and futures, and the influence of market maker hedging flow on price action. I have a two-step process for trading and the first is planning, and I use positional analysis, and I look at how traders and market makers are positioned in the options market and how those positions change from day to day to develop a thesis regarding the expected trading range and volatility for the day as well as a directional bias. And the second step in my process is execution. And I look at real-time order flow in Bookmap and real-time market maker hedging flow in Spot Gamma Hero to confirm my thesis and for setups, for entries and exits. I think this is a new way of looking at the market that provides a significant edge. And just to be clear, I'm talking about the influence of the options market on stocks, futures, and options. And I will be talking about setups, and those setups can be, you can take them any way you want with shares, futures, or options. So I'm just talking about generic setups here, and not necessarily which instrument or which version of an instrument that you should trade. Okay, on topic questions and comments are welcome again. These are my topics, order flow, options order flow, and the impact of options markets on stocks, futures, and options. And I will be watching chat in the options-dug chat channel and Discord and also the chat in YouTube. So again, on topic questions and comments are welcome. All right, let's get started. So the items that I want to cover today, first of all, go over the news, economic data and events for today and the rest of this week and also briefly touch on some economic data coming up in advance next week. And then we'll go through our positional analysis. And then finally we'll take a look at some setups. All right, so first of all, today, the news today, jobless claims came out at 8 30 a.m. Eastern time. And it was a little bit weaker than forecast or more more jobless came claims than forecast. And I have never seen a reaction like this to jobless claims. The from the at the time the data was released 8 30 a.m. to the opening high. E.S. was up 37 and a half points. And I maybe you guys in JEC, Trader HE, anybody else in in Discord, if you've ever seen anything like this for jobless claims, which is usually a non-event. And I guess traders were thinking that this jobless claims being weaker than expected might might point to the employment situation report that comes out tomorrow is being weaker than expected. So anyway, I've never seen anything like this from jobless claims. The market is just so focused on on data, you know, especially since Fed Chair Powell, I guess, re reiterated that the Fed will be focusing on the data coming up. And so speaking of that again tomorrow, the employment report at 8 30 a.m. Eastern time. And then next week, and we'll cover this more next week, the CPI report, PPI report, and then the big event for the week is the options expiration, the big monthly and quarterly options expiration on March 17. All right, let's take a look at some charts now. We'll start our positional analysis. This is the S&P 500 futures ES. And before I dig into this chart, I'm going to take a look at a larger timeframe, longer timeframe. This is SPX, a 20 day one hour chart. And this is just simply showing price and key gamma levels. And these levels are from Spot Gamma. They're provided to Spot Gamma subscribers in a Think Script. And you have to manually update this. And it's it takes a couple minutes. So this is a 20 day one hour chart. Again, just showing price and key levels. And just to point out a few levels, and I'll talk more about these in a minute. And what exactly they mean. So here are the key levels. The put wall at 3,900. And then here is the 4,000 key gamma strike. That's also the volatility trigger.  And now let's take a look at a shorter timeframe. Again, just focusing on a simple chart of price and key levels. And this is a, again, an SPX level SPX chart showing just price and levels for a one day one minute chart here. So this is showing this 410 level, which was noted. This is 40, 40 10 SPX 40 10, noted as a pivot level in the Spot Gamma AM founders note. Here's the 4,000 level. Again, the key gamma strike as well as the volatility trigger. And then this is the 39 60 39 60 support level that was also noted in the AM founders note right here. That's the purple line. So 40 10 was noted as a pivot. And then 39 60 noted as support. And then of course, here's the big 4,000 level. And while we're looking at this, the volatility trigger is spot gammas proprietary gamma flip level. And above that, the assumption is that market makers are in a positive gamma position. And they will need to hedge against price to hedge their delta exposure. And then below the volatility trigger, Spot Gamma market makers position on the gamma curve is negative. And that means they will need to hedge with price to hedge their delta exposure. And that tends to increase volatility. So above the volatility trigger, you would expect market makers to be trading against price and tends to suppress volatility. And it's just the opposite below the volatility trigger. So with a break below the volatility trigger, I would definitely be looking for shorts. And I was actually looking for shorts well before that. And I'll talk more about that. All right, so that is the bigger picture, just looking at price and levels. And now let's take a look at the bookmap chart. And one reason that I look at the look at those other charts, it's just very simple. There's a lot going on here in the bookmap chart. I have two columns of levels here. The first is the spot gamma cloud notes. These are the same levels provided to spot gamma subscribers, they provide those for a variety of platforms. And here it's shown for bookmap. These cloud notes are updated automatically every night. So this is showing the, there's that SPX 4000 level. Right now, spot gamma is using a five point difference between ES and SPX. And I calculated about a two point difference. So I've marked my levels a little bit lower. And this is my, these are my cloud notes. So there's that 40 10 level. And I'm also noting key spy levels. And there's the 400 spy key gamma strike volatility trigger. Here is the, I think a closer, closer to being accurate level for the 4000 SPX 4000 level. And then this is the 39 60 support level again that was noted in the AM founders note. And then finally, I'm also showing big round numbers, the zeros in the fifties for ES. So there were some levels in play and also the advantage of bookmap here is that you can see liquidity in the water book and the heat map shows the history of that liquidity. And up here at 40 20 that's showing all the cell orders in there. And that that proved to be resistance today. Traders traded up to that level, not quite to that level, and then started to move lower. And a couple things to notice here is the starting around, oh, just before 10 a.m. This dark blue to pink line is cumulative volume delta. And that shifted downward negative just before 10 a.m. And then price continues lower. And then also note the the drop below the four SPX 4000 ES 4000 level, and then just avoid of levels down to the 39 60. And then here are the levels below at 39 50. If this 39 60 support level does not hold. And when we look at setups, I'll look at this in more detail and see that we can see that options traders were not having any of this rally in the morning, I guess they briefly traded in the direction of price bullishly, but they quickly quickly shifted to bearish. And now the S&P 500 is taken back all of that move after the data this morning and more. Okay, let's talk about shifts in levels now. And I'm tracking the key daily levels for the S&P 500 SPX and spy as well as stocks. And I'm looking at the volatility trigger the zero gamma level put wall call wall and key gamma strike. And again, the volatility trigger is spot gammas proprietary gamma flip level. And that level shifted lower for SPX from yesterday to today, just slightly from four thousand five to four thousand and remain the same at 400 for spy. And then for QQQ shifted lower from 300 yesterday to 296 today. And then the only other significant shift was the call wall for spy shifted down from 408 yesterday to 405 today. So this this has kind of been a an ongoing theme of very little shifts in levels in the indices and in stocks as well. And I think you can attribute a lot of this to the to the volume in zero DTE options options that expire today, they're not held overnight. So they have this volume high volume for options that trade today, have an influence on the market today, but don't have any influence on on positions because they are closed at the end of the day or, you know, sometime during the day. So that that just points to the importance of marking your levels on the charts and then watching the watching the order flow and the hedging flow during the day. And that's kind of been the approach that I've been taking recently. All right, so those are the shifts and levels. And now let's take a look at the let's take a look at the gamma levels. All right, so these this is where those levels come from. So this is SPX absolute gamma levels. And what this chart is showing is market makers position at these different strikes. This is the zero level. And above that's positive gamma or call gamma. And below that level that showing put gamma or negative gamma with the teal bars. So black bars are called gamma positive gamma and teal bars are negative gamma put gamma. All right, so this is SPX showing the 4000 key gamma strike. That's the absolute gamma strike. The strike with the largest absolute gamma that can act as support or resistance or as a magnet. And then 3900 is the put wall. No change there. And 4200 is the call wall. The put wall is the strike with the largest net negative gamma. And that can be expected to act as support. And the 4200 call wall, that's the strike with the largest net positive gamma. And that can be expected to act as resistance. So that's SPX. And note the the predominance of put gamma below the 4000 level. And that is also the volatility trigger, the gamma flip level. All right, so that's SPX. Let's take a look at spy. For spy 400 is the key gamma strike. 390 is the put wall. Strike with the largest net negative gamma. And then remember the call wall shifted down from 408, which didn't make a lot of sense. It's usually a 0 or a 5 level. And so now it's at 405. And again, that's the call wall, the strike with the largest net positive gamma. And just like SPX, note the the dominance of put gamma below the 400 level and some call gamma above the 400 level. All right, while we're on this on this page, let's take a look at the combo levels. Let's start with SPX. And this is showing market makers position on the gamma curve, their position for at these different strikes for a combined SPX and spy shown in terms of SPX levels. So here is the there's the 4000 strike. Again, that's that is the volatility trigger. And note the put gamma below that level. Call gamma positive gamma above that level. So that's SPX. Here's spy. Same thing. Here is the right around here is the 400 level. There it is. Put gamma negative gamma below. Call gamma positive gamma above. But the put gamma clearly dominates. And then finally, right, welcome trader Pete glad you're here. All right, then finally, while we're on this page, let's take a look at the open interest in volume. And this is for SPX put data. Let's actually let's we'll show call data and input data here. And we'll let's focus on the put data zoom in on this so we can see it. The black bars are showing the volume. And this is from yesterday. And volume, that's what traded yesterday. And then the small teal bars. That's the open interest change. So this has been pretty typical for a while now is the the huge volume compared to the open interest change. So that just reinforces the fact fact that you know, the bulk of the volume is in zero DTE options. And that appears to be a good part of what's moving price around. And for the last few days, it has been zero DTE options traders have been selling highs and buying lows. And in just a few minutes, we'll take a look and see what they've been doing today. All right, so that is those are the S&P 500 gamma levels. And the open interest and the combo levels. Let's take a quick look at NASDAQ. And for NASDAQ, we'll just look at qqq. And for qqq. 300 is the key gamma strike. 290 is the put wall. And 310 is the call wall. And again, just like the S&P 500 predominance of put gamma below the 300 level and call gamma above. All right, let's take a look at data now. And I like it to focus on the gamma notional. This is market makers position on the gamma curve for SPX, SPY, and qqq. SPX in the left column, SPY in the middle column, and qqq on the right column. And notice that all of these values are negative. So this means that for all these indices, traders are long puts, market makers are short puts, and they have to hedge their delta exposure as price decreases. They have to sell futures to hedge their delta exposure as price decreases. And then if price increases, they can buy back their short futures. So that's typical in a negative gamma environment. Again, market makers are trading with price to hedge their delta exposure, and that can tend to increase volatility in a negative gamma environment. And these numbers shifted slightly less negative from yesterday, but still all significantly negative, especially for SPY. So SPX yesterday was gamma notional, market makers position on the gamma curve for SPX was minus 565. And today it has shifted to minus 429. And I'm comparing morning to morning. Okay, the for SPY. Hold on just a second. Let me check something. What I'm seeing on YouTube doesn't. I'm not seeing any questions on YouTube. I don't know why, but it looks like my stream is going. Okay, so that is again, gamma notional shifted slightly less negative SPX minus 565 yesterday to minus 429 today. SPY minus 2336 yesterday to minus 2026. Okay, so JTT JC says stream is good. No questions so far. Great. Thanks for confirming. Okay, and then QQQ also shifted to slightly less negative minus 704 yesterday to minus 506. So still very negative, gamma notional for all indices here. Alright, let's take a look at the Vanna charts and these charts will graphically illustrate what I'm just talking about. This is for SPX showing how market makers delta notional changes as price changes and with changes implied volatility. And that's shown by the green curve, which shows again, market makers delta notional how it changes with changes in price and with implied volatility. And that's the Vanna effect, the change in delta with the change in implied volatility. And this is showing for SPX that market makers delta notional will increase as price decreases. And again, they have to sell futures as price drops because their delta notional is increasing and they want to remain delta neutral. So that is SPX. And let's take a look at spy. Same thing. Just a steeper curve. Remember the gamma notional was much more negative, much larger, almost five times the gamma notional of SPX. And then here's QQQ. The same thing again, negative gamma. All right, let's take a look at and wrap up our planning and positional analysis by looking at the current key gamma strike for the stocks on my watch list. This is my primary watch list, mostly large cap tech stocks. And I'm noting the key gamma strike from yesterday, that's the E column, the previous key gamma strike. And then the current key gamma strike is for today. And I compare the values from today versus yesterday. And I note, I color code these just for a quick reference. And here, for example, AMD and NVIDIA, the key gamma strike both increase for both of these. And I take that as a bearish signal. And what I will typically do is go into equity hub and do further research and see what the additional levels did, the hedge wall, call wall, put wall, see if those levels changed as well. So again, the initial interpretation for this was bullish. And just the opposite for Tesla. And we looked at the equity hub for Tesla yesterday and saw that there were some shifts lower. This 200 key gamma strike has not moved for 10 days. So this is the first drop lower in the key gamma strike for Tesla. And I interpreted this as bearish. So mixed signals there bullish for the semiconductors and they've been AMD and NVIDIA have both been strong this week. And Tesla has been on the weak side. Okay, so that's the planning preparation. I know how the market makers were positioned on the gamma curve today. And really, for my thesis for the day for the S&P 500, given the lack of shifts in levels and the predominance of zero DDE volume, my thesis and approach for the day was to establish the levels, the initial trading range, and then watch how the options traders both the zero DTE and and the longer term traders in the SPX plus spy and we'll take a look at that in just a minute, see how they were positioning. And that was a big clue for today as well as the past few days. And then for stocks here, I, you know, again, was bullish on AMD and NVIDIA and bearish on Tesla. All right, so let's take a look at some setups. So let's go. First of all, take a look at a hero here. And for those who may not be familiar, this is the combined signal for SPX and spy. And this is what you want to look at or what I look at whether I'm trading the S&P 500 futures, ES or SPX options or spy shares or options. This is the signal, the combined signal. Let me just get rid of this. That is that was the market polls. That's an excellent indicator confirmation that I have been using. And that's provided with book map. So let's take a look at the S&P 500. This is the total signal. And this combines all expirations, SPX and spy options and showing how options traders are approaching the day, what if they're taking positive or delta negative delta positions. And in the case of today, definitely overall negative delta quite by quite a bit. Other than here's the here's the open RTH open right around 930. The initial move was higher. And initially options traders were taking positive delta positions. And then they quickly turn that around. And notice how hero makes a series of lower highs and price does the same. And let's zoom in now and we can see that they're there was a good lead effect. So notice how hero starts to slope down even as price increases. So here was the first shorting opportunity. And then notice, you know, multiple short opportunities. This was the this one was more clear here as hero was clearly dropping and price was consolidating and then drop lower. Alright, so one thing to keep in mind, I can only present on one screen. But when I'm trading, I'm looking at multiple screens. So I'm looking at book map on one screen and hero on another. So I can see that both in real time. I know it's a little bit awkward here to look at one screen, and then the other and line up the time frames. But I, you know, I don't have to do that when I'm actually trading. I'm looking at two screens at the same time. Alright, so that is that's hero. And let's go out and take a look at book map again. So book map is showing the quick run up from 830 to right about right about 10am. And then we saw that hero had already shifted negative. And I talked about cumulative volume delta here shifting negative. And you can see all the pink dots, the market sell orders shown by these big pink dots. That's by minus sell. And if sell is there more sellers than buyers that it shows a pink dot and then multiple entries. And then finally, this has been confirmed by sell stop orders as well. Starting maybe about 11 really. That's the sloping yellow line. And you can see the sell stop orders. And notice the blue numbers to that those are iceberg orders large traders with their iceberg orders they use to hide their size have been fading this move all the way down. And that's shown by this long tool, this increasing blue line light blue line. And that's also shown by these blue numbers here. But it looks like the stop orders and the options traders and aggressive sellers are are winning so far. And now ES is down to the in SPX down to the 3950 SPX 3950 support level. Also the ES 3950 level. And then this LEM is the lower edge of the expected move for the week. So I thought this was a very clear setup for a short given the what just watching hero just waiting given in a few minutes watching hero watching the order flow and book map that I've just pointed out. And then one other confluence. Here's VIX. Let me zoom out just a little bit here. This is VIX for today. And notice the turn around about just after 10 a.m. VIX starts moving higher, making a series of higher lows. All right, let me let me check for questions in discord. Okay, it looks like looks like a conversation between JC and trader Pete. Alright, so I don't see anything from that conversation that I need to comment on. Alright, so let's take a look. And Pluto, I don't know what. What are you looking at here? What what instrument are you looking at? He's commenting on on hero. So I am looking at SPX. I'm looking at SPX. This is plus by right. So this is what I'm seeing. Alright, so if you're having an issue with with hero, you might want to want to contact spot gamma. Alright, let's take a look at some other setups. Yeah, just refresh try it. Okay, great. Alright, so let's take a look at some other setups here. And recall that AMD was was initially bullish, just based on the based on an increasing key gamma strike. And we'll notice notice in the morning here that this was was bullish, rising hero line. And let's go take a look at book map. We'll go to AMD. So there's the bullish move in the morning and then AMD finally gave in like, like the rest of the market and is moving lower. And notice the this is pretty typical for AMD the the order flow shown by all these pink dots here and you can you can see the the falling CVD can make AMD hard to read a CVD is falling a lot of the pink dots, even as prices increasing. And to me that just indicates the problem are the predominance of options traders hero driving price action. And then we can see the the strong correlation between options trades hedging for one price action and not so much with CVD on AMD like we like there usually is on the S&P 500. Alright, so that is that's AMD. And let's take a quick look at Amazon. And this was a another trade with AM confirmation that didn't last long. And let's go take a look at book map. There's Amazon strong rally in the morning. And then started to fade at the 96 level price passed through the 95 key gamma strike and the 94 hedgewall. And now continues lower. Let's go back and take a look at hero again. Not the the correlation between hedging flow and price action is not nearly as clear as AMD. Alright, the next one Google AM confirmation. And then there's a stronger correlation between options trades hedging flow and price action. Let's go take a look at at book map again. Take a look at Google sharp up movement the morning didn't last long. And then price has been moving lower. Again, both the key gamma strike and the hedge wall and play and notice the liquidity there at the 94 hedgewall than the liquidity at about 93 90 and was pulled. Alright, let's take a look at Microsoft and strong up trend this morning. Definitely confirmed by order flow cumulative volume delta. You can see all the all the green dots in here. Quick run up to the 259 level. And let's go take a look at hero. And this is one of the stronger cleaner signals for hero, especially in the morning. If you're looking for a trending stock, let's see what traders were doing. So they were selling puts and buying calls calls shown by the orange line rising calls rising orange line means that traders were buying calls and rising blue line means they were selling puts both are positive delta positions. Let's go back and take a look at book map. Let's zoom out so we can see again the strong correlation between hedging flow and price action. Go back to book map and just like everything else that reverse lower sometime mid morning to noon and now price may be heading back down to this 255 hedgewall level and the liquidity there. Let's just take a look at Nvidia. So again, remember Nvidia was the assumption was initially bullish. And I think I traded. I think JEC traded that. Yeah, JEC, I thought it would have been a Microsoft today. Given that strong correlation. But anyway, here's Nvidia and let's take a look at Hero for Nvidia and really confirming the downtrend. So remember my process. I have a thesis but I always confirm it with Hero and Hero and order flow. So Hero hedging flow options trades have been negative delta market makers are selling stock to hedge their delta exposure as traders sell calls and buy puts. So yeah, in Nvidia there was a short up move in the morning but the overall the trend has been down today. So that's Nvidia. Let's take a look at QQQ and the move in Hero this morning set up a down move and it looks like traders started fading the move lower about 11 a.m. and price continues lower. So pretty difficult to read here in QQQ. Let's go to Tesla and a couple of a couple of things I want to point out in Tesla. Let's go to let's go to equity hub and actually here while we're looking at AMD, I want to point out this is the history showing the history 10 day history for these spot gamma key daily levels and recall my quick look at the key gamma strike indicated that that key gamma strike increased for AMD and Nvidia. So if I wanted to do further research I would go in here to the to equity hub and see there's the increase in key the key gamma strike from yesterday to today. So it's been at 80 for quite a while increased to 85 also the increase in the hedgewall from 81 to 83 and then also the increase in the put wall I'm sorry the call wall from 85 to 90. So I take all of that as bullish. Alright so that's a look at AMD and we saw that initially there was a good bullish set up in AMD but it turned with the rest of the market. Now let's take a look at Tesla and we'll see a different story here. So notice Tesla and I think we talked I think I talked about this yesterday. The key gamma strike has been at 200 for quite a while traders have failed to move it higher so now it has finally dropped down to 180. So from 200 yesterday to 180 today and also the hedgewall shifted lower from 193 to 190 and then the put wall shifted lower and it has gradually shifted lower from 195 10 days ago to 170 today. So a gradual shift lower so all of that is definitely bearish for Tesla. Alright let's go take a look at hero now for Tesla and we could see that order flow is definitely I mean hedging flow is definitely confirming this move lower other than the initial move higher in the morning. Since then hedging flow has been setting up shorts all the way down. So traders are selling calls and buying puts. The following orange line shows that traders are selling calls and the falling blue line shows that they are buying puts and both are negative delta positions. So let's go take a look at book map. Take a look at Tesla. Alright so for Nvidia it looks like the 235 hedgewall high liquidity level is the next target below. Take a look at Tesla. There's the initial run up and then Tesla moving lower down to the past the 180 T gamma strike and again remember that drop down from 200 to 180 today. Move through that liquidity seller buyers absorb the sellers. It did a retest of the 180 level and now headed down to the 175 level. It looks like buyers are coming in and watch what options traders are doing. Let's go back to hero. Let's zoom in and if you're looking for another short opportunity you know I would look for this hero line to start to dip lower and also confirm that with order flow and book map. Let's just see if CVD provides any clues and CVD cumulative volume delta has been been negative all day and let's just do a quick check of the S&P 500. So so far this cluster of levels here this lower edge of the expected move ES 3950 and SPX 3950 so far holding as support. Alright so JEC notes a sharp hero increase in spy and let's go back and take a look at hero. Let's look at the S&P 500 spy and SPX. Yeah there's that sharp increase in hero so and this is pretty typical and what has been happening the last few days is traders are selling highs and buying lows options traders and often with zero DTE options. Let's just change this. We'll take a look at this is the next expiration only so you can see the zero DTE options traders came in just before 130 just before I started taking positive delta trades and then prices slowly responding and again this is pretty typical they will pick their levels and in the case today this was the this cluster of levels at ES 3950, SPX 3950 and then the lower edge of the expected move. So this looks like a big move but it's I guess in recent days it is somewhat about a maybe a 70 point move something like that. Let's see what was this high here just below 40-20 down to 3950 or so so about a 70 point move lower. Again almost doubling that move after the jobless claims and so far traders continue sell stops continue although the iceberg orders are in there iceberg large traders with their iceberg orders of buying but there's still plenty of sell stops fueling this move down to down to these levels. So if you're interested in trading this I would you know certainly watch hero let's go back to the total signal now so this is all explorations that we're looking at and it same thing is zero DTE let's take a look at both at the same time so here at this point it looks like zero DTE is dominating. Okay that's all I have for today my time is up interesting day and we saw some good setups and the ones that I liked especially were the S&P 500 and also Tesla. So anyway again thanks for your questions and comments thanks for watching and I will see you tomorrow and remember the employment report at 8 30 a.m. Eastern time and we'll talk about that tomorrow afternoon so thanks again and I will see you tomorrow.


Well, uh, that is snow. So what am I doing? It's early, driving up Gonella Pass. Um, I don't know if I'm going to be able to do this run. I'm trying to get up here, but you got to be smart. Don't, you know, you just got to be smart. I'm in 2002 Toyota with good tires, very good tires, but not snow tires. And, um, it's not coming down too hard yet, but you don't want to get up to a spot that you can't get back down. Capiche? So it is right now 34 degrees. So it's basically, you know, just above freezing. Um, I got to make a call and I'm just going to think about it here. Nothing I'm going to keep going. Just take it easy. It's not, you know, it's not coming down hard. It's not sticking to the road. If it was 27 degrees, so basically five, six degrees colder, it would be sticking to the road and that would, uh, that would be an issue. But, uh, I think we're, I think we're okay. It's a little reassuring. I'm not the only crazy person up here. All right. Let's get dressed up here. Oh, man. Going for a run in the snow. Mountain is somewhere in that direction. I don't want to mess with moose. See it. So you really don't want to mess with moose. They can mess you up. If there's babies around, they do not like that, but that was, uh, that was not a huge one. So you couldn't see it really. It was, it was in the, in these willows and you just, uh, you just couldn't see it, but that was pretty cool. Pretty cool. All right. Let's keep going. I found a foot of snow up here. I don't know if I'm going to make it to the top, folks. I did find the trail again, so that's good. There's a nice big Karen. That's a good sight to see. Okay. Let's just see. It's about a hundred feet of visibility. So it's not bad. Oh yeah. We're on the trail again. I was off trail for maybe about five minutes, but we got it. Well, this is the top. Not much of a view up here. 14,088 feet. Uh, basically, uh, the phone is going to probably die because it's so cold up here. So it's, it's going to, it's too cold for the phone to work. So this is the last filming for, uh, this 14er. By the way, this is Mount Beerstadt, a front range 14er.  Made it up. Uh, you can't see a dang thing. I'm trudging through about, uh, I'd say eight to 12 inches of snow. And they're supposed to get, whoa, six more inches of snow, uh, tonight. So this is a good day to do it. Time to go down, see you at the car because the phone's about to die. Well, that was interesting. Oh, white out on top. Very muddy at the bottom. Past about 20 people, so it's not too late to come up here and enjoy the high country. That was good. First snow run of the year. I definitely, and yesterday's vlog, go check it out, was all about how I bought some, uh, used hokas off of Facebook marketplace. Well, I have my eyes set on this, uh, Solomon something. Solomon shoes, they're basically designed for winter running or really wet conditions because the gator is built into the shoe. I'll put a snapshot of it up now. That's the goal. I want that shoe 250 bucks. Gotta save the money. Alright, time to go to work.