many, many clusters popping up in the customer's landscape. So they started to have tens or hundreds of clusters, as I mentioned. And one of the key elements of a containerized journey is the containers and basically the images from which you run those containers. So as you guys probably know, a container is basically the instantiation of what we call the container image. And that image needs to be stored somewhere, which is the registry. And as you start to have those tens or hundreds of clusters, you want to have something that is your centrally trusted registry for your content. And that's basically what the registry, what Quay provides. It's an advanced registry that provides features like geo-replication and mirroring, security scanning, image builds. And the way you can envision it is that you can have a Quay instance that ships images or centrally manages the images that are going to be used by your tens or hundreds of clusters. And because of those geo-replication capabilities, you can have mirrors that are deployed close to your, I would say, geos. And then you can optimize the traffic. So you can have central images that are mirrored to local Quay registries, of course, in an automated way. And then you can optimize the traffic between your regional open shift clusters and that regional Quay registry that you have there. But you are still optimizing the management of your registries.  So basically, you can have disaster recovery scenarios or architectures. And that's also something that you probably want to envision when you have critical workloads that are running on your open shift clusters. So of course, Quay can work with open shift and any other, I would say, consumerized solutions. So it's a fully standardized registry that is compliant to the OCI format and such things. Yeah, we have a question. So thank you for the explanation. And my apologies for throwing that out there. I know that this is one of those things that sort of understanding some of these building blocks is what we're about today. Let's go ahead and dig into it. So where do you want to go from here? Yeah, so from here, I would say, now that we have a better, I would say, understanding of the overall architecture or architecture of the platform, let's see how we can get access to open shift, how it gets installed, how it gets administrated in terms of content. So yeah, that's going to be our first take on the platform. And then afterwards, we're going to switch our hats and then see from a developer perspective what are the services that we provide and how it can be also used. OK, so first thing, how do we get access? We now know what open shift is. We want to try it. We want to experiment with it. How do we do that? So if you go to try.openshift.com, you're going to end up on this page. And it shows you that you have at least three starting points where you can start digging into the platform. There's what we call the developer sandbox. And it's basically a 30 days free trial that we host for you. You just have to go there, request an access, and you are going to get an open shift environment that is created for you. Of course, it's going to have some limitations in terms of resources. We're not going to provide you 100 nodes free of charge for 30 days. Well, you probably don't need that if what you're doing is looking for a developer sandbox. Exactly. So this is a full-fledged open shift with all the latest innovations that we provide in there. It's not restricted, I would say, in terms of content or in terms of experience. It's just that it's limited in time. So it's 30 days to try and see if that's something that you want to go further with. You can start as managed services with your cloud accounts. So for instance, if you have access to AWS or Google, you can order an open shift as a managed service using your credentials. Or if you want to do things, I would say, more traditionally, you can try to self-host open shift in your environment, whether it be on the cloud or on your data center. And that's going to be the third option that you have here. Right. So there are some important options. And I know the managed services option is becoming very, very popular at this point. Yeah, correct. So I've seen the numbers. And it's definitely something that is getting much more used by the customers because, obviously, they want to concentrate on providing the end services and not spending time managing platforms and such things. Right. But of course, as always, we have those customers who maybe have unique security requirements, certain kinds of compliance requirements, or they just have that sort of build it yourself mentality sometimes, whatever the case may be. There is still that option to do it. But it sure does seem like managed services is becoming more and more popular for the exact reason you say is that it accelerates the process and gets you where you need to be without taking on a lot of additional overhead, which for many organizations, they might not be willing or able to take on. Yeah, exactly. And plus you get the benefit of having the engineering and the support, the SREs that come from Red Hat and the jointly managed teams. So that's also something very, I would say, valuable for the customers because you get hands-on experience from day one. And it's not something that you have to acquire or recruit some Kubernetes experts that are basically provided by the service itself. Right. So if I might, we did have some technical difficulties earlier where we were not necessarily streaming everywhere. We seem to have addressed some of those. And so maybe some folks are joining us. I just wanted to say very briefly today, we are rewinding, coming out of the deep dive, and really just talking about what is OpenShift and getting some background from Jafar on the fundamentals of what OpenShift is, what comprises it, and what it's about from both an administrator perspective and also from a developer perspective. So Jafar, back to you. I just wanted to put in a little bit of an explanation there for the folks who might have been joining us late. Yeah, sure. Thanks. So I'm going to go and hit that starter trial for the self-managed part just to give you an overview of how you can do things. And so basically, you see that there are a lot of supported architectures. You can deploy on bare metal, Z-Power, OpenStar, Crab, V-Sphere, or just any agnostic infrastructure, which is what we refer to as the UPI, user provision platform. And depending on the path that you choose, you're going to have guided instructions to do the installation. So let's see, for instance, this one. So you have the two paths which are the installer provision, UFRA. So basically, if we choose the case of V-Sphere, we are going to provision everything that you need to have a fully running OpenShift cluster with minimal involvement from the person that is doing the installation. If you choose the other path, you're going to have a little bit more work to do, but still, it's not going to be very complex. So you have an installer, which is basically a CLI that you can use. And the command that you need is basically OpenShift install create cluster. And that's going to pop up with some questions regarding the credentials that you need, the domain that you are going to install, the cluster name, the type of platform that you want to install it on, et cetera. And in a matter of answering five to 10 questions, you're going to have the process kicked off. And after 45 minutes, you are able to have a running OpenShift cluster on your target architecture. Now, we understand that some people may want a more user-friendly experience in terms of how they can do the installation. And that's why we provided what we call the assisted installer, which is a UI-driven way to install OpenShift. And so we have done a previous show last year on how to install a single-load OpenShift cluster with this AI being the assisted installer. And so here, I'm just going to go and hit Create Cluster. It's going to ask me for some parameters where I want to deploy the platform or the version. And afterwards, all I have to do is, so I can say, I want to add hosts. And the way it works is you are going to generate either a full ISO or a minimal ISO image that you are going to load on your target environment. So this is mostly directed at bare-metal installations. And it's going to generate an ISO that you push on your bare-metal instances. And the node on which you run the ISO is going to report back to the UI and get configured as a master or a node, for instance. So it's a very easy way to do the installation. And I really love the way that we are making it even easier for our customers to deploy OpenShift on their target environments. So that's basically what I wanted to cover regarding installation. So you have the CLI, which was the traditional way of doing the OpenShift installation. And now you have also that Assistant Installer. So it's here in Tech Preview, but we are going to release it as basically we have the traditional workflow where we have Dev Preview, Tech Preview, and then it goes into GA. OK, so that was it in terms of installation. So what do we have when we have a running OpenShift platform? So now I'm logged in into a cluster. We can see, let's have a look at the version. So this is something that I have just provisioned. And it's a 4825 cluster. And one of the very nice features that we added with OpenShift 4 is that you have the ability to automatically update the cluster. It's one of the core reasons why we decided to adopt what we call operators. And let me actually pose on that. Yes. Yeah, because it's the third time I have mentioned operators and we still maybe don't know what that is. So let's pose and see. Well, for those of us who are of a certain vintage, we hear operator and we think of a person. Exactly, yeah. And once you enter OpenShift world, you've got to understand that you're going to hear the word operator over and over and over again. And we are not talking about an operator as a person. It is instead, Jafar. Yeah, so I actually, in the early days of trying to enable people on what operators are in terms of Kubernetes landscape, I had a funny picture where it was actually a gif where there was a guy getting into a box, like entering into a box. And it's basically, if you look at the traditional way of doing things, you have the operators, which are the knowledgeable guys that understand how to install and manage your Java servers, your databases, whatever specific proprietary solution that you have. They understand how they configure it for HA. They understand how to manage upgrades. They understand how to recover from failures and such things. And basically, you really need that knowledge in order to be able to provide a 99.999 person of service availability, for instance, or something like that. So when you switch to the containerized space, you have many things that are much easier to do. It's easier to package your content, your application. It's easier to run it. Kubernetes can do basic things like, OK, the application has been shut down, meaning the container has stopped. I can restart it and redeploy it somewhere else. But what if your application needs some very specific order in terms of how the components need to be started? Or if you want to do an upgrade and there are some things that need to happen in a very controlled way? So Kubernetes does not understand how to manage a, say, for instance, a couch base database, which is one of the operator-based databases that we provide in the OpenShift catalog, thanks to the work that we have done with our partner. Kubernetes does not have that knowledge. It only knows that there's a pod. The pod can be shut down or started. And that's it. So basically, the operator, in terms of container architecture, is a side companion to your solution that really has that embedded knowledge that has been encoded in there by the people who better understand that solution. So let's take the couch-based operator, for instance. Couch-based have implemented the way installation should be done, the way scaling should be done, the way data propagation should be done in terms of automatically distributing the data across the different nodes when you have, for example, a new node that joins or something like that. They have implemented things like automatic recovery. Say, for instance, you have a cluster that is comprised of three nodes in terms of your database, and one of the nodes has an issue. So the operator has that built-in knowledge to say, OK. First, I need to start a new instance, and then I need to do those specific actions, which are probably something that a traditional operator would have known, except that you need the guy to do it. Now the knowledge is embedded within a side container that we call the operator that is shipped with the solution and does all of that magic in the background. So basically, it's going to monitor the solution. It's going to adjust whatever needs to be adjusted to make sure it runs. And because we wanted to have such high level of automation and resilience or reliability with the platform services that were shipped within OpenShift, we decided to fully embrace that operator model with OpenShift 4. So just for the background, the operator model has been created by some people that we have acquired through the tectonic acquisition, through the CoreOS brand, basically. And now, of course, it's become a much broader standard, and everybody in the Kubernetes landscape speaks about operators, but it was not something that was existing before, I think, 2016 or something like that. And because we have those engineers and we had early on that understanding of why operators are such valuable for Kubernetes, we created operators for all the infrastructure components of the platform. So for instance, we said that we have a registry. The registry is managed by an operator. We have the HCD services. They have their own operator. We have something like the Kube API operator, something that manages the underlying infrastructure, like the nodes, how they get configured, how they get updated, and such things. So I think we have over 37 operators just for the platform content itself. And again, the reason why we did that is it's because it provides you with so much built-in automation that you can delegate to the operator and then have everything happen magically when you hit that update button here. So with the previous version, we didn't have that. It was a set of Ansible scripts that you had to run manually and cross fingers and hope that everything went fine. Now I'd say it's a smoother experience. You can choose between different versions. So something that we heard from our customers is that they wanted to be able to upgrade, even maybe try the leading edge versions or what we call release candidate versions before we even released the GA for a specific version because they want to accelerate their testing or their validation process. So basically they said, we don't want to wait for you to release a specific version before starting to do our sandbox tests and see if we can upgrade to that specific version. We want to have a little earlier access and be able to do that on the fly. So we started to publish first. We created those candidate channels for the updates, which basically provide you with, I think, weekly updates for OpenShift in terms of patches and such things. And we also provide nightly builds for the installers for the components, if the customers want to go and download them and install them. So it's, I would say, a much more iterative process and you have access to those features much easier. Well, one of the things that's interesting, Jafar, is if you think about IT historically, there's generally the, if it works, don't mess with it. If it's not broke, don't fix it. And there's not always that eagerness to move on to the latest and greatest in the bleeding edge. And I think that's how things were for a long time. It seems to me that we really see a very different kind of behavior in the world of OpenShift, where there's that real eagerness for the next thing that's coming out and the new features and so on. And that it really is almost turning things on its head, where instead of that reluctance to go with the latest and greatest and if it broke, don't fix it. There's the sort of behavior that you're describing where they're saying, no, we want to see it before it's even out so that we can plan for it, so that we can prepare for it so that when it does come out, we're ready to leverage it and hit the ground running. Does that seem like a fair assessment? Yeah, so there's, I would say, two sides of that cone, which is, so if you look at the Kubernetes iterations or release frequencies, it's a new release every three months. And nobody in the traditional IT enterprise level would even think of upgrading their core systems every three months. So that's a very challenging way because they have validation processes and such things. And only if they are 100% sure that the upgrade is not gonna affect their running workloads, they are going to think about the possibility to do it and not necessarily do it. So that's basically what we wanted to enable is to have that shifting in the mentality that yes, we can do things in a much more agile way. We don't have to wait 18 months to upgrade to the last version and wait for four versions of patches before we are confident in something that has been released. Of course, not everyone is gonna be able to upgrade their platform every three or every six months. So we still have a lot of customers, of course, that have, they are regulated. They have, I would say, obligations that force them to have a very rigid validation process and they cannot upgrade whenever they want. So of course there are customers who are still doing that once a year or something like that, but there are also customers who are much more into what you described and they upgrade every six months or even faster for some environments where they feel that they can have that flexibility for their end users. So again, it really depends on the types of workloads and the types of regulations that control your platform, but what we did is actually we gave them the ability to do it, which it's a start and depending on how flexible they are, they can benefit from that feature. I know that that's something that I do whenever there's an upgrade, I just go there and hit upgrade on my clusters. Usually it works fine. It takes 45 to one hour to fix. When it doesn't work, I go back to engineering and there's been some issues because that's also... Surely not, oh, surely. Why we do that and basically that helps us make fixes before we go into the GA. So if we have customers who are experimenting with the candidate releases and they face issues and they submit the fixes, that's a way for us to gain some time and be able to fix the issues before they land into the GA versions. Yep. Okay, so that was again the explanation of the core change that happened with the operators in the platform and that's also what makes it easier for us to basically update the platform. Some of the, I would say, benefits also of doing these changes is we make it even easier to actually manage or administrate the platform through the UI. So here, as you can see, I'm logged in as an administrator and if we look at some things like, oh, we have the ability to automatically add new identity providers from the UI. I can say, for instance, I want to configure GitHub or add that configuration or just upload a new HC password and the operator that is responsible for this section here which is basically in OpenShift is going to see that there's a change request, which is I want to add a new identity provider and it's going to automatically reconfigure that specific operator and it's going to provide me with an option to identify or to authenticate with that identity provider. So if you think about the way things were done before, you'd have to go to a configuration file, you'd have to edit the configuration file manually and then you'd have to restart the services on all of the OpenShift components to make sure that the change that you have submitted has happened. Well, that's the way we did things before. Now with the operators, you just make the changes in here. The operator does what we call the reconciliation. It's basically it's monitoring the desired state versus what it has in its current configuration and it's going to say, oh, okay, so you want me to add a new identity provider? Okay, let's do that. And it's going to reconfigure the authentication component automatically in the background. So that's basically how we changed the way we administrate the platform. It's really to try to delegate things as much as possible to the underlying operators that are responsible for a specific area that they are managing. So let's continue with that operator story and administration and let's have a look at what we have in this current cluster. So I see that I have three masters, so that's a requirement because we want to have three HCDs and so that's a traditional architecture in communities. And we have two workers which are, so this is currently deployed on AWS and I have basically two nodes. And as an administrator, I'm often responsible for managing the infrastructure. So people ask for more capacity and I need to provide that infrastructure. That means in a traditional way, I'm going to deploy new operating systems. I'm going to configure them, et cetera. And this is something that we also wanted to make much easier for our customers. So we have what we call this notion of machine sets and just basically it's a grouping of machines or nodes. And we have three zones in here. We have EU, West A, West B and West C, but we see that one of them has no machines yet because if you remember, we had two workers which are the two ones we can see here. Say now that as an administrator, I want to provide more capacity for my users. I'm just going to go and hit the edit machine count and now certainly what's going to happen is the operator that is responsible for managing the infrastructure. Because if you remember our opening architecture, we said that with OpenShift 4, we are now managing the underlying OS also. So what it's going to do here is that it's going to kick off the provisioning of a new machine on AWS and it's going to configure it as a new node, meaning it's going to deploy, generate the certificates, communicate with the CUBE API server to make sure that it's accepted as a new node, et cetera. And once the provisioning is done, I'm going to see it appear as a new node in here. So something that used to take a long manual process for an administrator is now fully automated and that's something that we provide for all of the target platforms that support the API installation. So very easy and that's basically what we want to provide for the OpenShift administrators, make it as easy as possible to automate everything. Of course, things that can be done here through the UI are all YAML driven. So anything that we do is basically, the UI is just a front end for what happens when we change YAML files. And basically, you can do a getups approach if you wanted to configure your clusters and push changes. And that's actually what we do when we are using ACM for instance. You can have a set of centrally defined standard configurations like this is the LDAP configuration that I want to push. These are the authorized registries, et cetera, et cetera. So everything you want to configure. And whenever you create a new cluster, you can have ACM push those configurations as YAML files to the target cluster and apply them. And it's gonna be automatically picked up by the operators. They're gonna do what they have to do and you're gonna have your cluster end up in the target state that you asked for. So much easier to administrate than having to create scripts where you basically say, okay, you have to do this and that and this and that, et cetera. So yeah, that's what I would say was really groundbreaking with the OpenSheet 4 architecture and why it's such easier to administrate than, I would say a traditional Kubernetes platform first and the previous version of OpenSheet Austria. So as we're coming up here to the top of the hour, we have covered a lot of ground and yet I know there's more ground that we had hoped to cover. Can you maybe share a little bit about sort of the developer perspective before we wrap up or do we need to cut that to another show? Yeah, sure. So I think we're gonna have to maybe wait for an upcoming show for that part. And again, it's not a problem because as we said, we want to kick off those new shows with new ways of doing, coming from the ground up and going step by step. And so as you can see here, here we have the worker which is starting to appear, which means that the automation has correctly happened. One of the things that I wanted to speak about is the operator hub. We spoke about the core operators that manage the platform itself, but as an administrator, you are also responsible for providing content to your end users. And as you can see here, we have over 500 items that appear in the catalog and this is comprised of some solutions that are provided by Red Hat. So again, we have our solutions. For instance, the ACM or ACS, which are the multi cluster and the security solutions are both deployable as operators, meaning that you can install them very easily on the platform. But we have also some components that are part of OpenShift, like I believe we have the login. So one of the decisions we made with OpenShift 4 is that we provide a basic installation that provides you with, I would say, the minimal footprint that you need. But if you wanted to configure additional solutions with things like login, because you don't have your own login stack or for whatever reasons you want to install additional component, it's gonna be done through operators. And actually, let me do that because I wanted to show you how to do that for a developer oriented solution. So now as an administrator, I want to provide OpenShift pipelines as a service to my users. And OpenShift pipelines is basically our downstream version of the Tecton project. Tecton, which is the Kubernetes native CI CD or we have GitOps here, which is our distribution for Argo CD. And just a quick reminder, if people are interested in the subject of Tecton, check one of our earlier episodes. I don't remember which one, but we actually had a dedicated episode talking about pipelines and Tecton. So check it out. We do dive deeper into that particular subject. Correct. And so, yeah, as an admin, we said the question here is, how do I configure the platform? How do I manage the content and how do I add or remove services from the platform? And if you look at the left pane here, we currently don't see a pipeline section. We don't have that capability enabled yet on the platform. And we are going to do it by installing the operator, actually. So when you have an operator, you are faced with some options that you can. So you can use the preview channel or you can use the stable one. And in this case, it's going to be installed for all the namespaces. And basically just by enabling the operator, it's gonna install all the dependencies and in a few second minutes, maybe I'm gonna have the pipeline service running and available on the platform. So I wanted to kick off the installation and now we can switch back to the developer perspective, which is, so again, from the OpenShift UI, you have two perspectives. The first one was the admin and the second one is the developer one here. So what I'm gonna do is I'm going to create a new project. And actually, no, let's switch to this perspective. And what I can do from this perspective is I can deploy from different sources. I can choose to deploy from Git, which is what we're going to do. I can deploy from a Docker file, for instance, but I can even upload a jar file directly into my UI and that's a nice feature that we can show maybe in one of the upcoming shows. It's basically just drag and drop your jar file on the OpenShift console and it's gonna create everything that you need. So let's go ahead and choose a Git repo or no, let's go back and choose the samples. And just for the record, you see now that we have the pipeline section that has been added, which means that just by enabling the operator on the platform as an administrator, I now, as a developer, see that the service is available to me. So what I'm gonna do here is I'm gonna hit that basic Node.js option and it's going to deploy a new application for me. So what happens in the background is OpenShift is going to kick off the build process. It's going to fetch the source code from the repository. It's going to trigger the build for me and as soon as I have my image that is ready, I can then have the application running on the developer perspective, which is this one here. So because we have added the pipeline feature here, I'm gonna go ahead and right click on my developer perspective, which is what you see here and I'm gonna say create from Git. So this is a sample repo that I have for a basic Node.js app. And one of the interesting things here is that I can say, please generate a basic pipeline for me to kick off my application. And I want to create an application group called. So this is going to kick off the build for my application, but at the same time, I now have a pipeline that is being executed in instead of just a simple build that we do with OpenShift. So the pipeline is now running. We have a few steps here, which are I'm gonna fetch the repo, I'm gonna build the image and then I'm gonna deploy it on the platform. So very easy to get started with the platform and for the earlier application, we already have the Node.js starter application that is deployed. So yeah, very easy for me as a developer to get started with the platform. The nice thing is that I also have monitoring capabilities for my workloads. I can see metrics, I can see alerts, et cetera, for my applications. I can configure the UI if I wanted. So for instance, I want to add something that is called deployments because I don't see it in the UI here. So I'm just gonna go and look for deployment here. I'm gonna say add to navigation and now I have customized my developer console to my liking and I have the deployments that are accessible from this circuit. So really easy to consume and deploy continuous applications on the platform. And yes, basically I have hundreds of services that I can use from the catalog that we provide. As you saw, for instance, if I wanted to deploy, yeah, I need to enable them first as an admin to make sure that they can be deployed. But we mentioned things like databases, for instance. Databases, for instance. You see here that we have 60 items that can be deployed. Some of them are certified operators. Some of them are community operators. And oftentimes you have the two versions that can exist. You can have the certified version by the third party provider or the community addition of it if you want to experiment with it before going into the buying process. Right, this is a commercial option. Yeah, exactly. So yeah, that's, I would say, a very convenient way of configuring the services from an admin standpoint. The goal here is basically provide a cloud-like experience.  Then as a developer, you just click instantiate the service and can consume it in your environment. That's exactly- Well, it works for both administrators and developers in this sense, because on the one hand, it's not complete anarchy. The administrator has to say, well, okay, here are the components in the catalog that we will make available. Exactly. And they have the ability to do that. And it's, like you say, it's sort of that cloud-like experience of, okay, I have enabled that particular capability. And now all of the developers automatically have that capability and they can choose among the capabilities that have been approved. And there is some degree of governance, but there's also the benefit of having this huge catalog that can be enabled very, very easily. Exactly, yeah. You saw how much time it took to enable the pipeline feature. I just hit the install operator then less than a minute afterwards, I had the service enabled on the platform. And I really think that that's what we provide in terms of user experience for both the administrator and the developer, which is- It certainly has the potential to really accelerate projects because of exactly what you just showed is that it doesn't become a huge operation to say, well, okay, I wanna enable pipelines, for example. It becomes something that there's agreement that it's needed. The simple step that's taken is by the administration is taken and all of the developers immediately have access to that new capability. It really is very transformational to use an overused term, but it is. Yeah, that's a fully agree. And that's the intent is basically to make that as much efficient as possible for our customers so they can focus on their core businesses instead of focusing on building platforms, which is our job and our responsibility, I would say. Indeed. All right, well, we are a bit over time, but I think it was time well spent. So thank you, Jafar, for the walkthrough here on OpenShift. And I hope everybody found this as informative as I did. There's a lot here to uncover. Please do like, subscribe, and share. We're here regularly on Wednesdays. We are going to be changing our schedule a bit. We have previously been a mostly weekly, occasionally missing weeks. We're now going to be going more officially to a bi-weekly schedule. And we hope that you'll remain interested, all of you regular watchers. Our next show will be on February 2nd. And we're looking forward to bringing a lot more information about OpenShift, about containers, about Kubernetes, about all of these things and the things that touched them this year in 2022. So please do like, subscribe, share, look for our next episode. And again, thank you very much, Jafar, for a really great walkthrough on OpenShift. Thank you very much. Thanks, Randy. And we hope to see you soon. I haven't seen the chat, but I don't know if we have had questions. I think we covered, we had a few.  So I think we're good. Great. Well, thank you everybody. Thank you everyone. Have a great day wherever you are. Bye.


Thank you for tuning in to Davis Media Access TV. I'm Lynn Weaver and our topic today is to learn more about our immune system and the brain. New evidence shows that the immune system and the brain are in direct connection with one another and they also impact one another as we go along. And this new understanding will hopefully result in a new understanding of diseases such as multiple sclerosis or Alzheimer or schizophrenia. And to learn more about how they occur and hopefully find cures for them. We all know that when our immune system is not functioning as it should, we all get sick but we don't quite know why. So here to help us to extrapolate all these complexities is my guest, Dr. Kimberly McAllister. Thank you so much for being here, taking the time to be with us. Dr. McAllister is an outstanding scientist of international reputation and has been recognized with a long list of very prestigious awards. She is, and I have to read because she has many title, a professor in the UC Davis departments of neurology in the School of Medicine and neurobiology, physiology and behavior in the College of Biological Sciences. And she's also the director of the Center for Neuroscience. I am. Wow. Thank you. Thank you for the opportunity to be here. Well, remember we're all lay people, so none of those complicated sentences. You mean like the list of the departmental names, right? Exactly. I read in one of your many bios that you love puzzles. I do. And is the brain a complicated enough puzzle for you? Oh, yes. Yes. You know, the brain is the most complicated thing in our entire universe and in anything that we can comprehend.  It's exciting. It's what makes us who we are, but we don't know very much about it. Well, that's interesting. Is there any particular aspect of the puzzle that you are interested in? I know you're interested in the immunity and immune system, but is there anything that first fascinated you? Yes. It's just a fundamental curiosity about what makes us who we are. Yes. The fact that in development our brains are nothing and in little babies in the womb and then they grow, the brain grows this very complicated structure. It makes all these connections and then it allows us to develop and become who we are. Each has individuals and it develops differently. And one of the most amazing aspects of brain development is that it's not just our genes that impact our brain development. It's our experiences. Fascinating. Fascinating. Well, we all want to know what is the immune system and what does it do, right? Well, that's also a complicated question, but we all have a sense for what our immune system is, right? We know that we need our immune system to fight off infection. And so our bodies have lots of different ways to do that. They're barriers, they're different cell types. And generally what happens is that when we have a cut, when our barriers are breached, we have a whole series of cascaded events that happens that causes cells to come into that site. You have some inflammation, which we all know, it's where it gets red and warm to the touch. But over time, you end up healing that wound. And our immune system is absolutely critical for that. We also have aspects of our immune system that fights off viral infection and bacterial infection in science. And I'm going to get back to that in just a moment because that's really very interesting. Now, tell me why do neuroscientists like yourself care about our immune system? Right. What's interesting is that when you're trained to become a neuroscientist, somebody that studies the brain, you learn so much about brain anatomy and about how the different cells in the brain work and how it's all connected. And that's difficult enough. But only recently have we started to realize that the brain isn't just completely separated from the rest of the body. In fact, it's influenced by it. And that sounds really silly from the outside of neuroscience that we didn't realize that. But in our brains, we have what's called a blood-brain barrier. And so there's a series of structures that surround your brain that prevents infections in the body from entering the brain. And so that allows us to function even if we get injured in elsewhere in our bodies. Even if we have peripheral information. That's right. And so for many, many years, it was thought that the immune system didn't interact with the brain because of that barrier. But about 20 years ago, there was one of my scientific idols, Carla Schatz, who's at Stanford. And she discovered that immune molecules are actually present on cells in the brain. And we've since gone on to discover that some of the signals from our immune system, from immune activation during infection, that they can cross the brain barrier during brain development and alter the development of our brains. And one example of this is you're studying a very important case, and that would be susceptible pregnant mothers who are susceptible to inflammation, viral inflammation, and can affect how the child, the unborn child's brain develops. And that can lead to what? That's right. So it's been known for a number of years that exposure to a wide range of viruses, including influenza, increases the incidence of a number of psychiatric disorders in offspring. And so one of the first ways that this was realized was by looking to see whether there were increases in the rates of autism or schizophrenia after pandemics. Oh, yes. And so you have to look at numbers of years later after the pandemic because it's the exposure of the fetus in the womb to something about those maternal infections that then was causing an increase in the incidence of a wide range of psychiatric illnesses. And so this has been studied for the most part by schizophrenia and autism, but there are also links to depression and to neurodegenerative diseases like Alzheimer's disease. So if I understand correctly what some of these dysfunctions, if you like, like depression, for example, malfunction, I should say, are not necessarily genetic. Well, so we know that a number of these diseases have both genetic components and environmental components. So we know, for instance, that autism and schizophrenia both are highly heritable, but there is also a strong role for the environment. And epidemiology or studies that look at the incidence of disease have really shown this strong link between the maternal infection and these diseases. But we don't know why. And so this discovery that immune molecules are present in the brain gave us the idea that maybe the mom's immune response, all of those signals and chemicals that get released in her body to fight off infection, that those might cross into the brain of the baby as it's developing and alter the structure of cells in the brain and the development of that brain that could then predispose the offspring to getting to getting these different diseases. Fascinating. Also, it's scary. It's very scary.  Yes. But so one of the most important things in this field is to see if we can understand why some pregnancies are susceptible and most other pregnancies are resilient. Because if we can determine and identify which ones are susceptible, then we can treat the moms so that their offspring don't have that in the stress. Absolutely. And that is wonderful. Let's... There's something, I'm going to ask you an in-n-n question, and there's... Do other people who don't have immune systems, are these the babies who are in bubbles and in those bells that cannot live in oxygen like we do? Well, so I'm not sure exactly what you're talking about, but there are definitely... I'm not surprised. No, but there... I mean, we hear about this, right? And I don't have direct experience with that, but there are many, many people that are born with different levels of intensity of autoimmune diseases. Some of them can't fight off any infections, right? And these are severe immunodeficiencies. I think that's probably what you're referring to. And these are kids that kind of have to be kept away from infection in this bubble that you're talking about. That's right. Yes. And it's known, so a lot of... There's not a lot of people with this, but for the group of people that have this, it is known that their brain development is a little bit different than is typical and that that can lead to some behavioral proclivities, but there are just differences in behaviors, right? I see. And a lot of these psychological diseases we call them, they're things that are advantageous to having them and they're other things that are not, right? And so just talking about them as negative is not... They're a part of all of our lives, pretty much, with the incidents. That's a very good point that you're making. Now, I often read that if your immune system is somehow impacted by disease, by a virus infection, you may, one, may have diminished memory, diminished capability of learning. Is that a scientific fact? So it's hard to study because humans are really variable and the things that we do in terms of what we're exposed to, whether we take medication, whether we have disease, whether we smoke, those things can actually change the integrity of our blood-brain barrier. And so for some people, this can have an effect on their ability to fight infection and if they get sicker and their blood-brain barrier allows for signals to come through, that can then actually alter memory, learning in memory, it can alter mood. And we're just beginning to understand how it does that. Oh. They're these little proteins that are on the surface of your cells that are important for cells in the brain to talk to each other. That's how information flows. You're not talking about the neurons. I'm talking to the neurons of the brain cells and the connections between the neurons are called synapses. Yes. Good. Yes. And they're these really incredible molecular machines that are made up of thousands of different proteins, but what we've discovered in my own lab and in others in the world is that immune molecules, so molecules that we thought only mediated the immune response in our bodies, they're actually found at these connections. And so if the blood-brain barrier is compromised in any way for a number of reasons, those immune signaling molecules that usually are kept out that just fight infection can then enter into the brain and alter information flow across neurons because of altering those immune proteins. How extraordinary. It's really remarkable, nobody was expecting this. I could listen to you for about, I don't know, a whole week without getting tired. But I do want to ask, you're the director of the Center for Neuroscience at UC Davis. It's a big responsibility and you oversee many labs and so on. What would you say is the overall goal? I know the overall goal is to find the truth, the scientific truth. Beyond that, there must be a human aspect. Oh, there is. I'm not saying that scientists are not human. Oh, no, no, no. Yeah, well, and especially neuroscientists, so we want to understand how the brain works and we want to understand how it works for a number of different reasons. Yes. We want to understand how it makes us who we are. We want to develop new treatments and therapies and cures even for the wide range of brain diseases that affect just about all of us in our families. And we want to develop the next generation technologies that are really changing the world. So artificial intelligence is something that we all hear about in machine learning. We even have it in our phones that we all use every day. Those algorithms that run that artificial intelligence are based on how we understand information transfer in the brain from 30 years ago. Now when we understand it's so much better, we're developing new algorithms that are really going to drive technology development. So the overall idea is that we want to understand how the brain works so that we can use that knowledge to improve people's lives. Oh, this is wonderful. I'm afraid our time is up. It went very, very quickly. Yeah. Dr. Kimberly McAllister, thank you so much for being here. And I hope that we'll have a sequel to this. And for all of you, thank you for watching. And if you've liked this program, you can go on to our website, DCTV, davismedia.org, and check out some of our other programs. We have very interesting topics and wonderful guests. So please do check us out. Thank you again from all of us here at Davies Media Access. See you next time.


Hi, everybody. So yeah, we're going to today talk about the network visibility. For those of you who attended our previous talk, this is the second in the series of the three talks we are presenting here on OpenStack operational visibility. So this particular talk focuses on the network visibility. And in the previous talk, we did present the overall idea of the theme of where we want to head to in terms of capturing the OpenStack operational monitoring and visibility. So this is the theme that we work with. So to begin with, in terms of the network visibility, where are we right now? What do we have right now? Probably for any user, any admin to go and figure out what's happening in your cluster, what's happening in your network cluster, what is the kind of network load that the various hosts and instance are going through, you may have to actually go through the various logs and various APIs and do a bunch of calculations. And it's a whole lot of complicated. And if something goes down or something goes bad, to troubleshoot, it's such a huge complicated task to go the logs and figure out what went wrong. And in terms of the topology, I think currently in Horizon, all we can see is just a bare minimum topology. So it's a huge daunting task to figure out how the network is performing or what's going on, if something, what are the hotspots, it's really a hard task. So it's a big headache. So where do we want to get to from this current, what do we have currently? So we want, like we said earlier in our first talk, we want to get to a stage where we have a really cool visualization tool and various data analysis tools out there which helps users to easily figure out the status of your network and otherwise, like compute and storage and everything. So we want to have cool interfaces and tools that easily shows you the current visibility of your infrastructure. And as part of this talk, we are going to present you some of these frameworks and also our whole architecture of where we want to head to. So this is our first, as a first step, we want to present you the visualization step and present you the whole picture of network. So I'll hand it over to the team now who are going to go into the further details of the talk. Excuse me, can you hear me? Okay, cool. So, okay, in regard to the network part, what exactly what we want to see, what we want to know about what's going on in the network in our cluster, we think that really depends on who you are, what's your role in this game.  And then based on that, you probably want to know what the hotspots in the cluster and that will help you to feel easier to define what you should take care of. And then on the upper level, you probably want to know how are you really using my cluster? Are they using it really heavily? Are they performing some heavy jobs? Are they generating huge traffic?  So the first thing you want to know would be the resource status in a real lifetime. And then based on that, you probably want to know the performance.  And on top of that, you might want to know once, for example, if you have some job going on and it's slowing down or it's just stopped, you probably want to know why, you probably want to get a track of what's going on in your virtual cluster. So we believe these three things are kind of three steps that we're going through. The first step will be data gathering and the second step will be data storage and statistics and the last step will be data analysis and visualization. So here we present you our architecture of the three step. On the left side is data gathering. We're going to expand it a little bit in the next slide. So we're doing the data gathering through a cylinder and as well as the log gathering agents. And then we store these data into both the salameter collector and the log collector. And here what we do is we also push the salameter data into the log collector so that we have a centralized database of what's going on. And then we push these data into the analysis so we get a better understanding as well as we use these data for later visualization. Okay, so on regard to the first step of data gathering we did some tweak in the salameter to get better information. So for now if you look at the salameter agents in the customized, in the non-customized open stack you can only get, regard to the network part you can only get the outgoing or incoming flow. Sorry, the outgoing coming packet or bytes of each machine. But that's far from enough if you wanna really know what's going on in the cluster. So what we do is here you can see in the graph that's a normal workflow of the traffic, right? Going from one machine to the switches and then to the destination machine. So what we get is we wanna get the end-to-end traffic. We want to get to know the VM to VM traffic flow of each VM's pairs. So for doing that we actually, we write it our own salameter agent which could get these in information and then we compare these information with the neutral database so that we actually get the ultimate virtual machine to virtual machine traffic. And regard to the log collection we, besides the open stack logs for example like Neutron and Cinder and Vonova we also collect the server syslogs and as well as the virtual machine logs. For example, if you were running a Hadoop job on top of open stack we're in our environment we're collecting the Hadoop logs so that it's better help you to get to know the information. So based on these data we gather we present to you the avos, the analysis and visualization on open stack. So I'll give you a demo of this video. Sorry, that doesn't look like, I'm not sure how white this shows like that but yeah, the color is really weird. I think it's so good now. Okay, let me, one second. Okay, cool. So this is the avos mainframe visualization. So in here you can see that each circle is one of the virtual clusters you actually have and the heat map is based on, currently is based on the outgoing traffic of each virtual machine but actually if you configure it you can actually make them to represent the CPU or any other heat you want. So, okay.  If you go through the network part, sorry, one second. Okay, so if you go through this network part you can kind of see the circle of virtual machines you already have in one of the virtual network and the virtual machines are surrounded as a circle and each line in the graph means a pair of flow that from or to one of the virtual machines. So you can actually see there are four lines here representing five nodes traffic and that means these five nodes are one of the cluster you have and also by just looking at these pattern you will see that there's one virtual machine on the right will stand out because he is connecting or communicating to the others. You probably don't even know this is a Hadoop cluster but you might know that this virtual machine on the right one might be the boss of the whole cluster. So yeah, that's exactly right because it's actually the master of one of the Hadoop work. So yeah, if you hover onto each virtual machine you actually get all the flows that are coming out of this virtual machine so you can actually have a better look of the pair to pair communication. Now let's look at a heavier situation. So for example, we are actually running many jobs many Hadoop clusters in one network, virtual network. So this would look like a little more messy but if you take look into it there are some patterns still inside and again if you hover on one of the virtual machines you will get the pattern. And one of the interesting thing here is we allocate these virtual machines and gather them by their host. So for example, you can see the outside of the ring represents different hosts and by that you can have a general idea of what is going on between host to host not just virtual machine to virtual machine. So it's like a generative like a gathering model at itself. So for example, in this way you can actually get idea of which host is kind of overload by the network side. And just so you know these status are live data they're changing over time. So you can actually, it's a very good monitoring way to see what is going on and the color right now is representing the bytes per second of each flow. So you can actually get to know the idea of if they're a hotspot in my cluster. Okay, so that's so much for the demo now. And sorry. Okay, that's so much for the demo. We were expecting something like this from you but if it's not then it's fine. So okay. And yeah, what we believe is those data's directly get from either kilometer or log are like fresh data's like juice. You squeeze it directly from the fruits. That's fresh, that's live and that's tasty but sometimes you might need something even more tasty. Maybe you wanna change the juice into the wine. So how are we gonna do that? We're gonna use analysis. And here we present Xinyuan to give you a taste of wine tasting. Okay, thank you. And so we have seen that the real time network visualization could provide us with an efficient way of monitoring the status of cloud operation. And now I'm going to use some examples to show how we can revisit and analyze the historical data so as to get more insights of what is actually going on in our cloud and also use them to achieve a more efficient troubleshooting when something goes wrong. So we have collected the network traffic between each pair of virtual machines and Hadoop clusters which is running on top of OpenStack. And this transfers the distribution of each virtual machine's network flows over time. And we can find some interesting patterns from those traffic. For example, you can see the horizontal trajectories that indicates the communication between Hadoop master nodes and slave nodes. And also we can see such kinds of radical stripes that shows the communication between slave nodes and slave nodes. And this kind of feature indicates active status of Hadoop jobs. And if you take a more closer look at those charts, you will probably find some more interesting patterns or features from them. And so how can we make use of those information? For example, suppose that you are running Hadoop services on the cloud and your users complains that their Hadoop jobs are going slow, what are you going to do? Maybe you will have to go into thousands of lines of say Hadoop logs, OpenStack logs, or system logs, and trying to guess what's happening in the system and trying out things one by one. Or you can just have a look at those network traffic. And you can immediately tell that, saying at some point the traffic of a specific virtual machines is stopped. And a couple of seconds later, maybe you can tell there's something is wrong here because there's a delay of Hadoop traffic. And now if you go into the logs now and search for the specific virtual machines and the specific timestamp that you observe the problem, you will just get a couple of lines of logs that are highly related to the problem that you want to solve. And I believe that this kind of process would be much more efficient than the traditional way of troubleshooting. So, and here is another example. And in this example, we not only make use of the network metrics, but also other kinds of metrics that we collected from our system, such like CPU utilizations and disk input output things and network information and everything else. And if we analyze all of those metrics in an integrated way, we can find some interesting features that can tell us if something is going wrong or some abnormal events happens here. For example, we can see the red color on the left graph. That shows some natural abnormals and we can find different features from the abnormal events and the normal Hadoop workflows. And if we do some more mathematical analysis here, we can also find some, we can also find that some abnormal events in the network show some very special patterns of distribution. And we can use that kinds of things to classify the status of our cloud. So, this is pretty much about all of the research that we have done and some plans for the future. We are planning to make use of those natural flows information to help estimation of the network distance. And here we define the network distance as a kind of relationship between two network entities, especially for the optimization purpose. And also we are planning to go deeper into the data-driven diagnosis with more metrics collecting from OpenStack or bare metal or everywhere and do more integrated analysis of all those kinds of metrics that we have. So, that's it. Thank you very much. And we would appreciate if you can go to the survey and tell us some of your requirements or what you would like to see in the future. Thank you very much. Any questions? Great job, that was really neat. For your analysis piece and the visualization piece, could you go over maybe what tools you use and really how much effort did go into to get some of those visualizations? These are standard machine learning tools that we can use all the existing algorithms that are out there in the machine learning literature. So, pretty much we are using some of them in our architecture roadmap. And this was like a teaser for a project that we are just started. And as part of a roadmap, we want to have more extensive analysis on this. So, but for currently, it's mainly the standard machine learning tools like classification algorithms out there and some basic plotting tools that we have used so far, yeah. So, I had pretty much the same question. Is there some place, is this open source overall? What are your plans? This project, yeah, we are actually, right now in the phase, we want to get the feel of the community, how the community kind of reacts to this and we want to gather requirements and we are eventually going to open source. So, we may actually plan this out as an open source project with the help of the community. Right now we want to see who interested people who would like to collaborate and figure out the requirements, yeah. Absolutely. I just want to congratulate you, this is awesome work. Thank you. Thank you. So, the NetFlow that is getting generated, what format is that in? Is that like IP fix standard format? Any NetFlow collector can consume that data? So, the question is... The flow information, is that in a standard format or proprietary? Yes, actually, it's, we're using standard format to compare the flows. So, actually, yeah, it doesn't really matter how is your network configuration. You can always find the flow information at some point. Okay, thanks. Any questions? Any other questions? And like I said, if you would like to answer some questions out there in the survey, that would help us gather the requirements and what you would like to expect, what you would expect to see in this project. That would help us define the roadmap for this project and we actually would like to take this in the OpenStack community and try to take it to the next level, yeah. Thank you. Thank you.


Okay, as you know we have a historic snow storm out here in Pennsylvania and it's hit a lot of areas harder than we anticipated and it continues. The snow should continue for another two to four hours and it is coming down at a really amazing pace. Some places two to three inches per hour and that is making it really, really difficult for us to use all of our resources to keep our roads open. We, I am not at the point where I am going to have a travel ban in Pennsylvania but I am urging Pennsylvanians, everybody on our roads, not to go out, stay home unless you absolutely have to if we have accidents, if we have roadblocks on our highways we are going to have to close these highways and that's going to make it even more difficult for people who need to move around because we are going to have to redeploy all the resources we are now using to try to keep these interstates and other roads open. We are going to have to redeploy them to keeping people off the highways and that's going to make travel even tougher, it's going to make the cleanup even tougher. So this is where self restraint really matters.  But right now we only have one major problem and that is between Bedford and Somerset on the turnpike and we are trying to, we are doing our best to address that situation. I know we have over 500 vehicles trapped in shoots out there and we are deploying Pennsylvania State Police, the National Guard, PennDOT and the turnpike personnel to try to make sure that our folks in those vehicles are safe, that we rescue them, get them to shelters. We have now checked, I have been assured, we have now checked every vehicle at least once that is trapped out there and to make sure that the people have food, to make sure that they have fuel to keep the engines running so that the heat stays on. We are working to get shelters in place as quickly as possible so that those folks who need to have more food or toilet facilities, there are some buses out there that we need to get to them as quickly as possible. So aside from that, the rest of the state is in as good a shape as can be expected. But again, this is a historic snowstorm, this is a huge challenge for Pennsylvania. We are deploying all of our resources to try to make sure that people of Pennsylvania are safe. That is my biggest priority and that is what I will continue to work toward. Let me just turn this over to Director Flynn and then we will have two other people talk. From the storm's perspective, all of our efforts, as the governor pointed out, is the incident on the turnpike. However, the good news is that the rest of the state seems to be going very well. No major road closures. We have about 4,400 customers out of power, primarily in the southeast counties. The good news is the snow wasn't as heavy as we anticipated, thinking there would be more power outages. But again, in communicating with the utility companies and communicating with the Public Utility Commission, obviously they are on it and the companies are following up with those return time very quickly. So again, from the Commonwealth's perspective, Pennsylvania Emergency Management perspective, our resources are very much focused in on what is happening out there, but we also are keeping our fingers on the pulse of everything else. Thank you. Just kind of an update to the weather situation. The height of the storm is starting to come to a close between about now and six o'clock this evening. Then from six to midnight, the rest of the snow will finish up, so the heaviest snow will come to a close in the next couple of hours. Some of the spots can see an additional four to eight inches. Hardest hit areas have been along the southern tier, especially along the Pennsylvania Turnpike, and areas from interstate 81 south of Hazelton and points east into the Poconos. Again, totals 24 to 30 inches, up to 36 inches in some of the mountains towards Gettysburg, and once the storm is over, we still have to contend with the wind, so there will be some blowing snow concerns going into the overnight hours, but positive news by the time we get into tomorrow for any cleanup efforts, the weather does look relatively quiet. Thank you very much. Okay, we have folks from PennDOT, from Public Utilities Commission, the National Guard, the Pennsylvania State Police, of course, Emergency Management, the Turnpike, and we will answer any questions. Senator, can you talk a little bit more about the people stranded on the Turnpike? Are you just waiting until they can get their cars out of the way, or is there possibly just getting them off, but what's the plan moving forward? Yeah, the plan is to try to get them and their vehicles off, but our first priority is the safety of those human beings, and if we, this is how we have to do it, we want to get them to safety as quickly as possible, either shelters in place or move them with buses to shelters that are fixed and that we can get them to. So we are working, sending buses in there as quickly as we can, and to say in the meantime, we are checking on each vehicle to make sure that something has been done, that they have fuel, that they have what they need to survive until the buses arrive. Governor, I'm sorry, did you say 500 vehicles or 500 vehicles? 500 vehicles. 500 vehicles, so there could be more than, clearly, multiple people in those vehicles. Well, and some of the vehicles were buses, so yes, there are. Any other questions? Yes. At what point does someone's bad judgment turn into something where, you know, it becomes, authorities need to become involved and they, you know, face trouble more than just. At the point we have, the point that someone's bad judgment turns into a social problem is when that bad judgment causes things like what happened out in between Bedford and Somerset. We cannot have that happen. It hasn't happened so far. The citizens of Pennsylvania have shown admirable restraint and that has allowed us to keep our roads open for people who really need to use them. But you have people out there who are making elective trips and they cause problems and they cause problems for other people.  We need them to everybody in Pennsylvania to exercise self-restraint. That's going to be the best for everybody. Have there been any incidents or accidents involving state vehicles such as the National Guard, state police? Not that I know of, not to our knowledge. No? As far as the, do you see any update? I know any update from you. Last we heard there were about 1,200, I believe, out of just statewide. Where are we at now? We're at actually about 4,400. And the highest numbers are in the PICO area, a little over 2,000. But not all of them are snow-related, just to emphasize that. But they're working very quickly in terms of getting people back, their power back on. And they have sufficient crew to do that. And we're very happy, actually, with the numbers, because that's not very large in terms of an event this size. By the way, I spoke with the CEO of PICO yesterday. And he was doing everything he could to make sure they were prepared. And if you saw before the snowstorm on the interstates and the turnpike, there were a lot of trucks coming into the state from out of state to help the local utilities address the issues as they arise. First, big of a snowstorm as it is, are you pleased without everything that's played out so far? I'm not pleased when one person is inconvenienced by this. And that has certainly happened out between Bedford and Somerset. I'm not pleased with that. And we'll look at what happened and see if there are things that we can do better in the future. But again, first priority is the safety of every Pennsylvania, not just a few, not just most, everyone. And if we don't do a perfect job, that's a problem. We can learn from this, and we will. Again, this is a historic snowstorm. This is not something that happens every day. And I think these folks are doing admirable work to try to react to this, again, huge, huge challenge that we all face. Any other questions? One more question regarding the handout equipment that was installed on many of the trucks that were trolling these onboard systems. Want to know how that seemed to have worked out during this first storm? We have the Deputy Secretary. Hi, I'm Deputy Secretary Scott Christie. As you mentioned, we did put automated vehicle location systems in. The trucks that serve basically the interstates, it's working very well. We're getting a lot of good information. I will say I do know that in the Philadelphia area, there were some outages today. So if you were checking the Philadelphia area, you would have seen some outages. But for the rest of the state, it was working very well. And we were able to get the location of the trucks and figure out how much salt they were putting down, if any, for this type of storm. But the information was valuable, and it helps us manage the treatment of the roads as we're going forward. OK. Any other questions? If not, thank you very much. To the folks of Pennsylvania, your Commonwealth is doing what we can to keep you safe. We need you to do your part. Stay off the highways. Stay home and let our folks do their jobs of trying to keep these highways open, and we'll do the best job we can. Thank you very much.


What's going on guys welcome back to the channel critical overload here So we'll be talking about two things in this video We'll be talking about foundest nation six going over an updated plot description that is now available courtesy of production weekly And we'll be talking about Screams seven and speculating pulling at straws grasping at straws if you want to call it that nothing official Just something a bit interesting that seems to be Happening that could tie into scream seven if you choose to believe what I am speculating on so Just to start off I want to shout out to UK if you're listening to this because all of this is coming from you But starting off with final destination six final destination six as I put out a video on Sunday It's going under the working title of foundest nation six bloodlines and At first going off of what I was saying was coming from the Hollywood North Buzz It seemed as though the first responder concept was still at play for the upcoming foundestination six movie We know that it's supposed to actually start shooting in Vancouver later this year during the month of July through September That is still the case, but now I'm not too certain if that First responder concept is actually going to be fleshed out in this upcoming entry Which does has me a little have me a little bit upset However, there's a chance that this could just be a specific person who is still a first responder Dealing with the latest string of events associated with death and its design So the updated synopsis according to Production weekly for final destination six goes as follows a young woman named Stephanie Has a recurring dream about dying in a fire that occurred in the 1960s She realizes that is not just a dream But a premonition of the fate that awaits her family her grandmother had escaped the same fate years ago now Death is coming after Stephanie's entire family and she must find a way to stop it before it's too late Now the young woman she's named Stephanie She's having a recurring dream about dying in a fire that occurred in the 60s But she comes to realize it's a premonition We don't know who Stephanie is she could actually end up still being a first responder I'm holding out hope that this is still somehow connected to first responders She could be a EMT. Let's say for instance and then her grandmother I thought that this is an interesting tidbit. It says that her grandmother had escaped the same fate years ago So did this grandmother actually manage to do what Alex couldn't do? Which was cheat death and get out of its design get out of its path And if so is this film set in the same universe as these other movies? Or is it just a complete entire rehaul that of course is still a found destination movie one way or another but The grandmother stuff I think is gonna be something that's fun to explore because it says her grandmother had escaped the same fate years ago Now death is coming after Stephanie's entire family and she must find a way to stop it before it's too late So this would be the first time I think where you have death coming after an entire family And it's connected to an older relative getting away from death years ago that that is different I I don't think we've had that before in the found destination series I would if this is the different thing that they're talking about that is very different The concept of the fire doesn't sound all that exciting compared to some of what we've seen in the past But again, there could be some aspects to Stephanie that still make this a compelling story I'm still again holding out hope that Stephanie is a first responder But time will tell if Stephanie is a first responder or if that concept was abandoned completely You guys can let me know what you think about this information regarding found destination six down in the comment section below We're gonna jump into scream seven Scream seven again has not been officially green lit by paramount spy glass Nobody involved with radio silence or anybody involved with the official cast has actually said that yeah, it's happening But we more or less do the commercial and critical success have a have a good hunch that ghost face Will be returning sooner rather than later and of course recently at the cinema con panel Paramounts made it known that they listen to their consumers And I guess if your consumers showed up for a screen movie You're gonna continue to listen to them and give them another screen movie because they're gonna show up for that one as well Which is the again the other sign that scream seven is coming sooner rather than later It just hasn't been officially green lit now recently the last biggest thing we speculated on here Was the fact that Christopher Landon could be involved in scream seven because Christopher Landon who again is responsible for Freaky and happy death day He recently started following the core four of actors Melissa Barrera Jen Ortega Jasmine brown Mason Gooding along with head of my terrazzo who we know plays Martha Meeks in the screen franchise Hasn't followed Courtney Cox So that's the only thing that kind of takes away from that being a possibility but the other interesting thing that has now happened is Mike Flanagan and again shout out to UK has started following Christopher Landon on Instagram and Christopher Landon has started following him back or at least their interactions might have been might have been increased recently So the reason I found that to be interesting is because while he hasn't followed the core four actors the way Christopher Landon has Could Mike Flanagan be involved with an upcoming screen production and the reason I think that this is something worth speculating on is because if you click on the link in Mike Flanagan's Instagram bio it comes up with a Bio to his website Mike Flanagan film calm that says that under their In respect to him and producer Trevor Macy under their intrepid banner Flanagan and Macy entered into an exclusive overall deal at Netflix in 2019 for the television projects and have produced feature films for Warner Brothers Universal pictures and Paramount among others now It's that among Paramount. They got me going now you guys can help me because I haven't been able to find anything What Paramount movie has Mike Flanagan worked on I can't find anything That's why I'm like is this actually related to a new upcoming Paramount project. Could it potentially be? Screams seven. I mean you just started following Christopher Landon who also just recently started following the core four and Heather Montorazo and then your bio has stuff related to you working and producing feature films for Paramount, but I can't find anything from Paramount that you worked on recently in the past That's why I'm thinking it's a future project now I think that the pairing of Mike Flanagan and Christopher Landon would be something something that could balance itself out People were already concerned about Christopher Landon leaning too heavy on comedy I think that if Christopher Landon was come was writing the script and Flanagan was bringing it to life He would lean more on the horror side of things and he would also of course Give you Something along the lines of what you have seen if you love haunting of Hill house Bly Manor all those Mike Flanagan projects, but this would be a lot different because it would be Mike Flanagan's I think this would be his first slasher film So it would be nice to see him kind of again balance that comedy and that horror Which I would say he kind of already does have a good habit of doing but he leans more on horror So I just think it would be a more a thought-provoking film if Mike Flanagan was in the or at the helm behind a screen project The other thing that was interesting Nothing too crazy just something small back in 2022 He actually responded to a fan on twitter when asked why he doesn't do sequels Mike Flanagan said I did the sequel to The Shining and had a blast doing that and I did the preco to Ouija And loved that too for the record if anyone brought screen 5 to me. I would have been very interested So that's again another fun thing to see. He's already made comments about how he would have done screen 5 Is he about to do screen 7 time will tell let me know just think about this down the comment section below If you haven't already course make sure you subscribe turn on post notification in this video in the description I have links on my social media accounts. I'm on facebook, twitter and instagram You can message me there, of course, there's any movies news or reviews like me to cover in the future And with all that in mind guys, I will see you in the next video


That was the only announcement I made. Today, we will continue this discussion. In particular, I am going to talk about the Gram-Schmidt orthonormalization process. So there's one definition I want to put down before I begin. This is the definition of an orthonormal or orthogonal basis. So if you are given a basis consisting of vectors v1 through vn of a vector space vector space v is said to be an orthogonal basis with respect to an inner product. So in order to say whether a pair of vectors is orthogonal or not, you need to have some notion of an inner product. And I denote that inner product by these braces with two arguments here and a comma between them. If this set v1 to vn is an orthogonal set, what is an orthogonal set? We defined it in the previous class. A set of vectors are said to be orthogonal or mutually orthogonal if the inner product between any pair of vectors in that set is equal to zero. And we say that this basis is an orthonormal basis. It is orthogonal, vi inner product with vi equals one for all i. And that's one definition. So two keywords that have come here, orthogonal basis and an orthonormal basis. Okay, so it turns out that any vector space v and inner product defined like this has an orthonormal basis. So the question is how do you find such an orthonormal basis? So if you're given a basis for a vector space, then you can use the Gram-Schmidt process or the Gram-Schmidt algorithm to find an orthonormal basis for the vector space v. And why are we interested in orthonormal basis? We'll be clear as we go further in the discussion. So the Gram-Schmidt process. So basically this is the input. So it's a set of vectors, say x1 through xn. And these are linearly independent vectors in c to the m. And what is going to be the output of this algorithm is a set of vectors z1 through zn is an orthonormal set of vectors such that span of first set of vectors or z1 through zn is equal to the span of x1 through xn. So by the way, actually the correct way of writing a sequence is always like this. You have to always write out the first two elements and then separated by a comma. Then a comma and exactly three dots. Then a comma and then the last element of the set xn. You should not put four dots, five dots and so on. And there should be always these commas in between them. And you should always list the first two. But sometimes as usual I get lazy and I just write z1 to zn where there is no confusion that I'm not skipping anything in between. It's just z1, z2 up to zn. Okay, so this is how the procedure works. And I'll first put down the procedure and then maybe make some remarks as to why this procedure will yield a set of orthonormal vectors such that the span of these vectors is exactly the same as the span of x1 through xn. So I expect that you also seen this procedure previously. So this is more of a recap. So you start out by saying let y1 be equal to x1 itself. And then you normalize it. So you set z1. So I've already found out what z1 is. The first vector is going to be y1 divided by inner product of y1 with itself power half. So this means that z1 is now normalized. I already mentioned this in the previous class. If you take any vector divided by the square root of the inner product of that vector with itself, you will get a unit norm vector pointing in the same direction as the original vector. So z1 is now normalized. Okay, now I want to find a z2 which is orthogonal to z1, but span of z1, z2 will be span of x1, x2. So how do we do that? So we let y2 be equal to x2 minus some scaled version of z1. And the scaling factor is the inner product between x2 and z1. So now what this means is that this y2 is perpendicular to z1. Why is that true? So if I take the inner product between y2 and z1, that will be the inner product between x2 and z1. Inner products are linear. So it's the inner product between x2 and z1 minus this coefficient times the inner product of z1 with itself, but z1 is already unit norm. And therefore the inner product of z1 with itself is 1. So it's the inner product of x2 with z1 minus the inner product of x2 with z1, which is 0. So y2 is a vector that is perpendicular to z1. And then I normalize this and I set z2 equal to y2 divided by the inner product between y2 and itself power half. So now z2 is unit norm and so on. So I proceed like this. And so just to kind of make it clear in the case step, I let yk equal to xk minus the inner product between xk zk minus 1 times zk minus 1 minus the inner product between xk and zk minus 2 zk minus 2 and so on inner product between xk and z1 times z1. So what this means then is that yk will be perpendicular to all the previous vectors z1, z2 up to zk minus 1. So we can set zk equal to yk divided by inner product of yk with itself power half. So this is the overall algorithm. And you keep going up to k equal to n. Sir, can we say that orthogonal vectors are linearly independent? Yeah, so if you remember in one of the previous classes, I did say that any set of non-zero orthogonal vectors are linearly independent. And I said you should try to write out a little proof for why that should be the case. Okay, so obviously if I take the zero vector, the zero vector is orthogonal to every other vector. Okay, you take the inner product of the zero vector with any other vector, you will always get zero. So orthogonal vectors are not necessarily linearly independent, but non-zero orthogonal vectors are linearly independent. Yes, sir. So just to make some remarks about this, just by construction at step k, we have that span of z1 through zk, zk equals span of x1 through xk. And this is true for k equal to 1, 2 and so on. So at every k, this is actually true. So what this means is that if I want to write a linear relationship between x and z, then I can write this matrix z whose columns are z1, z2 and so on. This is equal to the matrix x times r, where r is an upper triangular matrix. So going forward, I'll use this notation to write upper triangular in short. Okay, so if you look at this, so if r is upper triangular, what it means is that when I multiply, so just for the sake of completeness, I'll say here, z is this matrix formed by z1 through zn, and x is the matrix formed by x1 through xn. I don't want to put commas here. It's just tacking these next to each other. Okay, so if r is upper triangular, it means that if I look at the first column, remember I talked about how to view matrix multiplication. If I look at the first column of v, it's a linear combination involving only the first column of x. So basically that is what is captured by this equation here. If I take the second column of z, it's a linear combination of the first two columns of x. Okay, and so it goes. And the second remark I want to make is that if x1 through xn are linearly dependent, remember I presented the algorithm by assuming that x1 through xn are linearly independent vectors in c to the m, but I can actually run this algorithm even if these vectors are linearly dependent. So if x1 through xn are linearly dependent, if they are linearly dependent, we can still use Gram-Schmidt to find a basis and the dimension of span x1 through xn. So basically how this happens is that if, for example, xk is linearly dependent on x1 through xk minus 1, then when you run this Gram-Schmidt process and if you compute this yk here, it will turn out that yk will become equal to 0. So that is something you should convince yourself about. I'll write it down for you and you should, again, try to write out a small proof for that. Then what you can do is to skip xk and then proceed. So you just don't compute as zk.  So basically this is something you should show. If xk is linearly dependent on x1 through xk minus 1, then yk equals 0. So at the end of the Gram-Schmidt process, you will have an orthonormal basis for a span of x1 to xn. So to be more clear, these are two remarks. Any questions about the Gram-Schmidt process? Okay, so I'll make one other small remark. It relates back to some things we discussed in the previous class, actually two classes ago. So this is a note about orthogonal complement subspaces. So recall that the range space of A is the orthogonal complement of the null space of A transpose. So that means that Ax equals B. If I take this system of linear equations, this has a solution if and only if. So this will have a solution only if and only if B lies in the range space of A. If B is not in the range space of A, then it will not have a solution. So if B lies in the range space of A, it means that B must be orthogonal to any vector that lies in the null space of A transpose because the null space of A transpose is the orthogonal complement of the range space of A. So to put that in words, the way to write it is B transpose Z must be equal to 0 for any vector belonging to the null space of any A transpose. That is to say that for any Z such that A transpose Z equals 0. So that's just a side remark I wanted to make about orthogonal complement subspaces.


He's right on the tip of my tongue. What do you look like? Bob Hoskins! Recent Google searches. Crosswords. I was stumped so I was cheating and looking up with some answers. I got into crosswords from doing theatre because I was in Hamlet and I played Fortenbrass. Fortenbrass basically comes on stage when everybody else is dead. It's just a long, long, long wait until you get to come on stage. And at that point, most of the dressing rooms empty because they're all on stage. So I started to do crosswords to occupy my mind. I'm just getting the grips with the New York Times one because it's... They're kind of tricky. I mean, they invent their own words. I don't quite... Maybe I'm using the wrong dictionary. One of them recently had a lot to do with The Lion King which I've never seen. I know! I've never seen it. So, yes, I didn't know the characters' names and stuff like that. So I cheated and looked them up. Can we edit this? I had to do this thing yesterday and so some of the questions that they were asking were what would I consider to be a movie that defines Britishness? That was tricky because depending on what part of Brittany you're from, you could really piss people off with the answer that question and say train spotting. But, of course, that's Scotland and they probably aren't going to like it if you say that you're quintessentially British. So depending on where you come from in England, it's very difficult to say what one movie is quintessentially British. But I would say that the best definition of the curse of being British was offered up by John Cleese in a fish called Wanda. That is that you're in constant fear of embarrassing somebody. Search a Google... I was Google searching. Craig Mazen's Chernobyl podcast. So after every episode, he would then post the podcast talking about that specific episode, which I found really fascinating because obviously I'd had talks with Craig beforehand, but never you don't have the opportunity to go into that much detail and it's really fascinating to peer into his thought process and understand how he constructed this narrative. One of the things that people are responding to the story is there's a very clear analogy towards the climate debate that's going on at the moment and the denial of the science and the refusal to confront that problem. It's a masterful piece of a construction, of narrative construction. So I'm fascinated by that. A hole in one's education is a very good tool for fulfilling in Google searching.


I just just realized that we just got a sell signal on spy. Let me analyze it really quick. Nope. Don't want to trade this one. It's just not to my liking. Yep. It's a sweet deal that I didn't trade the signal right here. I'm really honing down on my strategy. Pretty cool guys. I'm really excited about that. The only thing I am disappointed is that Netflix, I'm not at that level yet. I'm not at that level quite yet. But I am really thankful, really happy that even though I got a signal, it just wasn't within my parameters and I didn't trade it. So that's a win in my book guys, so that's it. That's all I got for ya. Do you know what's just as good as getting yourself into a good trade? Is not getting in on a bad signal or a bad trade. I felt so good whenever I decided to not jump in per my strategy essentially and not get in and then truly it being a bad signal. And it feels great, feels phenomenal. It's almost, dare I say, it's just infinite power. It really truly feels that good guys. That's what a good strategy will do for you. That's what a good strategy will tell you. It'll tell you when the possibility of you being in a good trade or making a profit. It'll tell you that and it'll also tell you when you shouldn't get in, when the odds are completely against you. So that is what I wanted to tell you guys and show you guys. I'm so happy I didn't trade that signal even though gosh I just, I wanted to so bad just because it was a signal of mine that popped up but I didn't. I'm following through with my strategy, I'm getting over it. I'm getting, I'm learning, I'm getting it. I'm working super ridiculously hard to get over the emotional side of trading and trying to think logically and that's what's going to help me. That's what's going to help me succeed in this game of day trading. I really do feel like I'm making an awesome roadmap on how to be successful in the stock market and I'm doing it here for you guys in front of you guys. I'm doing it for myself and my son as well guys. Super happy, super proud of myself to show that restraint. To show that just the restraint of hey, it's not there, don't trade it. And then also there was, my strategy also missed essentially, missed a good trade yesterday as well but I'm not so disappointed in that. There's always the next trade guys. There's always the next trade and that's what I'm telling myself. That's what I want to tell you guys so regardless of what you are doing today, if you lost money or if you made money, there's always the next trade. The stock market isn't going anywhere. Thank you everybody for watching. I know this is going to be a shorter video than usual and not quite exactly my norm but I wanted to show you that my strategy visually isn't 100% but I'm learning how to better trade it guys. Don't forget to hit that subscribe button down below and that bell notification so you get notified the moment I upload a video guys. Thank you so much. Let's get profitable next week. Thank you.