Hello, everybody. Welcome to another Cloud Native Live. My name is Mario Lora. You've seen me before, I'm sure. I've been hosting Cloud Native Live on and off since we started the Cloud Native TV network this year. Thank you so much for joining us for another wonderful episode where we are going to dive into chaos engineering. So today I have Karthik with me from Chaos Native. And they're a company that is working on resilience engineering in our world of Cloud Native and leveraging a chaos engineering to achieve that with their product litmus chaos. So I'm going to be, I'm not going to get into Karthik. What I'm going to do is try to answer all of your questions. Please leave your questions in the platform of your choice that you're using to watch this right now. We thank you for tuning in and spending time with us today. This is going to be a really, really fun session. I have a lot to learn. I know Chaos from the Chaos Monkey project on GitHub and other talks from Netflix engineers like Adrian Cockroff and others who have been pushing for a chaos to increase resiliency and reliability of your platform. Very, very difficult to hone in and get just right. And it's also very scary for a lot of organizations knowing where companies I've been at. You know, what they've been able to do and what they've been comfortable with doing introducing chaos is actually really scary. And it's hard to take that first step. So I think Karthik is going to be teaching us a ton of great stuff. I'll let leave him to get into his background. But again, I think everybody for joining, please leave your questions, comments, thoughts in the chat. And I am monitoring those. So I will be sure to get those questions asked to Karthik. And we'll be kind of going through a wide gamut of different areas in chaos engineering, the ecosystem and cloud natives role. So thank you so much. Please join the public Slack channel, hashtag cloud native live as well. If you want to chat with more people, I think myself, Karthik and others that have been on the show are definitely, definitely hanging out there. And check out chaos native while you're watching at chaos native at litmuscast on Twitter, chaos native.com. I'm scrolling through here and I even see Victor Farsik from the I think DevOps Exchange podcast has even done a episode on integration with Argo workflows, which is super exciting. And I didn't know existed and I use Argo. So I have a lot of work to do this week to share this with my team, I think without further ado, Karthik, thank you so much for joining us. I'll let you take it away. Go ahead. Thank you, Mario, really excited to be part of CNCF live and discuss chaos engineering in it was chaos. Thank you for the introduction. Like Mario said, my name is Karthik. I work for a company called chaos native. And one of the main dealers of the open source CNCF Sandbox project called it was chaos. And today we just want to discuss what cloud native chaos engineering is and talk about the project that there has been a new version that was released just early or late last week, I should say.  And I think in the process of talking about the project, I just introduced you to what it was one dot X did and what is the feedback that it received from the community and how was part of how it was created. And we will go through a couple of demonstrations to discuss about what this platform is about. And I hope this encourages you to start with your chaos engineering journey in your organizations. So please feel free to ask us any questions and be happy to answer. And that's about it. All right, with that said, I just want to introduce what chaos engineering is. I'm sure a lot of folks already know about chaos engineering. You might be practicing chaos engineering also might be practitioners or you might have heard about it read about it. Mario mentioned about Adrian Cockroft and Netflix. They were really the pioneers that sort of started the movement of chaos engineering. And Netflix along with a few of the other organizations early adopters of chaos came and created the basic tenants of chaos engineering. You can look at this website called the principles of chaos.org, which carries a lot of information about what ideas, why it is important, what are its principles, etc. This brief summary, I have a couple of slides, which I just used to talk about chaos engineering and state of chaos engineering today with all the cloud native revolutions that is going on. So I hope my screen is visible. Okay, I'm hoping that the screen is going to be visible. Let me just quickly run through this. One of the basic reasons why chaos engineering is very important is because downtime is very expensive. We have had some past incidents in organizations that are generally very resilient, where it has cost a lot of money because of downtime. And that is something we would want to avoid. We would like to test out how the system behaves to different kinds of failures and how the deployment environment can be improved and how the application residents can be improved in order to withstand this turbulence and still be available. A lot of services that we're consuming on a day-to-day basis have publicly available SLAs. For example, Google Cloud and Azure Cloud says it is 99.95% available all the time. So chaos engineering is a practice which actually helps you to verify if you're able to provide that kind of Nestle and be available all the time. And by definition, there are a lot of definitions on the internet where you can see. There are a couple of forms that I've picked. It basically says it is a method by which you're testing a distributed computing system so that it can withstand unexpected disruptions. You're testing if some of the components or some of the assumptions that you had when you built the code. For example, you always thought the network is always going to be alive. You have unlimited compute, storage, bandwidth. That's not often the case. There are failures that happen all the time. And we need to check if we can withstand the disruption. We can recover quickly enough and continue to provide the service and acceptable level to the users. And chaos engineering is not about reckless fault injection. It's a scientific process by which you identify a control group, an experimental group. You inject faults in a very controlled way. You basically ensure that there is minimal blast radius when you're injecting faults. And then basically you see what happens. You try to learn about the system. Sometimes you go with hypothesis that is proved. Sometimes it is disproved. If it is disproved, it is better. That means there is something that you learn newly. You can go back and fix your application. Or you can go back and fix your department practices. Maybe you can improve the underlying infrastructure and make it more resilient. There are a lot of things you can do. Repeat your experiments, gain confidence, etc. So that is generally the practice of chaos engineering. Because of the times that we are living in today, I think the pandemic, probably this is a better analogy. It is like a vaccine being inject harm and try to build immunity from outages. That's what we try to do. The standard chaos experiment flow is like this. You identify some study state conditions. That's part of your hypothesis. You see how much deviation there is going to be from your study state, if at all. How quickly you are expected to recover. Then you go ahead with the fault injection. Verify the hypothesis. If it is, that means you're going to go to the next fault. Maybe it's a more complex fault that you go to the test.  Or if there is a weakness that you found and your hypothesis was disproved, then you go back to the drug board and check what went wrong. What needs to be better? Make those fixes and then repeat once again. Chaos engineering is traditionally, it has been traditionally done in production for a long time. That was the philosophy chaos engineering is most effective and useful when you do it in production. The principles of chaos tells as much. But with the recent proliferation of Kubernetes and the evolution of the cloud native paradigm, where in a lot of organizations are re-architecting their applications, they've been taking from, taking away from the monolith model and creating everything as microservices. They're containerizing it. They're running it in new deployment environments, mostly Kubernetes. So there's a lot of apprehension about how things are going to work and probably folks are not ready to do chaos engineering in production from the get go. There's a lot of protection and chaos experimentation that is done in preparation environments to gain confidence before it is really done in production. That is the change that we've seen happening in the chaos engineering world in the last couple or so years. And we mentioned the ADM.NETX and Amazon in the beginning of this discussion. There is a principle that ADM is a big advocate of called as the chaos first principle. So it is about doing chaos engineering in a more ubiquitous and democratic way. You start doing it in development environments, you start doing it in stage in production.  And you basically do SLO validations based on or during chaos experimentation.  So it's our objectives are met under US before let's say your application is moved into production. And then probably when you mature you start doing the actual game based chaos experiments in your production environment and try and see whether your system works out there. So that is what we've seen happen in the recent times. I mentioned about how Kubernetes and Cloud Native is a factor in getting people to do chaos engineering much before and earlier and often. That's because in a Kubernetes based deployment environment, there are so many variables, so many factors. Kubernetes itself is quite dense. There are a lot of content services, but you're hosting there on top of some platform infrastructure. Then you have a lot of tooling that you've pulled, a lot of frameworks that you've pulled from the CNC landscape for service discovery, for monitoring, storage, then you have your direct application dependencies, your databases, message queues, then your app with all its services, services, your middleware, front facing user facing services, etc. A lot of things can go wrong. And it is important that all these components work well in sync to provide the best user experience that you have guaranteed to the users of your service. So it is possible to test out various scenarios and test it often. And one of the reasons, one of the pillars of the Cloud Native way of doing things is to release fast, to keep everything as micro services, to ensure that everything is declarative, everything has the gift as a source of truth, you have controllers that ensure your infrared, your code in your source is synced on base. So changes are happening in a fast pace. So you need chaos engineering to sort of borrow some philosophies from the the current model, ensure that your chaos intent can be declarative, ensure that you automate steady state hypothesis validation as part of the experiment run, ensure that it lends itself to GitOps, and ensure that you have the same user experience or same homogenous experience that you have had with other things on Kubernetes. Maybe you're talking about defining application, life cycles, security, resource policies, etc. Everything is defined as resources and we have controllers in Kubernetes to manage that. And you would sort of like to break that into your chaos engineering as well. So that is an introduction on what chaos engineering is generally, and what this category of cloud native chaos engineering is. It introduces you to latest project. This is an open source project, which has been around for about three years or so now. And it provides you an interim platform for doing chaos engineering on Kubernetes. And we've also started in spending it, providing capabilities to do chaos against pre-cubanities or say non-cubanities infrastructure aspect. Easy to instances on AWS, GCP VMs, VM-ware machines, VM-ware VMs, etc. So the Flippers platform runs as a set of microservices on Kubernetes. So it uses Kubernetes as the substrate to run the chaos services, so to say. And you could make sure you could pull some ready made off the shelf experiments that are available in what we call as the chaos hub. The chaos hub is an open marketplace where you have a lot of common scenarios that you would like to execute. You can pull the fault templates, install them on your cluster and define a custom resource that maps the fault to any object on your cluster. It could be a node resource, a power resource, and you sort of go from there. That's what the difference is about. Very simply speaking, it has a set of custom resources to define chaos and statistical validation at its heart. And it has a controller that reconciles these resources and carries out the chaos experiment of the fault injection business project. And there is a way for you to look at the results of the experiment so performed and gain some information about your applications and enterprise behavior. So the project was started, in fact, to serve the resilience test needs of another CNC project called OpenEVS. And over a period of time, it sort of acquired a roadmap with its own became more popular in the community. So we had requirements which sort of start coming in. And we went from being a platform that can do chaos in a cloud-native way, that is you define intent in CR, this controller is going to carry out the experiment for you. From there, went on to make it an end to end platform because chaos and stating has a lot of other requirements in terms of observability needs, in terms of defining blast radius in a very controlled way, in terms of ensuring that your chaos results are being analyzed for a period of time to give you useful information that you can generate about your system. There's a couple of KPAs associated with chaos and training practice. So help you gain some information about how your KPAs are doing as far as your practice goes. So some of that information we wanted to bring in, and we also wanted to make it easy for folks to do complex experiments, be not simple faults. We just, we start off being simple faults, of course, but sometimes you want to generate complex conditions. You want to provide the study state validation agent, spot of the experiment run, and sometimes there are very diverse ways of verifying study state. So you want to impact all of them in. So all that is about what we did to get it from its initial stage of the one dot x release to make us 2.0 on what it is now. So that's an introduction to the philosophy of chaos and what it says. I'd just like to see if there are any questions we've got to see. Yeah, for sure. Thank you so much.  This is, this is great. Okay. So I just have a couple of these are lightweight questions that you'll be able to smash pretty quickly. I think when when most people think about testing an environment to to maybe test as close to a real world example as possible, what they often consider is something like emulating a DDoS attack, something outside is causing harm coming in, right? If the kind of ingress layer, right? And they are hitting certain API endpoints, or they are sending malformed requests, right? They're doing something at maybe a higher level. And it sounds like what litmus does actually runs in cluster, right? And this is kind of going back to chaos engineering, you're actually inflicting chaos from from yourself, like in internally, not externally, right? And so, you know, you mentioned limits has a few different types of maybe like attack library. And I'm actually looking at gremlin as well, which is another chaos engineering platform. And I'm interested in some of the differences there. But what what, you know, what is kind of the go to MO for the the default patterns that you find people using litmus for? And can you expand on a little bit of what you're doing? It sounds like you're taking litmus to the next level of building a platform. How do you intend to like, leverage that platform to help provide continued reliability insights, SLAs, things like that for not just your Kubernetes cluster or the API or an API, you know, for your application, right? But more so for the entirety of a platform, if I, you know, I have 30 microservices, what does that look like? It's a great question. Yeah, so you're right about the first part, my latest litmus when it started a lot of members of the community started using it and still do predominantly a large set of users use it for inflicting some chaos within the Kubernetes cluster and the services that are inside it. So litmus has this feature to do some asset discovery, which we will show very shortly during the demonstration where you can identify what are the different services that are living inside of your cluster, and you will be able to sort of access them and sort of target them. And two different faults, for example, the generic category consists of most of the part level and Kubernetes node level faults.   So things that can be done with incubalities. And it has this model, especially in 2.0, where you could run the control main services within one cluster. And you can register several other target environments or Kubernetes clusters into the control plane. And you can run some agents there, which will actually carry out the faults. There are ways to keep the litmus parts immune from being impacted by the chaos it is generating. So you can target specific other parts, you can have labeled the rotation selectors in space, namespace filters that we can use. And you can also set up some affinity policies and load selectors and things like that to ensure that your application services, litmus application services are not really impacted by the fault it is causing. And you can really point to specific resources against which you want to do chaos. But when you think about things happening outside of your cluster, for example, you're talking about some application services, which are receiving requests from an ingress of their requests from outside. So it also has the capability to go ahead and ensure that the traffic is inhibited against a certain destination addresses, probably. So let's say there is service that is talking to a service inside of the cluster, you can ensure that the traffic between these services alone are disrupted, for example, that's something that you could do. That's one thing that we developed recently. And a lot of organizations still have a hybrid model, not everything's on Kubernetes. So there are experiments that we've started creating for AWS, for example, where you can run the experiment business logic from inside of Kubernetes, so the transfer's upon. But we are making use of the API that's provided by the cloud provider, for example, AWS or GCP or Azure. And we can go ahead and invoke those APIs, they are provided by SDK. So you can make sure that you can have some access secrets created on the Kubernetes cluster where the experiment business logic comes. And then you target some non-Kubernetes resource that's completely elsewhere. And still invoke the failures there, you can cause instance failures, discretaches, and also cause, let's say, the source of a network degradation within those fields there, which may have an update on Kubernetes. So that way you would still run like this from within the Kubernetes control plane. And you would still be able to target resource that exists outside of Kubernetes. That is the model that we are sort of working towards. And there are limited set of experiments on AWS and GCP and VMware, and Azure, and we are the process of expanding those experiments. And the faults that you could do on non-Kubernetes, so that you get sort of a wholesome platform, you're able to use the same centralized platform for doing chaos on different kinds of targets. So that is you brought up Gremlin, which is another great tool, which which has been around for quite some time. And they have added capabilities to do Kubernetes based chaos as well. And so they primarily started out as doing chaos against VMs. So that is we are in the chaos engineering community, and the tools in the open source as well as the closed source space are really growing today. It was differentiated in terms of its architecture in how it runs as a Kubernetes app, as well as the way in which it treats an experiment. So what we're trying to do is align with the principles of chaos and provide an end-to-end experiment, the notion of a complete experiment that has spot injection as a added score, but also has blast radius control, ability to do steady state validation, ability to simulate complex scenarios by sort of stitching together experiments. So you could actually go ahead and run more than one thought. Let's say you have a node which is almost exhausted with resources, there's nothing much scheduled there, then you have an other node in which there was, let's say an addiction that happened. Or let's say there's a part that got deleted there because of some reason, and you're not able to get scheduled anywhere else because there's another node which is already running full capacity. So this is a condition that is sometimes seen in production, I want to bring up this scenario, it's a complex scenario, it might happen to two fonts and tie the right validation along with this. So it was enables that through what we call as repose workflows. So to summarize, we're trying to build what is an end-to-end years platform for doing complex experiments, and also visualize the progress of the experiments. And you mentioned about how can I get information. So how can organizations try and take a look at how their case-injury practice is going, does it have an overrun residence view? That's what we're trying to build with LITMAS as well. So there's an analytics section here which goes through all the past workflows that you have run against your services, then you will have a comparison that you can do against, you might have done these workflows or experiments against different environments, maybe dev stages in production, or maybe across a few releases. So you're trying to validate this, you're trying to compare how your experiments went, and see whether you're improving or whether you're going down. So that is something that we're trying to add. So there are other views, other viewpoints that we're trying to add here based on community feedback as to what is what they're most interested in when they're running experiments. For example, people would like to see how their application behaves. We'll see that one of the demos where, okay, there's something that I'm pairing into my application dashboard. Now, I want to see when chaos is actually running, when did it start, when did it end, and how the application behaved during this process. So that's some amount of observability that we're trying to add into the platform as well. So there are some dashboards you can add within that it must chaos center as we call it, and there's something that you can use directly to instrument your phone dashboards, etc. So that's how we are trying to improve the platform. Yeah, that was amazing. Thank you so much for getting into that. And this platform, this UI really helps seal the deal in terms of what am I actually getting from an end-to-end perspective. I think the analytics, you need to be able to measure progress. Where am I at now? What is my desired state? And what are the incremental changes or pieces to getting to what my desired state is, whether that is being able to support so many requests per second or being able to sustain failures of database connections or whatever it might be, right? So I think, you know, principles of chaos.org, you've heard Karthik mention it a couple times. I think that's a good starting point. That's actually a GitHub project as well. There is literally just search chaos engineering on Google. You can find tons of great resources that kind of look like what Karthik and I have been talking about here and why this is so important. The other thing I wanted to mention too, Karthik, is a lot of people don't really understand why do I need chaos engineering. Why do I need that? I'm not going in. No one in our SRE team is going to go in and just delete pods. No one's going to go and mess with external name objects in Kubernetes or screw with our CNI daemon set. No one's going to do that, right? And it's not about the humans as much as is the natural elements of a cluster and the churn, what's going on, there's maintenance, there's updates, there's auto scaling. There are devs constantly deploying things. There are people hopping in pods to look at things and test things. There are objects coming in and out. There's many different namespaces. I'm talking about some of the SRE core principles here of assuming failure. Assuming failure and using strong measurements, SLAs, SLIs, to track your services, your endpoints, and really once you think about that and you think about maybe, let's say, because I have experience with an e-commerce platform where you've got, at any given time, you might have a marketing event and have millions of people coming into your platform in the scope of five minutes. How are your applications going to work? And I've seen so many different sorts of problems where you can throw compute at something, but if the things it depends on, if it can't get out to the internet, if the NAT gateway is broken, or if other services it depends on in the chain of doing its operations to do some processing and produce an output, if something is broken there isn't scaling there as you'd expect, right? You're not going to know about that until it actually happens. I fundamentally think that there is no way to anticipate problems until you actually experience them. And so I think that chaos engineering basically is saying, you have to commit to being okay and again it's going to be scary, but things are never going to be perfect. You're never always going to have five instances of your application 100% working, perfect, hitting health checks, responding in under one second, right? You're never going to have things in a perfect capacity. So what actually happens? What does that mean for your end users? For the people that are using your platform day in and day out who might be buying something from it or depend on it for whatever reason, this is all together making Kubernetes a better platform for you to continually use ship applications and really get that feedback loop of analytics, metrics, and other data so you know what's actually going on. Having that intelligence, right? It's not maybe the older world where you just like throw it on there in the services system CTO. Great, the service is running and you know hopefully everything's good, right? I think this is the new kind of model for thinking about how we do things, especially in a cloud native way. So with that I'm going to give it back to you, Karthik. I think you've already shown us a little bit about the platform. You probably want to dive into what some of the differences from 2.0 and 1.0. I'd love to hear more about you know what was the intent with 1.0 and what are some of the key things and learnings that you and the team leveraged to kind of figure out we want to do 2.0 and this is what it should be. Take us through that a little bit and I'm sure we'll have some questions from there. I know I have a few other questions as well but take us through that. Sure. I think when we built 1.0, it was just like I said the need for us to be able to create something that was cloud native to do chaos. So one of the things we felt was in Kubernetes everything happens to be a resource whether it is native or custom and then you have a controller that becomes as things. So we want to bring that experience to Kubernetes chaos engineering as well and that's when we basically created some custom resources and they call it with experiments here, the engine and the result of course along with the controller to carry out the chaos process. So this is a very brief summary of what it is. On the hub that I just showed you a few minutes back there are a lot of templates that you can put, pre-built templates that define a particular thought. Then there is a chaos engine the one that is user defined the one with which users deal with on a day-to-day basis where you provide other run characteristics about the experiment and map a thought with some component that is living on a cluster right now which is either a truck component or service or maybe in case of non- Kubernetes chaos some instance that is living somewhere on the clock. So that's what you create and so chaos engine is the one that actually triggers when creation of creation of which triggers the part injection process and the results of this experiment are stored in a chaos result and these sort of create certain resources because there's a huge scope for you know sort of expanding the schema and what all this can hold. In case of chaos results you can store the experiment status, the verdict of the experiment upon completion based on certain steady state validation constraints would like to know how each of those constraints work when you run the experiment. We use something called probes to define those constraints when you run the experiment. So how did they go and then of course to repeat the experiments in end with different scheduling options you might want to randomize your experimental donate over a prolonged period of time either strictly scheduled or with some randomness thrown in. So these are all the chaos CIDs. So when we started with chaos engineering project rate was we had let's say this part along this deployment alone called the chaos operator the rest that you're seeing here is part of 2.4. You initially had just the chaos operator and you could create a chaos engine manifest something like this we just have an application that you're defining by namespace, label and the kind these are the identifiers for a given application and you can basically go and run this experiment with a specific service account. It allows you to run your experiments with a defined set of permissions so you can choose who is doing the experiment and what permissions the persona has and therefore you can control what can be done as part of the experiment maybe provide permissions just say delete parts maybe nothing more. So you cannot do a more level experiment that way let us dance it into sort of a self-service model of experiments maybe there's a shared cluster different service orders and developers are running their own experiments you can still do that by adopting different service accounts and then you have something like this you have a total duration for which the chaos starts and then you have some tunables just to control the next of the experiment and we're going to do this experiment against a very simple service called as hello service it's a basically a hello world application that lives in demo space let me just take you to that it lives in a space name space called demo space it's just a part what I'm going to show is like the hello world of chaos engineering we're just still a part with one of the tests we provided this capability to create resources and run for it so you can actually see the part so people found it very convenient to make use of this in their scripts and automation pipelines cacd but things like that so you basically run the part the duration happens a few times we just set 30 seconds duration 10 second intervals it's going to move the kills two three times and you're going to get a chaos result and then you're going to get some events on the engine resource that might be of interest so you can actually see what's happening as part of the experiment it does a pre chaos check each experiment and red mess does a pre chaos check to see if the application that we're doing chaos on is in good state because we don't want to degrade an already degraded system so we make some checks and then we carry out the fault then we do some post checks and then we finish the experiment that is essentially what was available and you can see the gas injection is in progress like I showed you so this is going to complete the experiment and then just allow you to take a look at the results and see what happened to your applications you have your own influences that you can draw from what has happened so that is what we have you get the summary based on the constraints there are no constraints essentially in this experiment it's a the experiment passed because the only checks that we used to verify that it passed is whether the app was good before and whether it recovered after within a specific period of time but as we went along and I think I just just showing you the chaos result so the chaos result is quite simplistic in this case so you can see that the experiment was run once it passed and this was the target and it just ran right so this is very something that's very simple but real world scenarios are more different and real world requirements are more different so we sort of got that feedback as we went along the building the project in the open so we were asked how can I visualize the impact of chaos I have an application dashboard and I want to see exactly when chaos starts when it ends sort of how do I visualize the impact of chaos and I want to see what stage it is in of course the events are helpful but events is not for everybody there are a lot of Kubernetes is really democratized the way applications are operated so there are some personas involved that there are some folks who are very deep involved know the Kubernetes API very happy to navigate things like logs and events there are others who are looking at more graphical representations of a process dashboards so how do I visualize the impact of chaos and then how do I basically validate application behavior the word that you're telling me is too simplistic application health check application recovery after chaos is great but I want to see what's happening during the fault injection I have some SLOs that I want to validate maybe some IOs throughput latency that they want to validate even as the experiment runs how can I go ahead and do more faults maybe as part of the larger scenario like you mentioned some some minutes back we were talking about a case where your node is run to exertion and there's another correlation happening elsewhere you're stuck you're not what is in pending state how do I accelerate these kind of scenarios how do I do benchmarking I think many were mentioned about these cases where there's thousands of users using a platform at a single point of time how do I how do you simulate that load and then do fault there how does your system respond to faults under such loaded conditions is doing chaos in the utopian conditions is not great I don't want to do it in the ideal case what would have been this traffic that's full how do you do that basically do multiple things at once as part of the experiments a lot of pattern processes and how do you tell me in the precedence this is a metric that you can show and tell me this is how your fault or your experiment and your application of service is connected this is the metric that you have that says your application is resilient to this fault by this level by this much right and then there are other operational challenges how do I get different team members to comment collaborate on many chaos artifacts and visualize it how do I ensure that there's a single source of truth for case experiments yamels are great you can store them and get but GITOps is really the in thing I want to ensure that there's a change made on my GIT and the experiment definition needs to get changed on my cluster when it is around so how do you ensure that how do you use a single platform to target different environments we built upon this a little bit doing chaos in cubanities but also being chaos against other components while still running as an app on cubanities so how do you do all this these are the requirements that we got and we sort of spoke to the community and there are several meetups where we went and presented and we got talking to people and this is what we brought back into the project and built with it was 2.0 so the result is an architecture which basically gives you a single centralized cross cloud control plane we'd like to call it it's like a centralized management platform where you can connect one or more target environments of chaos depends on where you want your chaos to be done I have a fleet of clusters but I can use a single management platform to manage chaos against it so you have the self agent so this is the cluster on which the portal of the chaos center is installed it automatically registers itself as a candidate for a target environment for chaos then you could add other clusters as well essentially this is an execution plane you could do your chaos business logic on the same cluster where the cubanities control plane for chaos that is where the chaos center resides we can also use a different cluster as an execution plane so by doing that you're able to discard Microsoft's city on that cluster but you're just making use of you could also just be making use of that to run your parts your chaos parts targeting something that's totally not the varieties at all also and we have this ability to create workflows now instead of a single chaos engine that we saw getting created you can create a workflow that can stitch together more than one chaos engine in a different order panel or in sequence and you can also have load tests embedded within a workflow you could probably use locust or vegeta or k6 i o or a lot of other tools if i would probably that runs maybe as a job suspension things like that be known that the community is using today and that can be done if you can containerize then run that as part you can run that is one of the processes in the workflow along with the experiment so you get a better scenario the do test and we also have the analytics which does the comparison of workflows against what is called as a resilience score so the resilience score is essentially a metric that connects your experiment and your service so the resilience score is created or or calculated depending upon some importance or weightage that you give an experiment we see that very sharply and the success factor returned in the chaos result success factor itself is dependent upon some steady state variation constraints that you defined within the experiment using probes so you take the success factor and the weightage that you give the experiment you get a product and you get a summation of that product for several experiments that are listed within a workflow divided by the total points possible and you get a resilience score and that resilience score is something that you can use and you can use that to compare over a period of time and you can see how your experiment is sort of improving or whether it is reducing its resilience etc so that is about the analytics and it also has the option for you to sort of pick workflows chaos artifacts from a git repository so you can commit workflows that you construct around the on the chaos center on this wizard that is provided with the chaos center and that gets committed into your git repositories and any changes made that gets reflected here and the next time you run the workflow you run it with the new spec modified spec that you run and it also has a set of users that you can bring together as part of your team to collaborate in chaos and each individual gets a project into which you can invite users to form his team or her team and the users can be of several types you could create a user who is an admin a few only admin or just an editor etc different levels of users that you can use and you can collaborate on chaos so and it also has the chaos hub embedded within it very much inspired by the open-shift operator hub that's embedded within open-shift for context so we have the embedded chaos hub here so when you construct your workflows you can actually pick experiments from the hub and stitch them together and run it so these are all the capabilities that we created in response to the requirements that we gathered I will do a very quick set of demonstrations to show you how you can leverage this Mario was talking about e-commerce applications we've taken the example of an example e-banking app called the Lank Phantos which is comprised of several micro-services you can see that I have a bank of Anthos in the department space on this cluster I have links here just to make things easy in terms of visualization so you can see that there's a balanced reader application of service rather which is allowing me enabling me to read the balance here make payments do all sorts of things I've said this application without much resilience and what I'm going to do is inject a black hole attack something like very simple for a data attack maybe we're going to incubate the balanced reader service and that's going to give us a semi or quasi-operational e-banking application which is something you generally want to avoid so you can take a look how we do it we are just scheduling the workflow and selecting an execution environment and selecting the same cluster as where I'm at, it's the chaos center of the site and I go ahead and select the chaos hub from where I can pick my experiments you can define your own hub here as well if you're in a private environment you can create your chaos hub and pick experiments from there and then you go ahead and give a name I'm going to call it back of Anthos Backhole and we're just going to pick an experiment in this case network loss is the experiment I'm going to use to create this attack so once I've selected the experiment I can go ahead and tune it the way I need so I'm interested in the balanced reader service residing on the default namespace so I'm just going to select that I have the option of validating some behavior as I do the ford but I just keep it simple for this first round I'm just going to say next and I'm going to keep it intact the ford intact for 60 seconds this is going to be 100% network loss that we're going to inject so I'm going to say finish I'm going to say the word schedule fords so this is basically a feature that cleans up your TS resources or your customer sources that were created to do the ford afterwards I'm going to keep them just to show you the logs and this is the step I said where you can provide the baitage or criticality to your experiment we're going to give it all points you can do the ford once now or you can do a recurring schedule and what we're going to do is just do the ford once now and this is going to give us an argo workflow underneath it's going to construct an argo workflow where it has a couple of steps to pull the ford template for network loss and then actually run the experiment you can see the chaos engine is auto configured or created you don't have to create it by hand you can see the same thing that we saw last time with the pod delete that we did a few minutes back we have the balance reader being targeted in a particular namespace and we have the duration and other tables for the ford and just going to say finish so this is going to run the workflow can visualize what is happening as you do the ford and each step is going to get played out on the cluster through some transient parts that get created you can see first pulls the ford template and then it actually does the trigger of the chaos engine for this point Bancoventos was healthy and good so once the ford starts running you will be able to see that we can read the balance or make payments so like I said sometime back let us do some pre chaos some post chaos checks at this point the previous checks is to see whether the parts that carry this label that we just described is healthy and it is alive before it actually starts doing the font you can see that the step trigger the font has started you can use the the chaos engine schema is quite rich you can do a lot of things with it the documentation for that is available here you can take a look at the concept section and you can see all the the specifications that it contains and all that can be tuned so you can take a look at these sections here to see what all is terrible you can set resources you can define affinity policies to where this part is to go you can inject annotations into it you can define the amount of time that you spent trying to validate whether an application is alive a lot of things can be tuned but if setup is something very simple the font is active at this point so if I refresh this application you can see you cannot read the balance and I try to make a payment but that shouldn't go through because I cannot read the balance to see how much I have in my wallet to actually make the payment so these are some things we would really like to avoid in our applications we need to find the have the right middleware property to direct us to a different replica that is working and ensure things work and it is always risky that you have semi-operational applications for example I am able to make the pass but I cannot read how much I have to pass it and things like that so this was a very quick demonstration of how you can inject a font and how it runs and you will see that this experiment yeah this was this was wonderful sorry I didn't I didn't mean to cut you off I just wanted to I think so I think a lot of people think of down and up and they think binary about how a platform is operating it's just it's it's black and white right and that's not actually how most outages work most outages are actually kind of like a a brownout like a like a some things are working some things are not working the problem is that the totality of maybe some of the critical flows for using an application this example is fantastic that you that you use is that some things might stop working right and and things might seem okay but when a user actually goes to do something that's when dependency services other API endpoints are called and certain microservices that make up the overall platform are not doing their job as is expected I think that's one of the major use cases for this I'm loving this workflow dashboard I think this makes it easy for me to kind of again you know obviously the schedule interface you have here some of the agents and the hub stuff is fantastic so it's all tied together kind of all unified interface and I think like this is the next evolution of what it looks like to be comfortable feeling like you have the control to test your environment and the way you need to to really get the correct signal instead of just noise about like oh well you got this one pot using lots of resources you know that's one of many little things going on but there's a lot more signal that you need around the flows I think and what's actually happening in these certain scenarios so this is fantastic to see Karthik well you click around a little but I'm going to ask a couple of lightweight questions because we have just a few minutes left I think one of the big ones here that I'm thinking about is what is some of the key things what is the next step and you do a great job of talking about like what 2.0 is delivering versus 1.0 and so like what are the what's next on the roadmap what can we see here over the next few months as we end you know end of the year what should what is litmos looking to implement that has been like something you know huge that a lot of users have maybe been talking about or things that you've been asked about from people saying like hey you know I'm using this and if it did x, y and z I would be so much more efficient right be able to really nail down certain things what are those things look like for you and the team it's a great question so what are the things that we we're being asked is to improve it's exactly what you mentioned it's about you want to see what's happening to your applications it's it's not about it's it's not binary it's it's brown out generally and you want to but validate a lot of things get insights into a lot of things that's happening on the cluster even as we do the part so sprobes is one thing that we introduced to help do that for example in this case I'm just repeating the fault that it did at the 1.x experiment where we're trying to kill a part but along the way we are doing some checks we're checking whether a downstream application is always alive I am basically checking if it's always going to be alive there's a 200 okay that I get against it for a polling interval of every one second if it is not then probably I would like to abort the experiment so I can say stop and feel you true so these are things how do how do I abort based on conditions how can I have a dead man's switch so to say as I don't fault to sort of auto stop and what are the different kinds of probes that I can I can probably these probes today that's basically using for me this matrix to check division in your study state maybe is it is it under your SLOs or no so I support for different kinds of probes that work in different observability tools that are there in the in the CNC landscape today that's one of the things that we've been asked and we're working towards and more experiments for non-cubanities environments so that's something that we're working towards as well Azure, AWS, GCP these are some of the being where this is more the environments where people are still running a lot of their services in and we have initial set of experiments there but there's a request for being able to add more and from folks that who are trying to use this in enterprise environments who also want support for different kinds of authentication and authorization mechanisms as as to how people can access the kiosk internet on it so that is one of the things that we are looking forward into the identity roadmap as well and there are other fault types within cubanities that we can add faults are like thousands of faults that you can actually do using a base set of faults you can create thousands of sedans use rather so it first provides you a good set in the kiosk but we are committed to increasing that set of faults for cubanities and non-cubanities and also provide a resilience a very resilience view that people can make use of analytics and resilience scores are great but there are other things people would like to know about when they run the experiments approach and stuff in their direction people also want to know things about how their recovery was how much time did it take really maybe it was under the limits but how much under the limits is that something that people can improve upon how do you get better rate how do you provide better insights to people who are practicing kiosk engineering that's something that we're going towards that's awesome this is all fantastic yeah we just have one more minute I want to end on a strong note for people that are looking to dip their toes in and get started and maybe even evangelize this a little bit in their organization or play around in a kind of lower end environment like a dev environment of playground what would you say what's kind of the the best way for them to get started understanding kiosk engineering and starting to leverage it in their day to day on their laptops whatever they're trying to do what are some resources yeah I think we have done a fair bit of refactoring on the docs as well as part of the one that takes 2.0 so this is the docs Dr. Panskeas.io there are a lot of resources here that you can use to learn some of it is still coming in but there's a good sort of good sort of concepts docs that if you could use here to learn about it was and you also have experiment documentation there's a lot of information about how you can run each experiment the different variables that it provides and how you can run it with different options all that information for example is we talk about part of it there are different ways in which you can run part of it a lot of which is explained here so this I would recommend are a couple of good resources the docs and the pages of the repository itself that's about where you can find information about it must but when it comes to general information about chaos engineering you can take a look at the principles of chaos engineering and CNCF was just started with a chaos engineering work group which is trying to actively put together information about chaos engineering for beginners and for practitioners who've been doing chaos engineering for a long time and then jump into a cloud native world and looking at doing chaos engineering and cloud native way we meet once in two weeks and we're trying to put together a white paper that talks about chaos engineering there is some information for example if you're looking at common terminologies associated with chaos engineering this dictionary that we're creating talks about chaos engineering it's not really alphabetically sorted glossary it's more about chaos engineering as your element so you sort of come to principles and then you talk about what is an experiment and how you can sort of understand each part of the experiment glossary is hypothesis SLI's and SLO's and how you can practice it as an SR you know you can conduct game days information that we're trying to expand upon so this is probably good space to look out for for sure yeah this is perfect I did not know there was a working group that is amazing to hear thank you very much Karthik so much great content today you really did some amazing demos as well and the demo gods are clearly with you litmuscaos.io chaos native is the company thank you to Karthik today and thank you for the people working behind the scenes my name is Mario Loria it's been a great great pleasure to host today's session and talk to everybody later to have a great rest of your day thank you so much bye bye thank you so much bye


Hi, welcome to the cover glass selection video for our direct time of flight sensors. I am Russell Wong, and in this video I will walk you through the critical step of picking the right cover glass for integrating our time of flight sensors into your application. Typically, our time of flight ranging module is used in conjunction with a window covering or cover glass. The cover glass serves the main purpose of providing physical protection to our time of flight sensor module. The cover window can be opaque with either one or two unpainted apertures to permit IR light to be emitted and received. The cover glass can be darkened to visible light, but should be still transparent to 940 nanometer invisible light. The cover glass must fulfill some optical and mechanical requirements in order to guarantee the optimal ranging performance. Let's focus on the optical requirements first. The two quality metrics are haze and transmission. Embedded particles, holes, and other rough surfaces are major contributors to light scattering in cover glass. In order to minimize the haze, an ideal cover glass window should have no structural defects in the plastic or glass material. No surface particles, defects, smudges, or fingerprints that could scatter light. Anti-reflectance coatings are not recommended. The fingerprint coatings have negative effects, but they might be better than the fingerprints themselves. Also cover glass transmission should be more than 90% in near IR in order to ensure the optimal ranging with the IR emitter and the receiver. There are also mechanical guidelines to be followed. 1. Small air gap. Less than 0.5mm will be perfect. 2. Consistent cover glass. One millimeter is a good thickness. 3. Consistent cover glass material with a tight tolerance on haze and thickness. And lastly, for optimal performance, the cover glass should be parallel to VL53 time of flight sensor. If it is not possible with industrial design to have a small air gap of less than half a millimeter and a cover glass thickness of one millimeter, then it is essential to place a gasket, a small piece of foam or rubber, between the top of our device and bottom of the cover glass, filling the space between the two surfaces. You need to put two holes or openings in your gasket, one for the emitter and one for the transmitter, to guide photons from the transmitter to the receiver. This gasket reduces undesired signal reflection off of the cover glass, which is called crosstalk. Crosstalk is an issue that can occur when placing a cover glass on top of our time of flight devices. So what is crosstalk? The crosstalk is defined as a signal from the emitter that takes a wrong path and gets into the receiver. The red line shows the undesirable crosstalk path. The green line in the figure shows the intended optical path. In this case, light is emitted from the VIXL, hits the target, and is received in the SPAT array, resulting in the correct distance reading. When a cover glass is introduced, the photons can reflect off of the cover glass, buzzing between the device and the cover glass multiple times before traveling to the receiver, which will read at a very short distance instead of the total range. Our time flight sensors can tolerate and in some cases compensate for a certain amount of crosstalk, but the crosstalk needs to be minimized in order to ensure the optimal performance of the device. Our aim in this presentation was to show you the best cover glass properties that will give you the least amount of crosstalk, but on top of that, you need to do calibration in order to get rid of the remaining crosstalk. The gasket helps to prevent the photons from following the red path. In this figure, we show the effect of the cover glass on ranging. The green dotted line is the ideal. The red line is what happens when you add a poorly selected cover glass, and the blue line is what happens when you have a very poor cover glass. The worse the quality of the cover glass, the higher the air at longer distances. Once the crosstalk is quantified, crosstalk compensation can be applied through the calibration procedure. Crosstalk compensation is a feature embedded in the APIs for all ST time flight sensors. With our newer histogram based time flight sensors, the crosstalk issue disappears at longer distances, but you will need to account for it. For more on crosstalk characterization and the calibration process, please refer to the API user manual for the sensor you are using, as well as the additional videos on cover glass, crosstalk, and calibration. In conclusion, there are both optical and mechanical considerations in order to pick a correct cover glass for your time flight sensor. When it comes to the optical characterization, the clear cover glass with optical transmission of 90% or higher is recommended. The cover window must pass through the IR light at 940 nanometers. Any loss of signal will directly affect the VL53L5CX performance. Choose a smooth cover glass with low haze. Haze is a measurement of roughness and particle inclusion in the glass. Factors for both transmission and haze should be provided by the cover glass vendor. Choose a cover glass material made of glass or plastic with no anti-reflectance coating. Dirt, smudges, fingerprints, grease, dust, water, or anything that can be on top of the cover glass will increase your crosstalk, avoided as much as possible. Here are some mechanical considerations. Tight air gap. The closer the glass is to the sensor, the better. Try for an air gap of less than one millimeter. Parallel. Try to keep the glass parallel to the sensor. Thin cover glass. The thinner, the better. One millimeter is a good thickness for cover glass. For more information and application support for VL53L5CX or any of our time flight sensors, please refer to st.com slash time of flight. And remember, our technology always starts with you.


Hi this is Kimberly at Mountain View Dodge. It's the beginning of the month. We just received our new list of 30% off vehicles. We have trucks and a few vans so if you want more details come on in and see me. It's too cold out here to stand here and tell you everything about all these amazing trucks so come on in Mountain View Dodge. Talk to Kimberly<PHONE_NUMBER>


I found a basketball court. I'm traveling, so I was like, I'm gonna do a talk. Talk a little bit, talk about making your first million. We'll talk about Airbnb and real estate. So if you look at the net worth of the world, they say it's about 350 trillion dollars is the net worth of all the assets in the world. So about 250 million of it is estimated to be real estate.  For me, I try to have 60% of my assets in one category of my net worth, 30% in another, and then I have a subset that's 10, right? So e-com, buying businesses, brands, that's my 60%, and then 30% can be for me, it depends on the year, how you count it, real estate, or what I do with my personal brand and my consulting. So that's kind of three activities. So some of you, some people love real estate, they make real estate their primary focus. Airbnb is the simplest way. I've got properties, for example, where some of them I own and I Airbnb out and some of them you can just lease and arbitrage the lease. So I should do a couple giveaways. It's been a while since I did a basketball giveaway. Somebody said, tied you on a Lamborghini. I sold my Lamborghini. I'm gonna get another one. I had two. I sold them because I was in Puerto Rico. You can't really use a Lambo in Puerto Rico. Too many potholes. Way too many potholes in Puerto Rico for a Lambo. There you need basically a truck, man. Okay, so I'm gonna do kind of Q&A on somebody said help me. Okay, you're gonna have to be more specific. Big man tie. What are you most excited about right now? So I would say, look, a recession is most likely coming. I live by this kind of saying that Warren Buffett came up with, when everybody's greedy, you should be scared. And when everybody's scared, you should be greedy.  You can just say, when everybody's scared, you should be excited. When everybody's excited, you should be scared. So the last year, everybody was excited. Everybody was making money and everything they touched. They're like, oh, I do crypto and I triple my money and, you know, I'm in the stock market and I've tripled my money. But when the tide comes in, you see who's swimming naked. And what that means is, what that's saying means is the masses never know what they're doing. So when the masses are excited, you know something wrong is about to happen. Okay, I need to do one of my giveaways, Dez. How many shots can I hit? 10 out of 10. Out of 10. There's one. What I'm excited about is the fact that now they're going to be buying opportunities. Basically, it's been at what's called a sellers market. For the last two years, it's been a sellers market. The government injected a large amount of cash into the economy. Basically, if you look at M1, the money supply, it went insanity, you know. I forget the number. It went to like 18, just a wild number. And when that happens, they get asset inflation. So you saw that on stock market, saw it in real estate, and everybody thought it's easy to make money in these asset classes. Crypto had the same thing.  And now it's no longer a sellers market. It's a buyer's market. If you went to buy a piece of real estate or buy, I buy businesses, I buy real estate, I buy assets, you know, I've deployed over $200 million in the last two years buying assets of different types. I bought PR1 for $31 million, you know, stuff like that. And I don't like it when you go and there's 50 people there trying to buy the same thing. You're always going to get overcharged always. So what you're looking for is the timing of the market. Now, some people say you can't time the market. They're talking about stocks, but you can definitely time the market when it comes to macro events and when you deploy your capital for sure.   You better time it. And the simple way to know how to time it is just when everybody's excited. J.P. Morgan, I think, was J.P. Morgan in the 1920s. He said he knew that Great Depression was coming. Why? He said his shoeshine boy was giving them advice. So you look at how the world is and you look at people who have never studied to show themselves approved. There's a Bible saying, study to show thyself approved.  That's a good signal that you're at the top of the market and you should sell. I bought a property piece of real estate in Puerto Rico. I'll get ready to make a video. I'm going to show all the details, show the people, now everybody's cynical. But I bought it for 4.4 million and 14 months later I sold it for 8 million. So that's timing the top of the market. I bought it low 4.4 and 14 months later at the peak, which was basically the first quarter of this year, I sold it for 8 million cash. Anyway, to answer the question of what I'm excited about, more opportunities like that are going to come right now. My back in the US, no, not right now. I talk about different stuff. Ecom is certainly, I can show, actually my phone is live streaming, but in Ecom, I'm doing some of my brands do 100 grand a day. If you look at my whole retail, I'm on track to do 800 million in the companies that I control, all the different brands. You can go to retail e-commerce ventures. This year we'll do over 800 million in top line revenue. So obviously Ecom and retail is something that I'm big in. I'm the executive chairman of a publicly traded NASDAQ retailer called Tuesday Morning. And so you can see those are public numbers too. But those kind of things for beginners, if you're watching, you're not going to start by building a large conglomerate holding company. I wouldn't do that way. What I would do is start, you can start with a simple Amazon drop shipping or you can start with a Shopify or I built some software called Brahms. That's better than Shopify. You can start there. That can be one of your 60, 30, 10 net worth kind of goals. And then real estate is certainly good. You can arbitrage. You can sublease something. I was looking at a place that I used to live in Hollywood. It sold for $2.1 million. Man, it went sold in an auction actually. I wasn't in Cal, I had moved out of California, but I was thinking, damn, I should have bought that $2.1 million because you could have rented out for $50,000 a month. So basically you could have made $500 a year net NOI on a $2 million investment. That's crazy money. That's 20%-ish depending on what your expenses are. And you can do that with Airbnb. And people are traveling right now. So travel is still happening. You know what I'm saying? Why didn't I buy it? Because I wasn't living in California. But I'll tell you, if you don't have the money, so obviously when I started out, I didn't have money to buy a property.  A lot of them are buying it as investments. Say, I'll manage it for you and I'll take 20% of the profits just for management.  You find, I like, go to the right places. Hollywood is a good place. There'll always be people doing Airbnb, always. So you see that that's sold. It's a Hollywood Hills house, $2 million. You reach out to the owner. It's not that hard to find them and you say, hey, I do Airbnb property management. I only make money if you make money. So you don't charge them a fee. You just say, I only make money if you make money. I'll do all the work. You can sleep good. A lot of out of town people buy places and luxury places like California, like Hollywood, like Miami. And you take 20%. You should be able on that property is not hard for it to rent for roughly 3000, 2000 to 3000 a night, depending if it's off season, high season or not. Guess what? Let's say you can rent on average. Let's say you can rent it and you're going to have obviously some vacancy. You're not always going to have it rented out, but you can keep stuff rented in Hollywood year round. The weather is good. People flying in, a hotel is expensive. Think of it, a hotel room in Hollywood is like, let's say a good one's 500 bucks a night minimum. And people come on average with three or four people. Three rooms is 1500 bucks. If you rent out that house for 1500, that's 500 grand a year. You take 20%, you got $100,000 from one property you don't even own. Who said I can't ball? I know you don't think that. This must be your first live stream with me. I used to do every year me and Chris Paul, I would do a one-on-one against Chris Paul.  Metal world peace, one-on-one, NBA defensive player of the year. He got surprised. He didn't know I could play. You got me in slow-mo? That was good. All right, you got to step back. He's tall. He's like six, eight long arms. You got to step back for a far three. I'll take people's money. I had an NBA, I had a guy come to my house as a pro basketball player in Germany, not in the NBA. And I embarrassed him on camera. He's like, please bro, don't post that. That was just horse. That was just a three-point contest. Some of those shots, I can hit like a pro, but I can't beat a pro. These NBA guys are not possible to beat. Did Chris Paul miss? So basically I had a bet, it was Steve Ballmer, that if I beat Chris Paul, he'll give me a 10-day contract to play for the LA Clippers. That one, Chris Paul, was tough. Ty, are you natty? Yeah, I'm not that big. Do I look? I appreciate the compliment. Do I look like I'm on steroids? Do I look like I'm on steroids? I don't think so. All right. Right when I brag about how I can hit shots, then I start missing. That's how the game goes. But not for long. That's how you trick them. You got to miss a few.  Duck eggs are great, man. They have a lot. If you look at them, ducks forage more than chickens. I have 1,300 acres of farmland and organic farms. So I got about 5,000 chickens. So I mean, these 200 shots I got to make, actually what you want to do, what I got this aura ring on, this thing tracks my steps. It's great, man. The worst thing, I'm reading this book, Exercise by Lieberman. He's a Harvard paleoanthropologist. Humans are meant to walk approximately, men in hunter-gatherer societies walk 10 miles a day. It's about 20,000 steps, which is pretty interesting.  People that are basically sitting too much, it weakens the back. So anyway, I like to do business while I'm on a basketball court. I do all kinds of stuff on my phone. You could run an empire from a phone. Would you buy land in Florida? Sure. But I like stuff that cash flows. I bought, you know, I own farms that have operating farmland. I was looking, you can look, I mean, America has the best farmland in the world. The best. Ukraine is obviously good. Saskatchewan, the pompous of Argentina is good, but the US, the center of the US, the glaciated soils, it's a great investment. I was telling people to buy farmland. 2019, I shot a video. Man, that land was at 7,000 an acre, and now it's 20,000 an acre. It's insane. But a recession is coming, and there will be plenty of buying opportunities. So build your skill. My recommendation for you is start doing an Airbnb property. There's a guy in London. I shot a video about this. He made $18 million through an Airbnb in one year, 18 mil, 18 mil. Somebody told me that's the first shot I swish. You actually don't want to swish. But he talked to, like I used to train with lethal shooter. Remember that lethal shooter used to train me? Now he's huge. He's training everybody. He used to come over to my house. He said I was the first guy influencer to give him a chance. Now he's massive. He's training the MBAs, Drake, all these guys. You want to hit the back of the rim, man. See, that was a swish. I don't really like that. That's not really a goal. It's a good analogy for business. Like basically in business, you want to make your first million, overshoot it a little bit. Try to make a million bucks a year, and you'll probably make, you know, a tenth of your goal. So you'll make 100 Gs. You know what I'm saying? Do I have a plane? No, I usually charter them. It's better to, I'm, I've thought of buying a jet. The problem with buying a jet is I own a lot of farmland. If you have a big jet, a lot of the landing, a lot of the landing strips that I go to, they can't take a big jet. So if you have a golf stream and you try to land in my farms like in Ohio in that area, the runway is not long enough.  So it's chartering is, I like chartering, although the charter market's pretty tight, so I've thought of buying now. Ask me to swish again. There was a swish. I wonder if they're closing up the park because it looks like somebody's coming to talk to me. Are you rich? Depends who you compare me to. Depends who you compare me to. Hello? Are you closing the park? Oh, even if nobody's here? I'm not actually filming. I'm on a live, I'm doing a live stream. But okay, I can cut it off. Can I do like five more minutes and I'll cut it off? But they implemented a rule that just banned all tripods. Oh, it's the tripods, that's the problem. Okay, we'll get rid of the tripod. That's good. Okay, I will fix it. Okay, so can you give me five minutes and I'll get rid of all this stuff? Thank you. Okay, I appreciate it. So I found out I got a rule here. I got to get rid of this. That's okay. It's not a big deal. Roll with the punches, man. Okay, let me just have this one. Give me a second, everybody. Just pull these out.  But would I consider myself a narcissist? I've done a narcissist. You're 57. I think narcissism is higher.  I don't know if people are going to be able to see. I could hold this one. It seemed to be fine. Yeah. Can they see you like this? Why does this look zoomed in? Yeah, you guys zoomed in. Okay, there we go. Okay, I got Des here. Here, can you put the tripod away? Let's put the tripod away. I'll hold that for a second. Anyway, what a world. What basketball trainer are we talking about? His name is lethal shooter. Ty, you're looking young. Keep moving, man. Keep moving.  Steve Jobs said he didn't want to be the richest man in the graveyard, but he was.  Never treat diet like a cult. There's a great book called Diet Colts, and it's true. People just have these wacky understandings. You can't eat 500 bananas a day and be healthy. You're going to disturb. Guess what he died of? Pancreas issues. Well, if you know anything about sugar, it's not surprising. Eat it diversified. Most important thing is eat off my farm. I got farms. I got my own milk cow. We milk them by hand. We've got eaten grass. Same with chickens. All the wealth in the world doesn't matter if you literally die, which I meet all these wealthy guys that are fat, out of shape. You should be walking, try to hit 20,000 steps a day. You can be on the phone. I do all my business on the phone. You can build an empire off a phone.  Old school phone still works. Why don't you flip that one around so that you can see where it's from? Shooter, I wonder if he's going to be here. I should ping the audience. Give you a good book to read. Let me say Gray Sweat Pants. Ty, I made a million with your first business, but the business ended. What happened with the first business? Remember, I called the 10-10-10 rule. You want a business that has the capacity to do at least $10 million of revenue for the next 10 years with ideally less than 10 units of brain damage. That's the holy grail. Now, as you get more advanced, you can change that from $10 million a year to $10 million a month. I still follow the 10-10-10 rule.  It always takes a lot of brain damage at the beginning to build a business, but can the brain damage taper off? So I like to build what I call front-end loaded businesses, businesses that take a lot of work at the beginning, but then they somewhat go on autopilot. They'll never go fully on autopilot. Gray Sweat Pants apparently are a problem. King Cap is back. Shit. All y'all motherfuckers that you thought were real and you thought I was Cap? I like to laugh last.   They're not even doing $50. They're not even doing $50. So don't get too...  You know the truth about this world? I'm a sheep in wolf's clothing. I'm a sheep in wolf's clothing. That means I tell you the truth, but I appear to be a wolf.   You know what I'm saying? People are like, ah, Ty doesn't know about real estate. Then I went and bought 1200 acres of land just recently. Then I just bought, I showed you this piece of Puerto Rico real estate, bought it, flipped it in about a four mil, flipped it for eight mil. People thought I'll, Ty doesn't know anything about operating businesses. Now I've got big brands that I own, passing 800 million this year in revenue. 8,000 people work for me.  You know what I'm saying?   So I had videos with Lamborghinis and beautiful women and night clubs and people go, that can't possibly make money.  It's not true, man. I know many billionaires that tell you they don't care about money. They all care about money. All of them. Even the ones at the top that say they don't care. It's better to follow a sheep who's in wolf clothing than it is to follow a wolf who's disguised himself in sheep's clothing. That's what most of you have done. You know, think about it. The school system is a wolf disguised in sheep clothing. Everybody says they want to help the children and they're doing things in the education system and how great it, how, you know, how the great intentions they are. They may have it, but they're a wolf feet down. U.S. college system has two, I was the first one talking about the $2 trillion college debt. How, and you can't even discharge it with bankruptcy. It's a complete scam.  That was the beginning of saying, Ty's encouraging people not to go to college. Well, damn right. For some professions, you should go to college. But why are you going to call it for a business degree? You learn business by doing business. That's what you do. Making your first million is mostly going to come from hyperactivity. Hyper experimentation and hyperactivity.  And if you're going and looking, in this case, if you want to do short-term rental properties, if you're looking at 50 properties a month, you're sending letters to people, you're sending emails, you're DMing, if you've got a social media agency, if you're hyperactive. In fact, one of the personality traits of people who make above average income is what's called hypomania. Hypomania means people who have insane levels of energy. Now, some of that's genetic and some of it's ambition and some of it is diet. A lot of people have shitty bad habits. You need to go 10 for 10. Let's see if you've got a 10. He jinxed it. 0 for 3. 1 for 4. It ain't over. It's going to be for money. This one I'm going to fail on. Take my glasses off. 3 for 9. 4. 3 for 10. I'm out here shooting like the Lakers. I'm shooting like Lakers. Now, who's the lucky person that wants to bet me money? Who wants to bet me money? That's what I need. Someone said, I bet you 100 million. You can't make 10 shots in a row. 100 million? Don't bet me that much. Who wants to bet 500 bucks? I'm going to get your name. If I win, you send me 500 bucks in crypto. How many shots do I have to hit? You made me too tough of a bet. I'm not going to do it. Okay. Say you're a bet. What do I have to hit? Ty, I make 2 million a year from a single business. Hold on. Should I start a new business or focus on one income source? Don't get rid of the business, making you a million bucks a year. What you can do, what I like to do is just continue 60, 30, 10 rule. Make that your 60% and expand the thing out. Bring in a manager. I bring a COO in. Don't try to bring in a CEO. A lot of people say they're going to bring in a CEO. It's too hard.  You're the CEO. I got to snap out of it just like a wife. Ladies and gentlemen, all day long, time is six in a row. I'm unfasable. Y'all will, you know, a good thing in life. Be calm under pressure. Be unfasable. People talk about alphas and all this. The actual true science, if you want to talk about what an alpha is, if you want to know the real thing, it's not what people are defining an alpha as. The real definition of an alpha is somebody who's calm under extreme circumstances. That's what makes you an alpha. It's not about masculinity, femininity, so it's literally who stays calm under pressure when everybody freaks out. I'm on a Lakers street. I'm on a Lakers street, guys. Someone said they'll give you 500 if you can kick it in. Please comment. I'm going to do a bet. Who's somebody's going to bet? Let the get. I said something. What did someone say? I only have to hit six. How many do I have to hit? Be the CEO. Yeah, in general, trying to find a CEO is a losing battle. That's why Elon Musk is the CEO of Tesla. He didn't start Tesla, but he made himself the CEO. But you can. What I recommend is getting yourself a COO. That's the most important person you can hire is a COO. That's kind of your second-in-command.  So who's out here doing short-term real estate? Am I in Europe right now? I'm in Europe. I was thinking, take off the top and just hold it myself without the tripod. Right now? We got a new idea. We got a new idea. Okay.  Okay. A king is not affected by the emotions of others. Something like that. So good about Airbnb during recession. It's going to be a different kind of recession. I mean, technically we've been in recession. What basically happened is people still travel. There's still a lot of money. The M1 money supply is insanely large. And so guess what happened? People are actually, you can position Airbnb as a cheaper alternative. For example, when I travel with my staff, I got to get them all, you know, hotel rooms individually. Hotels like in Europe right now are like even a dinky one's like 500 bucks. So if I get them an Airbnb house, you can put five people in one spot. Even if I have to pay 1500 bucks, I'm saving $500 a pop. So at the end of the day, I can actually, I can split this one. Yeah, that's good. Okay. This one just come down with it. Well, I can move this to the side. That's good. Okay. I got my step. This is my tripod thing. It's uncomfortable. Anyway, so what was I talking about? It was better. Watch out for my glasses. I'll put them back on. Anyway, so, oh, Airbnb, what's so good about it during recession? Like I said, travel is still happening at an insane pace. Theoretically, yes, you could get a slowdown in Airbnb. And that's why I said you got to pick the location right.  A link is from the Airbnb stuff. Ask them. I'm going to put a link. I launched a course in 2017 on how to do short term Airbnb. And I'm going to bring that back because the opportunity is here because here's what happened in a recession, all the people who own homes, they want income. So a lot of people own two or three homes. If you find them, you don't even have to buy the home. Like I try to buy the property myself.  So it's literally, you're going to make 100 grand from one property you manage that you don't even own. I would focus on big places with a big audience. Miami, Hollywood, basically luxury places, London, London's getting destroyed. Their real estate market is just crashing. The largest it's crashed in the last probably 20, 30 years. Ty, I've been following you 27, crazy time has gone by. Exactly. World's changed a bit, but not that much, but not as much as you think, man. Not as much as you think. Would you agree that Toronto is good for private property management? Remember, I wouldn't do private property management per se. I'm talking about Airbnb stuff. You can get premiums. Short-term rental stuff, you can get premiums. So if you're just doing property management, there's no asymmetrical return potential, you know. Is drop shipping worth it? Yes, if you know how to do it. If you know how to do it and you find niche products and really you need to know how to make viral videos, it's like how about trading forex? I don't trade forex that much myself, but some people swear by forex, man. Yo, Ty, where are you living these days? I'm all over, man. I'm the next year. I'm basically going on a one year. I need to be in like 50 cities. So I'm working on deals, looking to buy assets. Next 18 months will be a great time if you know how to invest. Great time. Better than 2020. Better than 2020. 2020 was a great time to buy assets. COVID, everybody was scared. Some people literally thought the world would end. I knew that there's a low chance that it's going to end. Stay calm under pressure, man. Stay calm under pressure. The thing about the modern world is basically everybody's habits are now recognized as some kind of protected system. You know, that's the main problem in the world. Everybody's bad habits are now protected. It's like, okay, if somebody has anxiety, it's like, oh, that's a protected system.   People freak out. So it's fine. Don't try to fight it. Let it happen. You just be different yourself. And remember, evolution is a comparative game. So to the extent that the masses act stupidly, it's to your advantage. Why do you care? You know, people are always trying to change the masses, but the masses have always been the masses. In the 1800s, that's why Pharoah said the mass of men, what's called resignation is confirmed desperation. That was in the 1800s.  And that's because humans are very herd animal. You know, I have cows on my farm. They're programmed to follow the herd sheep too. And you have a few species that aren't herd animals so much. You know, even goats. Goats are in a herd, but not as much. Goats can be independent much more. I have some bald eagles on my farm in the U.S. They fly solo. And I don't think you should fly solo, but a small group is what you need. And you basically make moves contrarian. So everybody is going to sell their assets in the next 18 months, liquidate into cash. It's already happening. I saw the chart economists posted a chart of money moving into money markets right now. It's just insane in the last quarter. People are selling because their stock ticker shows that their asset has gone down in value, but if they wouldn't sell, people don't understand how the stock market works. What drives the prices down are more people selling. It's not an actual change in the fundamentals of the business. Now sometimes people sell for good reason, but oftentimes people are just selling because they're watching the ticker. If you look at the people that have made money, look at Elon Musk. He's a distressed asset buyer. 2003, two guys start Tesla. Elon Musk comes a few years later when they need cash. He drops 6 million. 6.1 million was his first investment in Tesla. Then I think he put in 30 later. For every 100,000 he's put in, here's the insane number. For every 100 grand, Elon Musk deployed into a distressed asset. He's made 900 million back. That's insane. He's a true red belt. He's a red belt investor. There are not many red belts out there. I might be a black belt when I ain't a red belt. A red belt, a red belt is a whole other level. It's the same with Jiu Jitsu, you know? Can you not? Did my audio cut off? What do I think about? Oh, low connection. Thoughts on SMMA? I just launched a new version of SMMA. That's badass. It's basically charge people, charge business owners $2,800 a month to do their viral marketing. Back in 2016, SMMA, you were doing their Facebook ads, but that cost them money. Now you go to business owners and you say, hey, cosmetic surgeon, dentist, lawyer, what if I can get you customers for free? The only cost is my time. We use YouTube shorts, Instagram rules, Facebook reels, and TikToks to create virality. I've been messing around with YouTube shorts. It's insane. Insane. I've got a 90 million view short and you can repurpose other people's content. So Dez's arms starting to get tired. I have, this is my arm workout. If you don't follow me on TikTok, press the follow button. Any advice for a high-end jeweler based in the US? You're gonna have to double down on marketing. Last year, TikTok spent 19 billion on marketing. Isn't that insane? When recessions happen and customers get tighter with their money and they get picked here, so you're gonna have to deploy more money into marketing. It's kind of counterintuitive. Most people think you should spend on marketing when the economy is hot, but it needs to be the other way. You bought a lot of boxes filled with books, sell them on Amazon. Jeff Bezos got rich on books. Elon Musk, his sister just posted something and said, when Elon was growing up, he read two books a day. People got mad that I said, I read a book a day. I'm like, man, I wasn't ambitious enough. I should have been on that two book a day, two book a day. All right, I'm gonna go. Did they give you the link? I'm gonna put a link if you want to learn more about Airbnb stuff, short-term rental. Hold on, let me get the ball. Let me get a link, ladies and gentlemen. Give me a second. Oh, they're getting it. Knowledge, somebody said. It's a funny thing that I'm known for knowledge. It's like the greatest thing I could be known for.  It's a combination of action, but don't ever get it twisted up and think that action alone fixes everything.  The people who work the hardest in the world do not necessarily make the most money. If that's true, my mom, when she was a single mom working two jobs a day, would have been making above average income, but no, I grew up in a mobile home. It wasn't just frenetic energy, which is what a lot of people have and think that the, is the remedy. Yeah, there you go. A lot of people think that's the remedy for your situation. Obviously, you need activity, but you need guided activity. To the extent you know things that are practical and applicable, like I said, do you know how to invest your money? A lot of people think, well, it's this and that. No, but I mean, do you know like the in and outs? I'm talking about short-term rentals. Like, do you know how to drop a contract with a lawyer? But just remember, I don't ever leave anything just to lawyers. I probably spend five to 10 million dollars a year on lawyers. I oversee what they're doing. Do you know how to do that? To the extent that you know how to do that, that's a piece of knowledge that you have to have, and some of you don't have it. And so, action should be a consequence of knowledge. So, it doesn't mean you have to go to four years of college where you take no action, don't start a business, and you're paralyzed. They can be somewhat concurrent, but I like to know before I do. Some people argue, and they'll say, no, it's better to, you know, it's better to do without knowing. Well, that'll get you killed, man. The first time I met Elon Musk at a movie theater, The Grove, and I asked him how he learned to build SpaceX, and he said, I bought a whole bunch of books. I got video, go to my Instagram, scroll back, talking to Elon Musk about books. The man loves books. He became the richest man in the world, second richest man in the world. Jeff Bezos loved books so much that he launched a business selling books. That said, there are other ways to learn. A great way to learn is shadow. You want to learn real estate investing?  Shadow them. If you got to be the person who buys them coffee and donuts, who cares? A lot of people have too much pride for that, and they're like, Ty, do you know who I am?  Don't have pride before you have the ingredients to have that pride.   Come back when you can bench 500 pounds. Now, you can have confidence in yourself, but everybody's an entitled world. The Chinese are making money on TikTok by feeding the entitlement of people. It's a very genius play. I mean, I can't think of it. If you appeal to the narcissism of humans, it's going to go well for you in the sense that people will mass adopt. If you go on a date with somebody and you make them feel like they're the most important person in the world, that's a method of seduction, but it's not necessarily authentic seduction. I actually watched a video today, TikTok, where a woman who says she's a diagnosed sociopath, and her secret is she overwhelms people by making them feel good about themselves. And that's what we have in the modern world, what goes viral when you make people feel good about themselves. And when you make people not feel good about themselves, you get penalized. But that's to the detriment of people. A weak world society benefits nobody. You should make it your goal in the next two months that you have your first Airbnb property, whether you buy it or whether you leverage someone else's ownership. That's a great thing to do. That's a great thing to do. Then you can feel good about yourself because of the accomplishment that you did. And some people, look, I know there's other schools of thought that you should feel good about yourself without having to do anything. Look, we can agree to disagree and there's pros and cons to both approaches. You can take either one to a too extreme of a way. I can love myself even when I'm not accomplishing things or failing, but you can take it too far. Pain exists for a purpose. Pain exists as a motivator. Pain is your brain's way of saying move, pivot, change, stop, doing what you're doing. And so to the extent that you mask that and tell people, no, you're just perfect how you are. You're overriding the pain that people feel and that you're overriding the pain that has a purpose. And it's sad.   I'm a tribal approach to this world. And it doesn't mean I hate other people. Sigmund Freud said it well, if I love everybody, then I don't have enough love and time and energy to love the people who are deserving of my love.  I don't have any, they don't have love for me and I don't have love for them. And that's fine. That's how it's meant to be. And there's nothing wrong. I don't have to feel guilty, you know? It's the best Freud book. The best book almost ever written is Civilization and It's Discontent. That's a Sigmund Freud book that is so good nobody knows about it. The second chapter of Civilization is Discontents is you could basically say every social media post that was done in the last five years, you could assign them a value quotient and you could add that all together and it wouldn't be as valuable as that second chapter of Sigmund Freud's book. Now, it doesn't mean everything that Sigmund Freud said was accurate. He obviously had some concepts that are now disproven but the man was a genius. It is the smartest guy I've ever read and everybody who says he's not that smart, I'm like, you haven't read him.  They don't let you actually hear what people say but they make fun of people before you let them hear what they say. But when you actually hear them, you're like, wow, that person's pretty smart. Best book is 1984. Yeah, that's a pretty good book. Hello from Denmark. Yes. One thing I see for sure is Ty is handsome and fit. Great. Tell that to everybody.  It's funny. There's two schools of thoughts about my look because there's no in between. Always believedly positive. No, as long as it's the guys that think I'm ugly, not my target market. I don't care. I don't care. Somebody said, yeah, feed Ty's ego. It doesn't affect me. It makes me laugh. History of civilization. You mean the story of civilization? Yeah, by Will Durant. Somebody wrote the word biological imperative a lot. Not sure. Somebody said, oh, let me put this link to this. What was it again? If you want to, if you want to start doing short term Airbnb real estate, I built this program in 2017 and I've got all kinds of updates on how to do it in 2022, 2023. It's tylovis.com slash Airbnb one. I'll just pin this real quick. All right, we'll pin this. Can you let's see the jump shot. Man, I've been shooting this whole time. Or you can comment on your own fucking. Oh, here it is. Oh, you can do polls. Let's do a poll. I'm going to let you do this. Okay, Des, can you turn it around and do it yourself? Okay, how do I do this? This is being shot. I already did Instagram. How do you do this one? Turn it this way. No, just that one. That one's already turned. Yeah, this one's turning the wrong one. I was going to turn them face into you while I pin it. No, I want you to see you. No.  Yeah, it was enhanced right there and then flip camera. Imagine you have to go to enhance to flip the camera. That is insane. Oh my God, my arm is dying. You got to switch arms. There. That's the fix my hair. Des, you got this backwards?  Des does not want to be seen. There you go. She does not care. Oh, that one looks dark. Okay, there you go. Okay, you won't hear. I'll help you here. Okay. Do you want me to pin it? Yeah. I commented it somewhere on here. Someone said it's tight. Is this a prison? I don't know why they have a basket there. They got a basketball court. People crack me up, man. Where do you post your own comments? I don't think you can on here. TikTok, you have to be able to post your own comments. That would be insane. Ray Dalio is the changing world, new world order. Don't worry about the new world order, man.   No, it's not there. I'm telling you the amount of people that are actually like you can overcome the best way you fight back at whatever new world order you're worried about is just live a badass life yourself. I don't think you're going to find that people like you, Des. Des is going to fill the following. Why don't you just post it, post it through yours. Oh, and then I'll pin it. Did you post it to YouTube? I did. I did it to TikTok, too. But is it pinned? Can you pin on YouTube? This one? Yeah, just doing that. You got to click that button. Eight new messages. Scroll to the bottom. Is it a good time to buy crypto? Yeah, crypto's down, man. Crypto's down. It's gonna be your best chance. Oh, invite Nina to go live together. What's up, Nina? It goes away so fast. I know. Always calling me. Oh my god. Is your arm getting tired now? No. Nina, if you hear us. Don't worry about that. How do we get the post done? We can't do it. Why don't you get someone else to do it? I mean, I sent it myself. I think it's just not updated. Yeah, but I never saw it. All right. What do you think is the most important thing? Most is real estate the vertical to hit a million in sales with the latest amount of brain damage? No, not necessarily. But it's a great way to build wealth for sure. 250 million trillion in real estate. We'll just close it down. It's okay. I'll do it another time. All right, I'm gonna end this. Dez's arm is tired. Dez's arm is tired. So we're gonna end it. It's so fast with comments. Yep.