Excellent. I'd like to thank everyone who is joining us today. Welcome to today's CNCF webinar, Observability via Red in the Age of Kubernetes. I'm Lockie Evenson, Principal Program Manager at Microsoft and Cloud Native Ambassador. I'll be moderating today's webinar and we would like to welcome our presenters today. We have Dave McAllister, Senior Technical Evangelist at Splunk and Jeff Lowe, Director of Product Marketing at Splunk. A few housekeeping items before we get started. During the webinar you are not able to talk as an attendee. There is a Q&A box at the bottom of your screen. Feel free to drop your questions in there and we'll get to as many of those as we can at the end. This is an official webinar of the CNCF and as such is subject to the CNCF code of conduct. Please do not add anything to the chat or questions that would be in violation of the code of conduct. Basically, please be respectful of all your fellow participants and presenters. And with that I will hand it over to Dave and Jeff to kick off today's presentation. Thank you. Good day. I'm Dave McAllister and I'll be doing the talking. Jeff will be joining in to show some of the concepts that I'm talking about here. I am planning on covering a little bit about observability. I'll talk a very little bit about how observability and Kubernetes work together. And then I'll step into a discussion around the monitoring concept of red inside of this. But let's start off here. In an age of observability, as it being one of the new phrases that we're using a lot here, this is still perhaps one of my favorite quotes. You see, but you do not observe. Arthur Conan Doyle wrote this back in a scandal in Bohemia, and it applies quite well because when we look around here at observability, especially as things get more complex here, it seems that people look sort of across the top. And as such, they miss all of the underlying functionality. And therefore we need to be able to look at multiple dimensions and look at multiple directions as they cross through these boundaries to really understand what's going on. So observability really is a signal-to-noise problem, but it's not. It's actually signals to noise. And red is providing a useful filtering method here. In general, when we look at this, we have operational data that's coming in here. And there are two ways that we can help clarify the signals. We can either reduce the number of signals that are inbound so that we are reducing the noise level adjacent to those signals. But that also tends to reduce the fidelity, as well as the capacity for answering the question that observability starts to look for, which is how do we find out about the unknown unknowns here? The second side is the more preferred side. Let's take a look at the signals. We filter them post-reception. That clarifies the signal side by reducing the noise, but we don't have the same loss capabilities. And we can also defilter the filtering and come back to what the original signal itself was. That becomes really useful as we get into more complex environments. And Kubernetes definitely drives some of the more complex environments that we look at here. So, you know, TLDR here, observability is the quality of software, services, platforms of products that allow us to understand how systems are behaving. And the more technical model from control theory here is designing or defining the exposure of state variables in a manner to allow the inference of internal behavior. You see a lot of this actually in regular life. You see this, for instance, if the heat index on your car goes to the hot unit, you can tell that something is going wrong with the car. But by looking at the additional signals that you can get by connecting the new computer functionalities into the car, you can literally determine more about what the impact was, as well as what the underlying behavior looks like for that. So the ability really comes down to answering the questions of how is the system behaving, why is it behaving that way, as well as the attempt to predict how it will behave in the future. And observability is focused on both the known problems, as well as the unknown problems that arise in everyday life. So, with that in mind, observability is definitely not one dimensional. You know, if you think about that internal state inferred from external X points. Observability is a property of the system in itself is not a tool. There are tools that assist in observability, but it can't just be there is an observability tool inside of here. And because of the fact that we need to be able to see everything that's going on here, it should consist of things like logs, like monitoring events tracing and anything else that applies to those those functions, what you can read in here. For instance, there's a customer I know who actually brings in the data from their Twitter feed, because right now they know that things that will start going wrong, and their customers will start asking questions on Twitter, long before any of their current environmentals will trigger that. And so they actually monitor across this, looking for a certain keywords inside of here and raise alert structures across that environment. Observability also includes elements of both metrics and time for here. It crosses the boundaries between applications and services, as well as disciplines. So it crosses not only from the it off side into the dev side, but it can also cross into the business aspects here. And finally, anything that slows you down is bad, because timing is responsible and the response becomes increasingly important as we go across this model here. So, observability isn't just monitoring. Observability is a system attribute monitoring really is a verb here. And again, there aren't three pillars, even though we will talk about pillars here. There are lots of signals that come across in this line here. And you need signals is you haven't even thought of today. And those signals themselves are not static. They are constantly evolving and constantly changing. And because the nature of the microservices environments that we tend to live in when we look at this, we tend to see that we have things that are also ephemeral in nature. So all these things together lead into that. Now you'll hear about this and we use this a lot because these are the primary pillars of observability. It's the metrics. How do I tell that something has gone wrong? Do I have a problem? The metrics let you start looking at the alert capabilities inside of this troubleshoot traces. Where is the problem down as far as close to I can get inside of that. And finally, what's causing the problem pinpointed the functionality here really is the aspect of the logs and log structures here. So, you'll also hear a little bit, but everything is an event. Everything is an event, but events are only exist if they're recorded and measured. You know, this is standard if the tree falls in the forest and no one hears it, did it happen? Can you prove that it happened? And can you backtrack to when it happened? And maybe even what caused it to happen here. The metrics become very compact. They're efficient. They may not be sufficient to be able to determine all the aspects that we need to look at inside of observability. Logs and events are full fidelity, but they can be relatively bulky to capture, as well as dependent on the nature of the person who decided to capture the materials around that. In my past, I've seen a log that that literally comes back and says, oh, I'm here, which is not actually really useful for anything that I've ever found here. Traces are cool, but they require work instrumentation, whether it be auto instrumentation or capturing pre instrumentated functionality. If you do take a work to establish, they also can be bulky at full capture in their ways around that. So metrics become your points in time. Traces are the users journey through your application and logs are the verbose representation of everything, all the events that have happened inside of here. Logs are linear inside of here. Metrics are useful for the alerting structures. While we've been going through this, we've also seen that the world of operations and app developments have changed. And you all are here because very honestly, things are shifting to the right hand side of this. We're finding people that are really looking at refactoring. We're finding people that are looking at cloud cloud, where they're architecting, where we're looking at loosely coupled microservices and we're looking at serverless functions, be they public private clouds, be they container based, or are those based inside of here. This is heavily powered by orchestration by the necessary the need to be able to manage and control these environments across that and microservices organizations applications themselves can actually be very complex. And so think about it, building continuously distributed distributed continuously available distributed systems themselves is a challenge when you also do it in a distributed development model for a complex environment and this came from Martin Fowler's wonderful episode of microservices for this is a look at the microservices that are making up basically the Amazon co dot UK model with all of the little services introduced inside of here. As you can see, there's a number of these now take that complexity of add elastic capabilities to this. And all of a sudden you have a much larger scale of services that you have to keep track of across larger and larger environments. So why Kubernetes. So Kubernetes orchestrates all this on your behalf. And you're probably very familiar with this, but Kubernetes also adds its own levels of infrastructure, as well as control capabilities that you also need to bring into your space. So you're now looking across not only your application space, but also what the structure of what's going on inside of your orchestration space, all the way down into the infrastructure space. So each of these pieces starts adding this additional complexity. As we cross this. And that means that Kubernetes increases the ephemeral nature, as well as the churn nature inside of here. Kubernetes is heavily in use. This came out of 2018 report, 68% are using Kubernetes in production for here, but it does add that multiple levels of abstraction to monitor containers pods clusters nodes name spaces. And things can happen in seconds, containers can spin up, centers can spend down dynamic workload placement, you don't know where it's going to be placed, you can give directions for what placement you want it to look like. But you don't actually know whether it's going to be there, there or not. And because of that you ended with challenges around monitoring this into in performance of distributed services, because locality matters when you're looking at these pieces. We've also seen additional functionality short service measures to help us control some of this into in performance of distributed systems to manage that functionality as well. And those things also add yet another level of that complexity that we're working about and looking at.  This is a real time programmer I've worked in process control and skater and all those various other terminologies here. The duality of observability is controllability, just being able to see something and not being able to respond to it is not it's only part of the problem here. Let's talk about telemetry. That's our inputs, the inputs of logs traces metrics and whatever else we want to bring you bring into this, but observability needs to be a loop problem, being an open loop or a closed loop. I need my process to be able to talk through the telemetry into the observability, I need to be able to deal with controllability, either manual or automated back to control the activity of the process for that. This gives us the full control capabilities of which observability is part of, and we need to be able to look at more and more, how we actually respond to the information and respond to the concerns that our observability signals are telling us. So, why red? Well, complexity matters. We've taken a little bit of a look here, and we've already seen we've got lots of moving items here. We've got lots of interrelations here. And unfortunately, we also have a lot of not there now, when you go to look for it, if the pod's not there, where's the data. So we need to be able to have simplicity and abstraction to help resolve the clutter that's going on inside of here to actually start looking at what's going on here. At the same point in time, we have to retain that complexity to look for the gotchas in the aha moments to look for how we resolve problems, as well as how we investigate the activity that's actually happening inside of the system. So what is red? Reds basically starts with a subset of the Google Golden signals. It's more SRE related here. And it was first mentioned by Weebworks, my hat tip to Tom Wolke inside of here. It defines down to rate, errors, and duration. And it was designed for request driven systems, specifically for microservices. And we'll point out that red is useful in any request driven service where you need to know what's happening across the entire environment here. And red gives you the ability to do that from an e-commerce system or an IoT response system, and you can actually see what's happening. You also, at the same point in time, can be looking at this accumulation, this aggregation of information by seeing what its behavior is to the norm as well. So the little side here is showing you the services that are being called here, the request per second that are happening inside of that, the error rate that's showing up for that service, and then what its duration was at a 50% point as well as a 90% point. So red gives you a whole bunch of information, but in a very simple way of looking at it without having any confusion activities. But red by itself is not enough to be able to resolve to break out and figure out what's really going on here. So red is a need for multi-dimensional capacity, or as I like to call it, it's monitoring at the Chuck Norris level, when you see something take action. Metrics lead us to rate. So we actually are using metrics capabilities to determine what the overall rate of functionality is. Each interaction has its own unique metric that we can aggregate these together to see what the system's behavior looks like. Logs usually are related to errors. That's how we see things and report things inside of here. And traces usually are focused on our duration aspects here. Rate tends to give us a recognition of errors, and logs and traces tend to give us recognition of the root causes that are happening inside of this. So each of these pieces can work together to help us respond quickly to the complexity that, again, orchestration, Kubernetes, containers, serverless are all bringing to our new microservices environments. So, let's dig in a little bit more. Rate tends to be the number and size of requests on a network in the system. And these can be HTTP requests, they can be SOAP, they can be REST, they could be middleware functionality Kafka, they could be API calls, RPC calls inside of here. And they can be the overhead of control structures themselves. So for instance, service messages report what its functionality looks like as well. Any environment that fails on peak traffic is a target for rate monitoring. So again, it's not just knowing that necessarily what's happening in terms of request or microservices. It's keeping an eye on what's happening in my overall environment across this. You can kind of think of this as looking at my bandwidth and my bandwidth utilization. And quote John Mashee, a very famous computer scientist, bandwidth costs money. So are you heating peak loads?  This is the communication pipeline for your apps and your enemy actually is peak load. So rate can tell you quickly where you are in response to peak load, as well as giving you a chance to look and see what the customer activity and the customer experience looks like. So rate will report things like this. You'll see, for instance, in this case, I've got a rate that over a 10 second window is running about 10 requests per second across here. You can see what my peak activity looks like. Going through this, you can see the request rate by endpoint here, and you can see what the top endpoints themselves are looking like. And so this is a very simple example of what a red structure can tell you, looking into just the specific data around the rate of your request rate. So errors, everybody's had errors, problems that result in an incorrect, incomplete or unexpected results here, and they can be widely spread. They can be production load books. They can be peak load books. They can be things that are communicating. There are lots of places that errors can come up here, but errors require rapid response. They also tend to require point specific responses for this. And to do this, you need to be able to dive quickly into the underlying problem that's happening in here. You need high fidelity work here, and you need it as soon as possible here. Honestly, if your business is dependent on the system that failed, as soon as possible might actually not even be fast enough for this. There are lots of examples of companies that have rolled out brand new functionalities, the wonderful Amazon day of 2018, where they had a problem that basically kept people from being able to get enough bandwidth to be able to respond to the changes inside of here. There was an error that showed up in rate functionality, but the error itself required rapid response to prevent the company from continuing to both lose money and end up with unhappy customers here. So an errors example for this, if you see something that's giving, if you're seeing an error rate at the 45% range over a 10 second period, you probably have a problem that's showing up inside here. And similarly, because we need to be able to look at this for multiple dimensions, you can break it down across a time basis, you also break it down and look at the endpoints that are showing up here. And in this case, the specific one I'm seeing that, you know, an API area endpoint here is coming out of my catalog system. My resolution over that point in time is saying that a 10 second delta roll up, I'm seeing 54% error rate that's showing up in API catalogs. And now, because of this duration of functionality, have the basis to be able to go back and say something's wrong in the catalogs, step back in, look at the logs related to that timeframe inside of that specific services and can start figuring out what went wrong and how I can resolve it. So, duration really is all about time, duration is both client side and server side. We tend to find people measure server sides, but client sides may actually be more important than just hard to manage here. And usually this is the domain and discussion of distributed request tracing, open tracing, open census and open telemetry here. The job of this duration really is to bring events into causal order. When did the event happen? How long did it take? Why did it take so long? And finally, what service or microservice was responsible for the delay? As we move into microservices based environments, particularly with the orchestration approach that allows us to have functionality that lives anywhere. Quite often the time between services is as important as the time within services. So generally speaking, we do measure the time from the request, the span, if you will, to the end of the functionality. And that gives us the capability of measuring both the communication pathway as well as the service pathway itself. We may need to be able to drill into that a little bit more. And sometimes it's really useful to bring in something like a service mesh, an envoy and the SDO, to be able to help you understand and control that communication structure itself. In microservices, particularly where we have ephemeral orchestration happening, being able to understand your pathways are incredibly important. So here I can look at this over that same 10 seconds. I can see that my request latency is still running about a second, which isn't actually too bad, could be depending on your functionality here. You can see what the distribution of that functionality is by breaking it down through the various percentiles. You can also look at it by endpoint, which ones are providing the most capability and the most functionality. So why red? Well, red's actually easy to remember, great erasure. And it's a great starting point. If you haven't already looked into moving into observability structures, red is a great starting point. It also, interestingly enough, and we've seen this in multiple cases, reduces the decision fatigue, where everybody gets in a room and goes, No, I need to watch this. No, I need to watch that. Red gives you a common starting point, a standardization and a consistency that you can scratch across teams while retaining the capability to be able to allow each team to do the discovery that's needed for that functionality here. Red also because of the standardization and consistency across its structure and across where it's understood, these pieces are well understood here. It helps with the ability to be able to automate, be able to drive the responses, whether they are a invocation of telling somebody that something is wrong, deciding where it's wrong, or actually, in the age of AI and ML, responding automatically to that structure itself here. And finally, interestingly enough, one of the things we see red used for a lot is as a proxy for user happiness. There was a Google survey, mobile survey about 2018 that pointed out that a user who waited over three seconds for their shopping cart to appear was 86% ready to walk away. And that number went up to five seconds. The number actually of abandoned shopping carts was over 100%, where people would literally see the shopping cart appear and still leave. And that becomes an indication that something is going wrong. If you are not having happy users, and quite often users are driven by the response capabilities and the time capabilities. Red gives you a very quick indicator of what's happening in that very complex environment and how it affects your users. So red is a wonderful category for user happiness. So, here's one of the interesting gotchas inside of here, is that these three components, rate, error, and duration, can interact in interesting ways. Rate can be caused by an error. Something is not responding or a slow consumer. Something is responding slower than behaving inside of here. Errors can be showing up as bandwidth or response times mismatch. Oh, you asked for something, but you did it in an async manner and I'll get to it when I can inside of here. And duration can be literally nothing came back and told me you were ever finished inside of here, or it could be again back to a limit from the infrastructure back to a network bandwidth issue or back to an error bandwidth. So rate, error, and duration can all affect each other. That's why it's really the last place you look. And remember that each of these pieces provides a different insight into how you resolve the problems in your microservices environments. Rate, something is wrong, duration, something is wrong here, errors, this is what's wrong here. So there's some challenges that have shown up here. Traditional solutions tend to have poor visualizations. They tend to be slow at scale here. And what we've seen as traditional approaches to dealing with this tend to be really hard to use. They also don't allow easy disaggregation. Again, if all I can see is the metrics involved here, I can't necessarily drill in to find out what's going. So let's take a moment and actually see how read in monitoring can help you look at problems in microservices under Kubernetes. With that, let me turn this over to Jeff Lowe here. He'll step us into what's going on. Yeah, thanks Dave. Hi everyone my name is Jeff Lowe and I'm director of product marketing here at Splunk, formerly SignalFX. As Dave mentioned, I'm going to walk you through a quick demonstration of how that comes to life. And you know how you can leverage read to understand what's happening in a complex microservices environment, as well as drill down into what's happening in your Kubernetes clusters. Anyways, we are showing a services dashboard here. And as Dave mentioned, there's a number of every metrics rate metrics and duration metrics that you can kind of use to to see what's going on very quickly. What I'm going to do here and I'm going to back out of this just a little bit. So this is a simple topology of a new commerce application. And as I mentioned before, it's not always obvious, you know what's causing a problem in this particular example, and we're looking at our microservices APM UI here you see that there's color coding to kind of show that there's an alarm some alerts happening on all of these individual microservices. So they're all color coded in terms of error rate. If you look at the legend down here in the bottom left. And that ring around this API service here is actually your alerts so if I click on API, which immediately notices that there's an alert that shows a sudden change in error rate. We're using the red metrics and that sudden change to really say okay there's a potential problem here. But again, in a complex environment is not always obvious what's causing the issue. So if we click into this alert we pull up an alert model and we see that sudden change happening right at this time frame on this time series graph here. But you know what we really want to do is drill down and really understand you know what's really going on is it this actual service that's having a problem, or maybe that's a downstream service dependency that's causing the problem. And with some of the built in technologies that we're using to bring this to life. We have this ability to correlate services, you know all the way down to what is actually causing the problem so if you recall, the alert was actually on the API service. And immediately we can see with a very high level of confidence that it's actually not the API service that's having the alert, it's down to the checkout and down to the payment service. And so it's actually the payment service that is having a problem. And we have a number of things that we can show in a below as well as to the right, but what I really want to dig into for the sake of this webinar is really how we do a service to infrastructure level correlation. So we're starting off with these red metrics and then getting down into the Kubernetes and so what you can see over here are the correlated infrastructure components. So this is the infrastructure on which the services are running. And you can see there's a service here called Kubernetes pod and it has that payment service instance number six and so I'm going to click on this immediately to drill down. And what it's going to show me are the infrastructure the Kubernetes containers on which we're running. The particular service is running in this pod. It's running on a set of nodes and cluster, but this particular pod has nothing immediately obvious in terms of errors. See if I look around on this Kubernetes navigator. I see some pod properties but I see that the CPU doesn't look too bad. There's nothing obviously that's changing on the memory utilization. I didn't really change it on the pod throughput. I look down here below on the containers in this pod and nothing immediately jumps out as something that would potentially cause that alert on the API service that we saw earlier. So what I'm going to do is I'm going to back up basically go up the food chain or back up into the hierarchy and click on node detail. So by clicking on node detail. I can immediately see that there's a potential problem here. And what I want to call your attention to is this kind of second graph in the middle this memory percent utilization by pod, and you can see that there's a pod in pink that's using quite a bit of memory. In fact, I'm sorry to the containers actually running in this pod. There's a number of containers and this particular one container named DC 10 dash robot happens to be correlated with a not suspicious name at all bad robot workload. And it's chewing up roughly 90% of this node capacity. And so something's fishy with this particular container. So let's go ahead and investigate this guy a little bit further. Click on him. And I can immediately see in this info window, you know, all the properties that were used to deploy this container. And by scrolling down, I immediately see a potential issue, something around this memory limit, which is probably why the memory utilization is so high, you know, whoever deployed this container did not set a memory limit. That's why it's just chewing up all the memory. And therefore it's impacting neighboring services, specifically the payment service, which actually had nothing wrong. It just happened to be deployed on a piece of infrastructure on a container on a node that actually had noisy neighbor. So the idea here is again, using red to kind of very quickly understand what's going on in a complex environment, and then use it to drill down and understand, you know, how the infrastructure underlying those services can be monitored as well as Trouble Shot to understand what could be potentially causing alerts in your service, and therefore impacting your users, potentially with you know delays, latencies, potential, you know, service outages. So that was a very quick demonstration of how red comes to life in a complex environment. Thank you, Jeff. Appreciate that. Let me do this and get back to the right, right thing here. So as you saw, we can have things that are identified via this metrics functionality, but the ability again to use this this multi dimensional approach, being able to look at the multiple sets of signals that come into play here. Let us actually go down and determine what's happening inside appears that we can respond to it as fast as possible. So some some sense of observability, particularly when it comes in services. There are two sets of items that are important inside of here. One, the external your customers view is singular. They look at the request they look at the latency and they look at the response, the success capabilities here for this. And the operator's view is over the workload. It's all of the requests, the latencies their rates and the concurrency they're happening here, as well as the system resources and components. So Rida gives again gives you the ability to look at both of these features and figure out what's happening across those some basic philosophy. I once ran a nonprofit for on philosophy capability here. Let's start by pointing out instrumentation by itself is not an answer.  If you can't find the answer the instrumentation doesn't help you. Instrumentation should help you find the answer, and your visualization should help you pinpoint your answer here. The metrics are powerful, but they're not solely sufficient cardinality matters being able to drill into it, being able to look at all of the signals and all of the data that's necessary becomes incredibly important. Finally, you're observing the work, not looking at the service per sets, but you can look at the services anyway. And in particular, you want to look at how the service response to the workload. Again, production, we hear a lot often about I test, I test for production. The problem is that the errors that can show up in production can never actually be tested for. This is one of your unknown unknowns, you do not know necessarily how it's going to respond. So look at how the service response to the workload over both time, as well as in the moment here. And finally, your goal is not really observability. It's around reducing the meantime to detection mean time to response in the meantime to resolution. Shorthand for this, I want to mean reduced my mean time to WTF.  And so summing up here, observability is more than monitoring monitoring just driving observability uses monitoring capabilities, but it also uses a more functionality to be able to deep dive, go through the levels and figure out what the underlying causes are. Red wins for microservice based applications. Red simplifies as well as stabilizes the ways that we can look at the data so that all teams and all groups can be on the same page as we crossed here. And also tends to simplify the observability of Kubernetes and its complexity, while being able to retain the insights of how the underlying structure is working, as well as how your application is going. And keep in mind that red can interact in interesting ways that what you think maybe the problem can actually be caused by one of the surrounding components. We'll look at all of the components to determine what you need to do and how you need to respond to it. And then finally, find the right tool to give you clarity and insight into what's going on with your microservices environments, particularly in Kubernetes and is orchestration environments. And with that, like to thank you for your time today. And if there are any questions will open up to that. Excellent. Thanks, Dave and Jeff for the great presentation. So we have some time for questions. If you have a question you'd like to ask, please drop it in the Q&A tab at the bottom of your screen. And we'll get to them as many as we can right now. So we have a question here that I'll ask, please explain more what cardinality matters means when it comes to the sufficiency of metrics. Okay, so when we think about cardinality, we can think about in particularly we think about high cardinality and cardinality is a data property that's around how compressible the data is. So it becomes a case of looking at the complexity of the data. So again, in microservice environments, data is complex. You're looking at multiple services you're looking at multiple communication pathways, you're looking at things that are starting and stopping inside of here, you can even be looking at dimensions like geolocation, you're going to be looking at what browsers are being driven from a consumer environment for this. And each of those pieces can have an impact on any of those functions, whether it be a rate functionality, whether it be the duration that's happening. So cardinality matters, because it shows you the depth of what's happening inside of that. Yeah, that's a great question on cardinality. It's something that's very critical to microservice environments in particular. I just wanted to add one quick thing Dave touched on compressibility. One way to think about cardinality is uniqueness of data. It's one of those things where, you know, Dave touched on lots of different microservices, even within microservices lots of instances within very ephemeral highly ephemeral infrastructure like containers, you're going to have multiple devices coming up and down, each with their own unique container IDs. And so cardinality becomes one of those things that quickly expands the set of unique data that you need to now analyze. And so, you know, in these environments, leveraging red metrics and distributed tracing. It's one of those things that you absolutely have to account for when you're building and planning, you know, your monitoring and observability solutions. Excellent. Thank you. There is another question that we have here is Falco, a good tool for red observability. So Falco is a new offer from Cystic. You know, I've seen it in an early demonstration. I think it's a fantastic approach for particularly the security side of things. What they've done really well is combine both the basic monitoring and fundamental security aspects into that open source offer. You know, I can't quite comment on other vendors products, but you know, I like the approach of combining essentially from a very macro perspective DevOps and DevSecOps into a single solution because at the end of the day, you know, once you've got, you know, your monitoring, your complexity, kind of all your dependencies figured out, one of the natural next steps is to make sure that your security is buttoned up as well. And so, you know, I think it's a very smart approach. But that's really all I can say about that. Okay, so we have no further questions. I'll solicit one more time. If there are any questions, please go ahead and click the Q&A box down the bottom and ask them there and we'll give it a moment. Okay. Thank you, Dave and Jeff for a great presentation. That's all the time we have for today. And thank you very much for joining us. The webinar recording and slides will be online later today. And we look forward to seeing you at a future CNCF webinar. Have a wonderful day. Thank you.


The City of Weizberg held its Valentine's Main Street Market on Friday, February 9th. This is good for our up-and-coming businesses to set up and get their name out there and also our businesses that are in town. This brings people into town that maybe normally wouldn't come. Do you worry about having enough money to last throughout retirement? Give Reed Potter at Raymond James a call. Reed has 26 years experience helping folks enjoy their best life in their retirement years. The market hosted over 30 vendors selling a range of goods from handmade crafts to homemade sweets. Despite the overcast day, many turned out to walk Main Street in search of a gift for their Valentine. You know Weizberg is becoming a destination.  The Valentine's Main Street Market is not only good for the City of Weizberg as it gets people out in town enjoying the local businesses but also good for the small business owners who may be starting up their own local business. For Mountain Top News, I'm Kelsea Fidell.


Thanks for checking out this video. So let's get down to it. What did I watch for the month of October? I don't know if you guys know I've said it here and there on my channel before but I do at least 31 films throughout the month of October. I don't do necessarily one per day I try to but you know life gets busy So I just shoot for 31 total in October one to represent each day of the month and I've been doing this for I Think this is my ninth year doing it in a row. So sometimes I hit exactly 31 I've always hit at least 31 and sometimes I go a little bit over now. This year is a little bit different Obviously for everyone pretty much and for that reason I had extra time. So I went above and beyond I really hustled on it and I hit 50 movies, which I've never even come close to that before I think the most I did prior to that was maybe 39 in the month of October. So I hit 50 I thought that was a lot of fun. So I'm gonna go over what I watched I'm obviously not gonna give like synopsis or talk too in depth about any of the films I might not even talk about some of the films just say what they are But the ones that I really enjoyed I will obviously point out or ones I highly recommend and actually a bunch of these You have probably seen that I have reviews for on my channel almost all of them actually so just know So the and this is in order that I watched them So just know that chopping mall was my first one not just chopping mall But the chopping mall with the Joe Bob Briggs last drive-in Treatment done to it always fun piranha by Joe Dante. Love it scare package The Joe Bob Briggs last drive-in treatment of scare package the mortuary collection Which a lot of people are seeming to really enjoy these days one that gets Forgotten about slash not talked about much the hitcher. I quite like the hitcher I think it's a great one the original one with C. Thomas howl and rucker howl or check that one out If you've not watched it ready or not the movie from last year That's fun one ginger snaps what I consider to be one of the top probably top five Werewolf films maybe even higher than that maybe even top three I don't know but a great werewolf film nonetheless fade to black Which was an interesting watch if you haven't watched that I think it might still be on shutter Actually the majority of my films were watched on shutter not all of them But a lot of them from beyond the Stuart Gordon pick that one is crazy That's kind of like I don't know how I feel about this Pie whack it Didn't love that a whole lot Starfish, okay starfish is on shutter and this one it's not there's horror to it But it's not horror per se, but it's a very good story. It's very well done. It looks beautiful I highly recommend it, but just know it's not straight-up horror So if you're willing to step outside of that I'd say it's definitely worth a watch vampires versus the Bronx Okay, more of like a kids type movie, but it was all right basket case one two and three Because I love me some Frank Hennan lotter death becomes her which some people were very surprised that I actually watched and reviewed They're like, oh didn't see that one coming. I understand it the thing. Yes, John Carpenter's remake of the thing Such a classic such an amazing film Dude bro party massacre Three because it's a good horror comedy. I love horror comedies You'll hear a decent amount of horror comedies in my in my list part of that being because I like horror comedies But also part of it being that that's my wife's preferred mode of watching horror Because it's easier to consume for her than than most films Twisted tale the unmaking of spookies, which is the documentary about the film Spookies I have a review for spookies up and for this documentary Definitely worth watching especially if you know anything about spookies and the troubled past that that film had when it was being made House and not the house from the 80s. This is the house from the 70s That's Japanese that is very comedic intentionally and totally nuts if you have not seen house It is an insane experience that you have to see It's a visual bonanza it looks amazing, but it's so quirky so out there so crazy You at least have to see it once I loved it which board which I had heard a lot about that film I've been meaning to get to it and I quite enjoyed it. I thought it was gonna be a so bad It's good film, but I enjoyed it Hubee Halloween another one people were surprised. I actually reviewed it was fine for what it is Plus I watched it with my wife and over the phone with some friends. So it was more of like a group experience thing 32 Malasana Street, which is a good Spanish language film Franken Hooker.  Yeah, but anyway my bloody Valentine love it every time I watch it another movie I love so much and if you have not seen it, you should definitely see it It is beautiful looking film. It's very well shot. The pacing is amazing on it and it's so good Assassination nation. I have a review on my channel. I talked to people about the film all the time I hear no one talk about it. Basically. This one is going to become a cult classic at some point. Trust me It's very good. Assassination nation Tucker and Dale vs. Evil got a lot of great response when I put my Video review out for that one because who doesn't love Tucker and Dale vs. Evil It's one of the best horror comedies out there in my opinion and my life and my wife loves it another horror comedy Wolf Cop a lot of people love Wolf Cop a lot. I got a lot of love on that video as well May the devil take you to another Spanish language horror film is on shutter okay The head hunter now this this is a I don't hear people talking about this one And this is kind of one of those hidden gems. It's still on shutter. You should definitely check it out It is a very cheap movie. I think the budget was like $30,000 or something But what was achieved with such a small amount of money is phenomenal I love that film and I could watch it like repeatedly it's in the sound design Oh my god, the sound design on that film is ridiculous Haunt not just any haunt But the Joe Bob Briggs last drive-in treatment for haunt because a lot of us probably watched that live when it was on shutter the burbs Probably the best horror comedy film now my wife had never seen it So I was like we got to do the burbs. We have got to do the burbs Tremors Shrieker Island, which is the newest tremors film and if you've seen any tremors films and you enjoyed them You should definitely watch tremors Shrieker Island This is kind of a return to form for that franchise crazy enough I've said it in the review I put up, but it is the best tremors films since tremors 3 So 4 5 and 6 not the best 7 Shrieker Island. Yeah, it's pretty solid Creepshow animated series. I know is it a movie is it not I kind of counted as a movie It was you know about 45 minutes that one was fun If you haven't seen it watch it host which that was my second time watching host Obviously, that's the film that's kind of took over 2020 for horror fans. It is a well-done film The witches not the old witches the new witches I did not do a review on that one because I just did not feel like it. It's not very good It's not very good and the acting in particular. Well, I will say Octavia Spencer did a really good job in it I loved her performance. I did not like Anne Hathaway's performance And I think it was probably What was asked of her by Robert Zemeckis in the film because her character was so over the top It was annoying. So don't really recommend it Demons yes, the Italian horror film Demons with the Joe Bob Briggs last drive-in treatment to it love that one Also, Joe Bob Briggs blood rage, which I'm sure a lot of people as I said that right now are like, oh, yeah blood rage The beer can that's a big part Yeah, so I love that one blood vessel which actually the review for that one Oh the review for that should be out by the time this video goes up I just just would have put it up two days ago. So that is one coming to shutter On Thursday the 5th of November. I won't say anything about that. You can watch the review for it It's a no spoiler review. Don't worry pieces with the Joe Bob Briggs last drive-in treatment You noticing a bit of a theme here. I did a lot of last drive-in watches because you know, it's just fun Jack Frost with the Joe Bob Briggs last drive-in treatment to it as I'm sure you guessed Crawl, which I think is a very fun creature feature. I don't know if if you haven't seen it It came out last year if you have not seen crawl. It is fun. It's not like an amazing film or anything But if you like creature features, I thought it was a good time the cabin in the woods one of my favorite horror films I love the genre bending that this film has done that basically it takes the the horror formula And uses it to point out how stupid it is that we use a horror formula. Love it. Love it. Love it It's so meta Green room man, if you have not seen green room and I think it's on Netflix at the moment, so Very intense film. It's an 824 film and as Anton Yelchin in it and Patrick Stewart in a evil role He and he does it really well You don't get to see that often from Patrick Stewart, but really well acted film really intense the whole time It is outstanding. I loved green room the black coats daughter. That was a rewatch for me I really like the black hoods daughter. That's another 824 film Really good. If you have not seen that that is also still on Netflix dead heat But the Joe Bob Briggs last drive-in version of dead heat. So, yeah Villains which I don't have a review out on yet, but there will be a review coming. I've already recorded that Don't worry. It's coming. I watched that on Hulu. It's a newer film. I think it's a 2019 film from Yeah, I wrote down 2019 from it has Bill Skarsgard in it so Look for that review trick-or-treat Which I am going to do a review on and that'll be out sometime this month So look for that one as well That is one of also one of my favorite horror films of all time And then I was one of the people who stuck around for Shutterfest and did the surprise premiere of this the film lucky I Don't I need to watch that again, and I will watch that again when it hits in 2021 Or I'm sure I'll get a screener for it in 2021 and put out a no spoilers review for it ahead of time So I yeah, I just really need to see that one again because I I don't know how I feel about it That's one that you need more than one watch of so so that was it. That was all 50 I don't know if it didn't really seem like I went through 50 films right there But I did so this is what I want from you guys now Comment below. Let me know how many films you watched in October and then maybe throw out like your top five that you watched I'm really really interested to see first of all how many everyone else did I'm sure there are people out there who were like 50. That's nothing I did a hundred or I did 60 or 80 or whatever and then I'm sure there were people were like, you know what? I was busy. I didn't have a whole lot of time I only got like eight or ten or something and that's fine You know we all move at different paces with this stuff But yeah, tell me how many and give me your top five if you don't want to take the time to figure out top five Give me at least like the top two or three, you know I'm just very interested in what everyone watches in October and how much they watch So thank you very much for checking this out Do me a very quick favor hit that subscribe button because that is your best way to repay me in Gratitude for all the videos that I do and I've done a done a lot of videos not making money doing this or anything Just doing it for the love of horror and to connect with people like you That's why I want comments so we can you know get nerdy about it, but if you could do that for me I would love that also just hit the notification bell, too And that way you'll know whenever I'm putting up a new movie review video or an unboxing or doing a live stream or doing Something different like this Yeah, so anyway, thanks for checking this out and taking your time to do it and until next time keep it brutal


Be the first to escape our most immersive room yet and win a million dollars so When does the game start? I was stuck reliving the same day over and over again Until someone wearing a baby mask murdered me on the night of my birthday turns out.  I your owner. He's not like us move into a doll so that it could be with us


So, some states like Texas, I think, is going to have like a sales tax system. And so then finally, later on, they came to the idea of, well, this is kind of unfair that we're allowing some states to get a deduction for state taxes when all states still have to pay for their own stuff. Some states are just better at it than others. They seem to be more efficient, so we should be able to deduct the sales tax instead of the income tax for those states that have a sales tax that you're paying for. Then the question comes up, well, how are you going to deduct the sales tax? Because it's a little bit more difficult to calculate sometimes. And then we have tables and methods that you can use to deduct the sales tax. So this will probably be dependent on the state that you're in. So if you do state taxes for a particular state, if you're in California, you're going to be doing, most people are going to be taking the state tax and not the sales tax because the state tax is going to be, the income tax is going to be high typically. But if you're in other states, then you might have the sales tax. And again, if you do state, if you do returns for multiple states, then that could be a little bit confusing. And you want to make sure that you get it straight in terms of how you're going to be working that out. So state and local income taxes. So if you don't elect to deduct general sales taxes include online 5A, the state and local income taxes listed next. State and local income taxes withheld from your salary during 2023. Now, most people when they pay their taxes, similar to the federal income taxes, if you have a state tax system, will have withholdings. So places like California and I believe like New York, for example, mirrored the federal income tax system in part so that they can maximize the tax deductions and subsidize the state. So that means that the tax system is going to be looking much the same in terms of the withholding system. So the employer is going to be required to withhold the money from the wages like with the federal income tax system. And then you'll see them reflected on the W2. When we think about the deductibility of state taxes, we typically are talking about a cashed based system. We're talking about the state taxes that we paid. For most people, we paid the state taxes through the withholdings and therefore the data input into the software should be fairly straightforward for most tax returns because the W2 will have the withholdings and that will help us to calculate the deductibility of the state taxes on a cashed based system. But some people might have a estimated tax payments, in which case you got to make sure you put in the estimated tax payments for like a business kind of situation. And again, the sales tax messes everything up because then they're not going to have the withholding system set up and you're going to have to use some other system to calculate the sales tax. So your form W2 will show these amounts forms W2 DG 1099 G 1099 R 1099 miscellaneous and 1099 NEC may also show state and local income taxes with help. So these are all those income type forms we talked about in the income section. They may not have withholdings, they're less likely to have withholdings than the W2 except possibly the 1099 R for retired individuals. But they could have the same kind of withholding. However, don't include on line 5A any withheld taxes you deducted on other forms such as schedule C, E, or F. So here we come up with the same kind of problem that we saw with the medical type of expenses, meaning the normal kind of things we can deduct are those things that we use to help generate revenue. If we had to pay certain state taxes as part of our business, then you would think it would at least be a more of a legitimate deduction and therefore would be deducted more legitimate in that it aligns with what you would expect from an income tax system. So it wouldn't be a personal deduction, it would be a business deduction and therefore deducted on like a schedule C for sole proprietorship. If it was allowed as a deduction on a schedule C, you can't also deduct it on the schedule A because then you would be doubling up on that. We'll see examples of that when we get to say the real estate taxes, for example, where you might use like part of your home for a business, for example.


It's nice to see it's nice to see you recovered from that butt whip and the little Giants gave you earlier We won. We're still champions.  Ladies and gentlemen, you're looking at Sully Banger push people around the playground Doesn't surprise me. You would like an individual like that.  He is too nice too nice Drew Too nice. Too nice. Well, let's see if he's I doubt that he's gonna be nice to Mr. Sully Banger here today Wow Take a throwback to the old strongman style And his beard is way better than yours Chad. You can't grow a beer. I've got one. What are you talking about?  So yeah, I know trash when I see it Right now this batch is now gonna be a mix of styles. It's bully Banger versus Fido J. Liftington strong versus First in the corner to my right from Providence, Rhode Island Just called bully Banger the next Wow The beard alone weighs 112 pounds His personality weighs 110 pounds It's the hottest action Fenway has seen since 1918. I don't know. There was a little thing in the bathroom a couple years ago, but I Probably shouldn't talk about that on TV We're on YouTube not to mention a world series or two and here we go the bells been rung and we are underway folks Theodore J. Liftington getting the belt on club faithful into this match and firmly behind him Two powerhouses here. We're gonna see who can get advantage here and exploit. Oh, look at that Theodore J. Liftington. We talked about the mind games earlier Striking that pose to remind Sully. He just outpowered him. I don't think it's mind games He doesn't have half a mind to the actually spare It's just he is the barfado of a 1920 strongman He has a passion sense of 1-2 And again powers him off brute strength alone has won many a man a match or two and that could definitely be the case here today At Fenway Park for mr. Liftington Well, you gotta think for a guy who fancies himself a powerhouse to be deposited like that twice in a row has got to be Little discouraging. Well, here's the thing. I don't know if you've ever seen theater laylip You know shed a ring with him. He is quite possibly one of these strongest competitors in all of New England Well, if you're Sully banger, how do you counter that now? I don't know the eye and kick them right between the legs Words of wisdom here from Chad epic. It might not be pretty and might not be beautiful, but guess what it is effective. I Guess I could congratulate you in the Middlesex Express on your victory early I should first ever last ever New England's ag team title holders. Maybe I should congratulate you, but I won't Kmart and mine custom Taylor from the Kingsman.  This is perhaps the quietest most reserved suit. We've ever seen you wear, mr. Epic. I Didn't want to get my decent suits. This is my poor people suit when I'm around these inbreds here in Boston. I Probably shouldn't have asked I probably should have known better So right now all we have is bully banger getting very angry. I Told you we talked about the mind games Wait a minute. Oh Theodore J. Liftington has rented space and Sully bangers had right. I hope he's paying him rent You're running through a brick wall the brick wall wins And here we go see a limit lifting tin fairs and banger fails again Probably not the best idea for Sully banger and that guy's is called a headlock I know you don't know one from a wristwatch, but that is a professional wrestling move say that again spell that for me H Oh, I ain't here to spell or read. I'm here to lead the commentary table. That's because he can't do either I Could do it. I just don't want it right now Irish whip. Oh We got it with a clothesline They exploded out of that corner and it takes that kind of explosive power to get lifting to down It was almost two only got the two out of it I think you might have knocked though ever living weighing down a lifting tin and that's his is time to take advantage Pumble him cut his hair stab him in the eye do whatever you can stab him in the eye. What? geez Utilizing every second of that count of five to his advantage there's still four. You don't want to get to five Boy am I lucky to have you around Chad You are the pleasure is always all yours See doesn't matter how big and strong how intelligent you are if you can't breathe you can't do anything Wow, we saw earlier selling better explode out of the corner with a clothesline now see no J lifting to return to favor Oh, no, he's going Atlas mode right now. He's put the whole world on his shoulders Sully's fighting out of it. He adds lifting to them a corner groom. You guys can talk. I don't have to do it all What are you doing? Come on We got a huge this is a soup plate coming up a Gordon showly special watch out now because the power of lifting says He's blocking that maneuver Banner is trying but he cannot get him over. He weighs like 10 stones, of course you can't oh no He's powering up here those big left hands. He's going southpaw No fire for the right-handed mess. Oh big four under the back great to catches them messes up the O'Connor row Should be going for the cover right now Send him up. No. No. No. He's going for that big DDT and then it folks But only got a two cow out of it And lifting to now looking for some encouragement from the bell time club faithful Do not give him protein. No wasted effort there by so no he's put on the beer You don't talk on Superman's cape. You don't pull off the door J lifted In the power that Unbelievable double underhook Wow impressive victory for theater J lifting 10 the LIS Lictorium Parium specials right there the center of the ring one two three at academic Something you know nothing about his academics.  I think it's safe to say He proved he's got the biggest package in the ring Well, it's theater J lifting to you would never be so vulgar.  I could do what I want Well, Sully better taking the short end of the purse here tonight. Certainly not the outcome. He wants this Oh, he just broke his hand. I heard a snap always the gentleman theater J lifting 10 That was just that was a horrible act. He broke his hand. That's not very nice. He was shaking his hand. He broke it It's not his fault. He's a powerhouse hard fought victory for the strongman Well, ladies and gentlemen watching at home on YouTube. Thank you very much My name is Drew kazoo from mark green and chat epic. We'll see you next time


I'm John Furrier with Silicon Angle. We're here at EMC's mega launch in New York City where they had record breaking 41 product announcements, all kinds of gadgets and flair. And Jeremy Burton, kick-ass marketing guy who's got an amazing theme here. Great show. Joe Tucci's on board with it. Pat Gelsing is playing well. I mean, all kinds of great stuff. Really good show. Wasn't goofy. It was really clever, well done. Good messaging. But the theme's big data. You know, talking about data, storing data, moving data, in data centers, between data centers, around data centers, Zeta bytes, and there's a ton of data flowing around. And Len, you run the social media group over there. So, you know, one of the things they really talk about, they kind of touched a little bit about is the social media, where it's very data-driven. I mean, there's more data, gesture data, user data. Just how is EMC leveraging all this data internally? Oh my goodness. You hit it on the nail on the head. It's user-generated content, right? And in fact, you know, as a brand, I've seen us move from sort of the very traditional corporate content to now much of what we generate on a day-to-day basis is from the individuals. If you look at, for example, we've got a community out there called EMC One. It's internal for employees only. We've got 35,000 of 45,000 employees on this. And every day they're generating new content, pictures, you know, product plan strategy documents. So from my point of view, we've made that shift. It's all about what's coming from the individuals now. Yeah, Joe Tucci mentioned that about people with iPhones putting, you know, attended HD video around. But it's just so much data, new data. Yeah. Well, and you heard Joe's, the sound bite was what, between now and 2020 we're going to have about 44 times the amount of information to store. And yeah, as you suggest, a huge chunk of that's going to come from yourself, myself, the folks at Silicon Angle. We're here in New York City with Len Devanna, so director of social media for EMC, where they're pushing the boundaries. They're doing, using data. They're leveraging data. They're eat their own dog food. They're pushing the envelope. Certainly they're up their game on the marketing side with Jeremy Burton. And they're pulling no, holding no stops on this one. They're just killing it. Congratulations. Cheers, thank you.


Cardiovascular diseases, CVDs, are highly prevalent and have been linked to a variety of genetic and environmental factors. However, these factors differ between individuals and populations, leading to varying clinical presentations and progression rates. To better understand the underlying causes of CVDs, it is important to consider both genetic and environmental factors at an individual and ancestral level. This will allow us to gain a deeper understanding of the impact of environmental and lifestyle factors on disease onset and progression. Furthermore, leveraging genetic heterogeneity can help identify potential targets for therapeutic intervention and personalized medicine. This article was authored by Opaemi Sormakhan, Marejo Dibb, Skanda Rajasundaram, and others.


The world is anxious about the future, the world is concerned about the conflict of nations, the state of the economy, the political situations that are becoming tense, the possible food shortages and supply shortages that they're all talking about. But I'm here to tell you that no matter what is happening in our world, that no matter what we're facing, the church, we, the children of God, have nothing to fear. This is not the time to back down. This is not the time to slow down. This is not the time to hide in the corner. This is the time for the great harvest of souls, and if we're not careful, we'll miss it. Subscribe for more content like this.


of the woodland! Ranger Bill, warrior of the woodland, struggling against extreme odds, traveling dangerous trails, showing rare courage in the face of disaster, in the air, on horseback or in a screaming squad car. His mind alert, already smile, unswerving, loyal to his mission. And all this in exchange for the satisfaction and pride of a job well done. Ranger Ed Quarters, Bill Jefferson speaking. Oh, yes, Tom. Well, Ralph should be. Left here about half an hour ago. Is there something wrong out there? Well, I wouldn't be too worried about him, Tom. Doesn't know any other home anymore. Sure. Well, let us know how it turns out. Okay, Tom. Bye. That was Tom. And I figured out much. What did he want? He was anxious for Ralph to get out to Tower Seven to replace him. Seems that bright water has run off somewhere. That's true. I don't think there's anything to worry about, but you know how Tom is about that little otter.  Well, that ain't hard to understand. You remember from your tower sitting days how lonely you get out there, that little otter makes Tom's life a whole lot more bearable. And I'll say, bright water is the kind of pet every tower watcher ought to have. And it is strange, though, that bright water isn't near the tower.  I hope so. I wouldn't like to see anything happen. Excuse me, Stumpy. Ranger Adquatter is built. Oh, hello, Tom. What's that? Oh, no. This is the first I've heard about it. I don't like the sound of that at all, Tom. Sure, we'll be out this afternoon. I hadn't thought of that. Hope he hasn't been right. We'll be there soon. We're going to lunch, but we can grab something on the way. Okay, Tom. Right. Bye. What's up? Well, after Ralph arrived to replace Tom at Tower 7, Tom went looking for bright water. While he was looking for him, he came across three traps. Traps? That's right. And of various sizes. Somebody's out there in the game preserve taking advantage of the good care the animals get. And I aim to put whoever it is out of business just as quickly as I can. Yeah, it looks like Bill coming now, Tom. No, it's about time. Yeah, that's him all right. Well, it doesn't look as though you've found bright water yet. I haven't. And I've got a feeling why I haven't. There's a trapper somewhere around here that's got him. Who knows what he's done with him. Let's not jump to any conclusions, Tom. For all we know, bright water was frightened by the trapper and his hiding. You don't know him like I do, Bill. That poor little guy at head home as fast as his little legs could carry him.  Well, in a way, he is, Ralph. These wise, he's the only kinfolk bright water knows anything about. Oh, brother. Look, I'll leave this whole matter of Tom's runaway baby to you guys. I'm going back up in the tower. Take a look around, Ralph, and see if you can spot anything that looks like a trapper moving around in the forest. Yeah, I'll see what I can see, Bill. But you know yourself that once you get above the trees like that, it's pretty impossible to see anyone or anything moving around under them. Yeah, I know. But if you should see anything, give a shout. Right. Listen, Tom, I was only kidding about that baby stuff. I really do hope you find bright water. Thanks. I'll check with you later, Ralph. Just banging the tower, Bill. No sense in climbing all the way up if I haven't seen anything. Now, can we set about finding who's got bright water? Say, Tom, maybe this isn't the time of the place, but something's got me a little worried about you. Huh? Well, we've been kidding about your tremendous concern for your pet otter, but, well, you really do seem almost overly concerned for him. What are you talking about? I've done Tower Watch in my time, Tom, and I know the distractions to fellowship with God that can come from inside and from outside. Are you trying to say that bright water's a hindrance to my Christian life? No. I'm asking. Well, that's crazy. Listen, Bill, I used to pray a lot that God would make this job less boring to me. He sent me bright water as an answer to those prayers.  Huh? Sometimes, Tom, we can get completely carried away in the gifts of God, fine as they may be, and lose the giver himself. That's something to think about. Sure, Bill. Sure. Now, what do you say we start trapping this trapper? You sure laid it on the line, sonny? I had to, Stumpy. All the way out in the car and for the first few moments we were talking, I kept trying to think of a way to work it into the conversation. All I could think of was to be direct and say what was on my mind. Well, that's the way Jesus acted when he was talking with folks, so I guess you're not far from being right in what you did. I only hope that Tom does think about what was said. Well, that's why you let him look in one direction while we checked in the other, huh? That's right. Want to give him time to be alone and think. Well, from the way he acted, I'd say you got him right where it hurts. Look out, Stumpy. What's the matter? Look where you were about to step. Great horny toads, a trap and one big enough to catch a bear or a man. You mean you think he's trying to catch a man? No, but if you had stepped into that trap, you would have been caught. I wouldn't like the job of trying to get you out of it. I reckon not. It looks as though our friend isn't very particular what kind of animal he catches. It looks to me like he knows he ain't got a whole lot of time to trap around here before we'd get after him. So he set as many kinds as he can and trying to make a fast killing. You're probably right. That's why we've got to catch him as soon as we can. Now stand away a little. I'll snap this one with this branch like we've done the others. No sense leaving it around set. What's the matter old timer? Did I say that out loud? I was just thinking that that branch that the trap busted when you snapped it might have been my leg. And then you stop praying. What does he mean sticking his nose into my spiritual life like that? I never thought Bill would be that kind of a guy. Just because I get excited when bright water is missing probably trapped. Who wouldn't get excited?  Why every time I sit down to eat I pray to you. And maybe that was a mistake. I guess I don't pray very often. Well there's a lot to do on the job. God you understand don't you? I don't know why I thought the job was boring before bright water.  He's the cutest little fella though. He's God's creation isn't he? But well in a way maybe Bill does have something. Getting carried away with a gift and forgetting the giver. Maybe I'd better. Oh my leg I'm caught. A bear trap. I gotta get free. Pain is almost unbearable. Gotta get free. Oh blacking out. Help Bill. God somebody. Oh my leg. Hey what is this? I'm tied up. That's right.  You must be the trapper. That's right. What do you have me tied up here for? That ain't too hard to figure out. It's because I don't know what to do with you. I didn't think about catching a ranger in my traps. Where am I? In my cabin. I don't think anybody will drop in to help you out but then I ain't as sure as I used to be about how safe I am. How long your ranger's been on to me huh? How about untying me mister? It'll only make it harder on you when the others get here. You mean that big guy in the old man they went the other way. I know I'm safe for a little while at least. What do you figure on doing with me? It's a good question. If I had the answer to that I'd have done it. Maybe the best thing to do is to take the skins I already caught and get while we're getting good. Sooner or later somebody'll find GM's. Skins? That's right.  Where is he? You'd better take it easy mister ranger. I might have to cover you. Now what you talking about? I'm talking about bright water my pet otter. Pet? Oh no wonder. What do you mean by that? I've never seen an animal like the way that and did turn around through this cabin trying to get out. Once when I was out checking traps he almost chewed his way right through the door. I never see such sharp teeth before. Even when I kicked him away from the hall it was... Kicked him? You... I said take it easy. Even that otter you earn is too of a kind. I might have to fix the both of you. Where is bright water? What have you done with him? Me? I ain't done a thing. He gave up. All by himself. Gave up? That's right. After seeing that I wasn't gonna let him out he just went over the corner and rolled up in a little ball. He didn't even fight when I picked him up and put him in the cage I made out of branches. He stopped fighting? That's right. But don't you know what that means? It means that he's going to try to die.  Oh stop it you're breaking my heart. It's true. Answer me this. Has he had anything to eat since he stopped struggling? He ain't done anything to work up an appetite. Has he eaten? Okay so he ain't. That don't mean nothing. It means a lot mister. Now where is he? Oh forget it ranger.   Well that's up to him. Looks like I'm gonna have to get in a hurry. One less load to carry is okay with me. Where is he? You know for a guy that's tied up to a chair you sure make a lot of big noise. I'm gonna ask you for the third time to just take it easy. I'm feeling a little pushed right now. I might fly off the handle if you start getting too noisy. That's better. Your long lost friend is in the cage in the next room where he's gonna stay.  Which leaves me. And I'm gonna go out, make a quick check on my traps, and then pick up my pelts and get. I reckon I can trust you till I get back. In case it starts getting dark, I'll leave this here kerosene lantern left. That way if your friends don't find you tonight fall, well at least have something to go on. Oh don't worry about me none. By that time, I'll be in the next state. Oh what a mess this is. Me tied up. It's no use. He knows how to use rope. Feels like my legs busted anyway from that bear trap. And bright watered.  There's gotta be something I can do. See anything at all suspicious from up there Ralph? Not a thing Bill. Sorry. What about Tom? Can you see where he's wandered off till? Nope. I think he's somewhere over in there. The southwestern sector. Thanks. Well don't seem to be too many immediate areas left to cover Stumpy. Just the northeastern region. It's a sure thing that a trap around foot couldn't spread his traps out too far. Especially if any knew he'd have to pack up and hurry. Right. Let's check that last area and then come back here and check again with Ralph. Maybe by that time Tom will be back with something of importance to tell us. In more ways than one I hope. Well both about maybe spotting where the trapper is hiding out. Maybe even seeing that bright water is all right. But especially that he's been thinking about what you said to him a while ago. About walking closer to the Lord instead of getting carried away what the Lord's given him. Well we ought to be able to cover that area in about an hour. Maybe then we'll know how the trapper, bright water and Tom stand. Let's go. I wonder how long I've been here. Can't see my watch. If only there was some way to get loose. If only say if bright water were free he might be able to. That's a long chance. But it might work. Hope the poor little guy isn't too far gone. Maybe if I call him the sound of my voice will give him the will to wake up and break out. Bright water. Hey little fella. It's me Tom. Bright water. Wake up fella. Hey. Is that him. Is it working. Hey little fella. Hey bright water. It's Tom. Come on bright water. Come over here to Tom. Please little fella. It's the only chance for either one of us. It is working. That's it bright water. You can break out of that cage. You've broken out of tougher cages than that. Come on fella. Come on. He did it. Come on fella. Hi little fella. I'm glad to see you too. Hey stop running around like that. We've got work to do. You've got to get me untied. Sure I'd like to play too. But I can as long as I'm tied up in this chair. Hey settle down bright water. I'll play as soon as I'm free. You've got to get me out with those sharp teeth. Traps in the whole area. I know. As I miss my guess that means that the trapper is working from some point over in the southwestern area. He probably would have more traps closer to wherever it is he's staying. I have a feeling Tom will have a lot more to tell us when they see him. You ain't just whistling Dixie Bill. There's only a little more of this area I want to check stop in then we can get back to the tower and check with Ralph. Too close for comfort. Looks like them rangers is closing in. I better get back to the car and get my gear and myself out of here and hurry. I got a feeling that that other ranger will have a lot to tell him too. But it ain't exactly what they're expecting to hear. Hey bright water please settle down and chew one of these ropes. We haven't got much time before that trapper gets away. Come on little fella please. How do you get through to an animal like that?  This isn't any time to play. Come on bright water. Come over here and chew one of these ropes loose. Bright water look out.  Now we both have to get out of here before we burn. Please bright water please. If only you'll cut through one of these ropes I can get us both out safely. But you've got to do it now. Now bright water the way that fire is growing we won't be able to make it out much longer.  Oh dear god tell him what to do. How about it Ralph? Anything new? Has Tom reported back yet? Nope. I haven't seen anyone but you and Stumpy in the last couple of hours. You think maybe he's found something? I don't know. It's funny that he hasn't reported back though. Yeah. What's the matter? Fire. I can see smoke rising off in the direction Tom went. Fire? How big a one is it? I don't know. Can't tell you. Glasses. Where do you make out of that Bill? I wish I knew old timer. Mine just be a coincidence. Oh it might mean that Tom has stumbled on to something and is in trouble. Right. There's Ralph up there again. Can you see anymore Ralph? Yeah. It's not a tree fire Bill. It's a cabin. An old cabin over by Bear Pond. The old cabin. Of course I should have thought of it. Most sure the trap sort of pointed in that direction. That trapper must be using that old cabin for his hideout. You want me to sound the alarm Bill? Keep your eye on the fire Ralph. If it confines itself to the cabin it'll be all right. If it starts any trees or brush nearby get a crew out there and hurry. Right. What are we gonna do Bill? Just what you expect Stumpy. We're getting over to that cabin on the double. Let's go. There's no way to get in there with a car so we'll have to double time it through the woods. If we hurry we can be there in 15 or 20 minutes. By that time there won't be a cabin to arrive at. I know. I still think we'd better get there. There's something funny going on and as soon as we get there to look the situation over the better chance we'll have a finding out what's what. Let's get moving. These ropes. Too well tied. Gotta get out.  If only you'd give me a chance to start again. To live the Christian life instead of just talking about it. I guess that's too much to ask. Do what you will Lord. I deserve it. I wish you could get out of here safely little fella. I'll look at him dash around. Yet there doesn't seem to be. Hey look out fella. He made it. He jumped right through the window. Hope he's all right. Wait a minute. That jagged broken glass. If I could make it to the window I might be able to. Can I make it though? I'll have to scoot this chair.  Gotta make it. Dear God please help me to make it. We should almost be there Bill. The way I figured the cabin ought to be just over that next rise. Right. See look running this way. Ain't that Tom's otter? Looks like him Stumpy. I don't see Tom with him. That might mean Tom's in trouble. Look he sees us turning around back toward the cabin. Almost as though he's leading us there. I've seen dogs do that before. Never otters. How many trained pet otters have you ever seen? That's the point all right. Just about to the top of the rise now. There it is. Look at her blaze. Looks like you were right old timer. About what? Well if anyone or anything were in that cabin when it started burning. Well it's obvious that no one could possibly be a man now and still be alive. Yep. You can say that again Sonny. Hey. Where's that little otter headed for? Looks like he's going straight toward that blazing cabin. But he might get himself burned. Wouldn't be running there if there wasn't a good reason Stumpy. I'm going after him and see what's up. You're what? Bill! Wait a minute!  Can you imagine what he came after? Unless it's impossible. Tom couldn't possibly be in there. And to run out as soon as the fire started. Oh so the roof is caved in now. I hope that soon now there's the corner. On the ground. Too near the fire to be safe. The smoke is almost overpowering. Better get him away from here before this wall buries his both. Look he honored that cabin. What's left of it? God didn't have to get me out of there Bill. He didn't have to but he did. You were very fortunate Tom. Bright water broke the glass and God gave me the strength to scoot over and cut the ropes and you helped pull me out. It was God moving through all of it. Just to give me a chance to live up to my word. Your word? That's right Stumpy. You fellas were right you know.  Out of my mind. Sure came clear to me when I thought that any second I would be in his presence. But he's given me another chance. Even bright water seems happy to hear that. Yeah look at him. Nuzzling up to you like that. That's right little fella. I still love you but I love the God that made us both a lot more. You helped save my life trying to save your own. God did it just because he's kind and cares for his own. Almost in spite of ourselves. What's that? Sounds like a jeep. Things back in here. Only by slow and careful driving between all the trees. Must be the trapper. Let's get him. Look there he goes. Got a good start. I don't think I could run fast enough to close the distance between us. Wait a minute. I don't know whether he'd do it or not. What are you talking about young fella? Only thing to do is to try. Bright water. Go get him. Go get him fella.   Not exactly but watch him. He's up to the jeep. Look at that. He jumped right on the driver. Legal trapper trapped by one of the animals he trapped. Let's go and check and I was shaking up friend. I know a good strong cage where we can put him. One strong enough that even bright water wouldn't be able to eat his way out. Well see you next week for more adventure with Ranger Bill was produced in the radio studios of the Moody Bible Institute of Chicago.


Assalamu alaikum, everybody. Welcome to Half-Bardin Offline. 142 people applied for today's event, but 70 amazing people made it to today's event. 35 brothers, 35 sisters, and we have people flying from all over. We have people from Arizona, people from Florida, people from Chicago, people from Forest Canada. So many states, two different countries, and they all came down because why? Because they know this event is different, this event is unique. As many of you guys will experience today, there is no speed dating. We're going to have fun activities. We're going to let you learn about each other in a fun and natural way, unlike anything you've ever experienced. As quiet as the room is right now, in a short amount of time, there will be lots of laughter. And within an hour, hour and a half, those rooms are going to be really loud, lots of excitement. And for a moment, you're going to forget that you were in a matrimony event. I know it sounds hard to imagine because right now, as you're sitting here, you're like, I'm so nervous, what's going to happen? Don't worry. Everybody who's tried our event for the first time, everyone's nervous, until you realize what makes it so unique. I just want to say thank you and Jazakal Khair for MCC for hosting this amazing event. And in shalom, we're going to be back soon. And for all those who missed out, you'll be able to go and tell them what they missed. Because they're going to say, how was the event? What was it like? And you're going to say this was unlike anything else and like, man, I should have gone. So, alhamdulillah, you guys didn't make that mistake. And alhamdulillah, you have the experience to go tell everybody how different this is. And once again, thank you, amazing MCC, for bringing us together and helping you guys find your other half. Let's get this thing started.


Look, Michael Jackson. Look, Michael Jackson. That's, uh, the Earth one? No, that's not Earth's song. That's Black or White. Oh, that's Black or White. Yeah. And that's Smooth Criminal. Which favorite? My favorite Michael Jackson video? Yeah, go. You have to name it right now. Do it. My favorite Michael Jackson video or song video? Look, Michael Jackson.  You need some Corbin. I'm Rick. Instagram and Twitter. It's so juicy. Ring the bell to download the notification squad. Cool. Uh, trailer. How old? 1989. Oh, right. Uh, with Mamouti. Uh, and it's called Masiluka. How old? Masiluka. How old? Uh, with Mamouti and Ador Gopalakrishnan. Oh, okay. Uh, Mahaluka. How old? The Walls is a 1989 Indian Malayalam language film written, directed, and produced by Ador Gopalakrishnan. Based on the autobiographical novel of the same name by Valkum Mohamed Bashir. The movie gives two viewpoints on freedom, which transforms from one to the other. Smoothly. Like a good beer. Ador Gopalakrishnan is an Indian film director, script writer, and producer, and is regarded as one of the most notable filmmakers in India with the release of his first feature film, Swalyamavarabham. Excuse me. What? Swalyamavarabham. Swabham. Um. To blame. To blame. 1972. Forgive me. Ador pioneered the new wave in films are made in the Malayalam language and often depict the society and culture of Kerala. Nearly all of his films premiered at Venice, Cannes, and Toronto Film International Film Festivals, along with the Satyajit Rai and Rinal Sen. Ador is one of the most recognized Indian film directors in world cinema. Wow. If you include those two names with it. Ador Gopalakrishnan has won National Film Award 16 times in various categories, including five for Best Director. Cool. Awesome. We need to watch more of Mahmoudi. Um. And this is great. This is... If it's not the oldest, it's one of the oldest Malayalam things we're going to be watching right now. Isn't it? Uh, I think that dancing one was probably the oldest. With the green face. With mohanu. It was pre-da. I believe so. Okay. Well, this is one of the then. It's one of the oldest. It's one of the oldest Malayalam that we've seen. Great. Uh, so, here we go. Inspector Sade. Yennez nathum nathum nathum. How many of you guys are gonna win during the day? You satisfied with boys or girls? What's the score? Um... One liter is one liter. Okay. Two. Six. You have enough brains. Um. A lot more, though. Let's forget about four. We lose the lottery at four months, a rigorous, cash- with the chances. So we have you on our side? Nathum nathum nathum. That's why people behind you Thank you, Sumi. Thank you. And obviously, I'm sure it didn't have a trailer when it came out. Honestly, though, the quality of the video that they had was actually quite good for we've had some real bad quality, really bad quality ones trailers before. But it looked interesting, like in terms of just I could see that the acting was good. I could see that at least the place it was setting was looked interesting. The thing that was most intriguing to me, there were a couple of points where I'm pretty certain he was talking straight to camera. Oh, yeah, he was. Yeah, right? Which we don't see a lot of that. No, fourth wall breaking is very rare like that. There's narration that happens, but not a character looking straight in camera talking to the audience. That doesn't happen very often in any industry, but especially I can't remember much of that ever happening at all in any industry in India. Yeah, especially older, because that just doesn't happen. No, you'll get the occasional look into the camera, but not direct breaking of the fourth wall and talking. What should be a classic Malayalam film if we can get to a classic Malayalam film this month? Should it be that? This is 1989. Oh, it doesn't qualify. Somebody did tell me though, like in terms of Malayalam, tell me if this is true. A lot of like the big classics don't start till after 80s for Malayalam. I don't know if that's true. You guys can tell me. I'm looking at like the classics and I'm sure it's going to have a bunch of Mahanol.  Not just not get to it this month. Yeah, it's true. Looks like there's one with Mahanol, which is God try to pronounce that. And when they pronounce it, it's just lies right off the top of their tongue. Yeah, with Mahanol. This is 1993, 1991. I'm looking at like best classic Malayalam. Oh, look, we got a 1965 here. Oh, Chameen, which set in the fishing village in Kerala. 1981. The challenge, as always, is how to get a hold of them. And not just for us, because when we get a hold of something, if we like what we've seen, we want you guys to have access to it in some way. Which obviously a majority of them are easier for you to have access to because in India, there's a whole lot of stuff you can get that we can't. Regardless, like I said, how is this film, in turn, we need to obviously get, we know we've seen, I think, each of them. Mammoody, I believe, or have we seen Mammoody? I think we've seen Mammoody. Just older. Yeah, but I recognize his face, but I'm used to seeing that face much older. Yeah, and then, was it Paramboop with the daughter? Was that him? Oh, I have no idea. I can't place that at all. Don't want the daughter, like remember that one with the name of the cabin and the daughter? Yeah. I don't know if that's him or if that was a different... Yeah, no, I can't. That's what I mean is I cannot, I can't place... But I know we've seen Mahano, obviously, but we need to obviously see both of them because our favorite actor in Malayalam is, of course, the great Fahad Faseel. Now that you said that, I'm wondering if that's him. I can't remember if that was a different one. But that would be the age I'm used to seeing his face when we've seen him before. Because this is obviously much, much younger. Yeah, yeah. It's at 89, right? Yeah. For this film, Mammoody. Is that how you pronounce it? Am I just white, white, whiting that? Whitenizing? Films in production? No, no, no. Yeah, that was him. It was him. Good call, Corbin. I thought we had seen him. And that's why his face, that's what I think of is that age. Those are the two in terms of... He was good in that. Just legendary, just Indian actors, but especially Malayalam, Mammoody and Mohanal are the two that are... They're the two good ones. And they basically say Fahad Faseel is the current age who grew up watching them. Yeah. Yeah. So he was so good in that movie? Yeah. We really enjoyed that movie. It might have actually got snubbed at our awards. Now that I think about it, it probably could have gotten some more. But it was a bunch that was snubbed. Yeah, so... We've seen almost 100 films. Sorry, something's gonna get snubbed. Happens with all the awards shows. So... At least we didn't include some other film.  I'm not gonna do it right now. So... I don't know why you take that.  Because it... You know it gains traction for people in the Oscars. If you get a Globe nom, Oscar people are gonna pay attention to it. I don't think the Oscars actually care about the Globes. It causes buzz. I don't agree. Watch. You watch the Oscars nominate. That thing is an international film.  That foreign film in the United States. And it'll be in the Best Picture category. It probably will. I can't wait to watch it. Better not be a part of it. And I don't want to take anything away from the film, but don't call it an international film in America when it's an American-made film. They probably called it the tourist that I named it. And you know, Hollywood Foreign Press, I know foreign is in your name. You need to change your category to international film. Thanks. Change your name to the Hollywood International Press. Just do everything I tell you to do. Because I'm right. Remember when they gave Stallone an award? See?