In this presentation we will record a journal entry related to the requisition of materials in a job cost system. We're gonna have the information on the left. We're gonna enter the journal entry into our general journal. First a word from our sponsor. Well actually these are just items that we picked from the YouTube shopping affiliate program but that's actually good for you because these aren't things that we're just given to us from some large corporation which we don't even use in exchange for us selling them to you. These are things that we actually researched, purchased and used ourselves. Acer 27 inch monitor. I've been using an Acer monitor as my primary monitor for a few years now. This is the first Acer monitor that I have used after having used a series of different brands of monitors in the past. The Acer monitor has been performing well and I'm trusting the Acer brand more and more as I use the monitor. I have a 27 inch monitor which I think is ideal for what I do which is of course the screen recording and the editing. If you would like a commercial free experience consider subscribing to our website at accountinginstruction.com or accountinginstruction.thinkific.com where we have many different courses. You can purchase one at a time or have a subscription model given you access to all the courses. Courses which are well organized have other resources like excel files and pdf files to download and no commercials. Here then posted to the general ledger and the general ledger will be used to create the trial balance. We can see the trial balance is going to be in order in terms of assets, liabilities, equity, income and then expense accounts. In the trial balance we're going to have the debits represented with non-bracketed or positive numbers, credits with bracketed numbers or negative numbers for excel and therefore the total debits and credits are equal to zero at this time, no net income at this time, nothing in sales cost gets sold or any of the income statement accounts. Our focus here of course is going to be on the tracking of inventory through the job cost system so we're going to be working up here in the work and process and the raw materials finished goods overhead as we work through this problem. Our goal here is going to be taking raw materials, the raw materials that are going to be in our warehouse represented by the raw materials account and we're going to be transferring them to the jobs and to where we can. We'll transfer them to the job and anything that we cannot transfer to the job we're going to put into overhead so when we transfer things to the job that means that it's going from the warehouse we want to take this stuff from the warehouse and we want to put it into the factory where we produce things so if we're making guitars we would take the wood or whatever from the warehouse and put it into the factory where we're going to start to make the inventory so that's going to be our idea here now if we cannot apply it to a particular job within a job cost system then we're going to apply it out to overhead so first let's just take a quick look at an example of a form that might be used to do this and remember if it's a large company we're going to have to do this with documentation to have a requisition form in order to transfer the inventory so the inventory we imagine is in the warehouse we might have something like a requisition form something like this this is just an example of a requisition form which would have the job number the materials the date of the requisition and what we want if it's planks wood requested by and it's going to be filled out by so we have this check in balance here so in a larger company we would have this requisition and this would be what the documentation would be to allow us to take the the raw materials from from from the warehouse and put them into a job and notice we're referencing here a particular job and that's going to be allowing us to assign it both in terms of the materials ledger card which is kind of like the material tracking the material within an inventory type system in the warehouse it's also going to be used as requisition form to for us to apply it to the job and we'll see that process here so we need to know which job it is so that we know what job it's going from out of the warehouse and what job it's going to into work and process and then we might have a materials ledger card this is just showing the inventory just again just an example form that would say that we're tracking basically the inventory in a similar way in raw materials as we would just in a merchandising company so for example we have anything that's going to be received here would have a receiving report number of units received units total price and then we're going to add that to the total here so that this is what's on our balance sheet at any given time at any given date so so on the balance we started with one unit at 225 or 225 then we got three more units i'm sorry we got two more units to add up to that three at 225 or 675 dollars worth of inventory and then when the inventory is taken out we do that with a requisition form similar to this getting these are just examples and the requisition form says we're going to want one unit at 225 and that leaves us with three minus the one or two units that are still left at 225 for 450 so these are just an example of us having to track the inventory within the warehouse and it's similar to us tracking inventory if we were a merchandising company and tracking inventory if the price is changed we have the same flow assumptions that problems that we'll have to deal with first in first out last in first out average cost our focus here though is going to be on the job cost so these are just going to be some examples of the types of forms we would need and now we're just going to basically say i'm going to scroll all the way to the left that the requisition forms that we got are these these requisitions forms for these jobs job b15 b16 b17 b18 and b19 we're going to start these jobs and we asked for materials for them with requisition forms and so then we also have some materials that are are small materials that we're not going to apply to a particular job of 550 and so that could be stuff like if we're making guitars or something i it's like glue or something like that the things that go into the guitar if we're talking about construction these might be small small materials and whatnot that it's not worth us tracking to particular jobs okay so that means that what we're going to do is take from a journal entry standpoint the journal entries the easiest part of this we're just going to take the information out of the raw materials and transfer it to work in process both of these being inventory accounts raw materials is an inventory account with a debit balance we're going to make it go down doing the opposite thing to it which will be a credit so i'm going to right click on uh raw materials right click and copy i'm going to put that on the bottom so it's on b5 right click and i'm going to paste it one two three just the values and we're going to credit it for this amount the two uh two thousand two hundred and thirty not including the 550 so it's going to be a credit of 2230 and then we're going to debit something for that same amount i'm going to do that by saying negative of this number or we could just type in there 2230 and it's going to go into the work in process account so here's the work in process account that's where it's going it's a debit it's a it's another asset account it's going to increase so we're going to do the same thing to it as its normal balance a debit so i'll right click on that and copy it put that in b4 right click and paste one two three so there's going to be our first journal entry let's go ahead and record that to the general ledger so we're going to go to the general ledger for work in process it's going to be one two three four accounts over so it's going to be four accounts to the right as well so if i go to the right here's work in process i'm going to just go back and forth from the screens a little bit we could freeze the pains or you could make the screen smaller like this so you can see more but i'm just going to try to scroll back and forth here so we're recording this right there in s uh nine it's going to say equals and point to that 2230 i'm going to scroll to the right a little before it's going to go from zero up by 2230 to 2230 this amount then is it's what's being used to create the trial balance and we're of course out of balance by that amount now now we'll record the other side and these you may not be able to use these if if it's locked but they're in uh they're in the formulas section here i've put them in the quick toolbar okay then raw materials raw materials is here here's raw materials third account it's the same order on the general ledger so raw materials is going to be down here so we want to be on the credit side so i mean so p 24 p 24 and i'm going to have to scroll up just a little bit to do this so i'm going to be in p 24 here and say equals and i would highly you could put it just a dollar amount here but i would use formulas as much as possible scroll up and we want that 2230 on the credit and enter and that brings the 550 down by 2230 to 147 770 that then can be found on the trial balance and it's going to put it back in balance here debits equal in the credits no effect on net income no effect on net income now i'm also going to represent this on the jobs as well and we're just going to have a quick little job sheet so that we can track these jobs so 1516 1718 and 19700 450 uh uh 670 180 and 230 i'm going to copy these i'm going to go all the way to the right and here's going to be our jobs so i'll put this down here again just so we could see it so job here's going to be our job sheets now these are just fairly simplified sheets but notice what we're going to have is the job number and i'm going to represent whether it be opened closed or shipped meaning we sold it and then we've got the direct materials direct labor and the factory overhead every job is going to include those three things when we start the job we generally start with the materials that's the first thing we do so now it's in progress and we're transferring these materials and we know which job they should go to because they're right here so we're going to say okay materials for jobs uh b15 is going to be that 700 so 700 we're going to say for b16 is 450 450 uh b16 is going to be here and that was 670 uh we're going to say that this is b18 and that's going to be 180 and then b19 is going to be that 230 so here's b19 230 now if we did this correctly if we add up these jobs which is this cell adding them up there's the total for all the jobs which only includes you know the direct materials at this point that should be equivalent to what's on the gl at this time so here's the gl or here's the trial balance which is equivalent to the gl and that's going to be the same as what's on the job sheet so notice that this number is being derived from this number and this number is is going to be supported if we look at if we look at this number on the trial balance we need to support it uh with with a subsidiary ledger in a similar way that we need to to uh support the accounts receivable with a subsidiary ledger in other words accounts receivable uh we need to support it not only with the gl given its detailed by date but by who owes us money we need a subsidiary ledger telling us by customer the same thing is true here we need the gl tells us by date what happened but we also need it by job because we need to track this information by job that's what these job cost sheets are doing so we're going to track over here each thing by job the job cost sheet has to match uh all the job cost sheets if we add them together has to match what is in the working process okay i'm going to scroll back to the left now and i'm going to do the last piece of this which is this uh indirect materials that's also going to come out of the materials warehouse but we couldn't assign it to a job we could think of it like a bind the glue for all the guitars we're making they just needed more of it in the warehouse we don't know which job it's going to go to we're just going to put it in there and whoever needs it uh can use it so then we've got the working process i'm sorry the raw materials is going to go down so i'm going to right click and copy i'm going to skip a line and skip another line to have a new journal entry i'm in b eight right click and paste 123 so the raw materials is going down again by this 550 but and then there's going to be a debit so i'm going to do that with a negative of this number or we could just type in 550 and now we just need to know what that account is going to be it's not going to be working process because we can't apply it to a job so we have to put it in this bucket of overhead we will apply it to a job at a later time but we'll have to do some type of estimate in order to do so so i'm going to right click and copy the factory overhead put that in b seven right click and paste 123 and now we'll record this out so here's the factory overhead here's the factory overhead it's like one two three four five six over so it's going to be the same order on the on the gl and the factory overhead is going to be down here actually it's in uh s 25 factory overhead debit side so i'm going to put my cursor in s 25 and say equals and then go left and i'm just going to scroll up till i find this and so there it is i'm in c seven and enter so it went from zero up by five five hundred fifty to five hundred and fifty and again if you double click on it it's c seven this number then is being used to create the trial balance here and we're out of balance of course by the 550 till we record the other side so then we're going to go to raw materials here's raw materials it's the third account it's going to be the same in the gl so here's raw materials uh down here it's a credit again so we're in p 25 p 25 we'll say equals i'm going to scroll up just a bit and pick up that 550 and it's going to bring this 147 770 down by 552 147 220 that number then of course used to create the trial balance here and that puts us back in balance debits equal in the credits and we have net income nothing right now and notice that's going to be the case for pretty much this whole like job cost system until we sell the the finished goods and then it'll be affected by cost of goods sold so all this activity we're doing here is really just going to be moving throughout the assets more specifically moving throughout inventory asset type accounts


You are the dream station. Now we have to realize that we aren't going to go from being identified as a person and a body into pure spirit without a transition face. It would be too frightening if, you know, like in those magic shows where they pull the tablecloth. You've seen those times when they pull the tablecloth out and all the china and the silverware that goes flying everywhere just shattering and flying. We're not being asked to go from body identification and person identification into pure spirit. This body is part of a self-concept I'm going to call the doer. And you and I know what that doer is about because there's a lot of hard work that the doer goes through to improve the self-concept. It doesn't really get us anywhere. It's kind of like spinning your wheels in the mud. You've got the odometer going up to 70 miles an hour and you're not moving because the wheels are spinning in the mud.  Okay, that's fine.  We can deal with this. We've got a mud spinner here. We can deal with it. We're finest fates, but you don't know that yet, so we'll work with it. What happens is the only way you go from doer to being to pure beingness is to be done through. Doer done through beingness. So when I gave everything over to the Holy Spirit in my 20s, it was just saying take me to the beingness. Excuse me. I was ready to have a still mind. Has anybody in here tried to meditate? You know, is the monkey mind surrender at the first one minute of meditation? No. In other words, I went off. I left the ten years of university. I went off to a hermitage in the woods of Kentucky. I took my course book down. I was going to meditate as many hours a day as I could and everything.  I've had you in my grips for millennium. I've had you in prison for millennium and you think you're just going to come down here and meditate me away? Ha! It was a James Brown. Ha! And so I tried and the ego just laughed. It snickered. You know, he was thinking, sorry, I'm going to list simply like Henry David Thoreau and I'm just going to make bread and I'm just going to eat bread and drink water. And he goes like, ha, come on. You're going to starve me out now. You're going to try to get me with asceticism and it's just snickering and laughing. And initially, you know, if I had to stay there in the woods, try to just sit there and meditate, I don't know where I'd be now probably looking like Buddha with the long hair and the long fingernails and whatever. But basically the Holy Spirit of Jesus said, listen, I'm going to have to use you because you are so identified with that body and that person of David. I'm going to have to use you.  I'm going to have to perform miracles for you. I'm going to have to speak through you and laugh through you and hug through you and shine through you and it's going to take as long as it takes but this is the way you're going to come to this illness. You're not, it's time consuming and tedious but you're just to sit there in this little travel trailer in the woods of Kentucky and this is not the fast route. This is not going to save time. It'll get you there some lifetime but if you really are wanting to get back to heaven as quickly as possible, you're going to have to be done through. You're going to have to be willing to be done through. No small task because I was voted most quiet in my senior class and they told me don't go talk about God or politics in public and now I threw in a few things on politics but this is how I do it but I talk a lot about God and I've been done through for so many years so to speak and unfortunately that's where the stillness has come in and that's just what Francis has been talking about that she didn't leave behind her country and her family her husband and business and all these things just for the sake of it like she gets brownie points for how many things she can drop it was more to really be used in purpose that just helped free her up for her purpose and mission and then the stillness comes naturally when we're aligning with God and letting God do it through us This peace that you are This peace that you are


All righty, we've waited long enough for folks, so we might as well get started. So hope everyone could hear me loud and clear. Let me go share my deck really quick. Hello everyone. Hi, hi, hello, hello. I'm gonna go share my screen in a second. Cool, everyone see it, see it? Yeah, yeah. Cool, so yeah, agenda today. So we'll do some introductions, then we'll have some community presentations about 15 minutes each from the Gremlin and Chaos Toolkit communities. We'll talk a little bit about the status of where we are at the landscape, mostly me asking help from everyone and trying to come up with some reasonable categories on how to categorize at different technologies and chaos engineering. We'll also talk a little bit about the white paper based on community feedback. I uploaded it cut to GitHub so we could bang away at it via pull requests instead of Google Docs, which seems to be favorable to a lot of folks. And then we'll kind of end things out. But first off, it would be great if we could get some introductions from folks, especially if you're new on the call. So any new faces from last time want to speak up and say hello. Cool, I'll go ahead. My name is Roman Kane, I'm up in Seattle. I'm working on an early stage start up here called Fuzzbox that runs our failure simulations on your production artifacts, so great chaos adjacent. So that's why I'm here and interested, so thanks. Cool, very cool. Anyone else? Yes, hello, my name is Alexi Ledinev. First time joining this call. I work on Open Source Project Pumba which is chaos testing for Docker containers. Okay. Awesome, glad to have you. Anyone else? Anyone else here? Yeah, I can go. Hi, my name is Julian. I'm currently in Stockholm in Sweden and I'm a software engineer. I'm doing a lot of Kubernetes and Docker work these days and I'm really interested into a chaos testing and especially the continuously testing production environments. Awesome. Anyone else? All right, that'll be interest for this time. We'll try to make sure everyone has a chance to introduce themselves that is new every time. All right, let's go move on. So, presenting mode again. So, landscape, so one of the few things that we wanted to accomplish from the working group is to kind of produce not only a list of kind of the different chaos engineering projects and products and tools out there, but also attempt to categorize them. And I've been bashing my head a little bit working with Sylvain and some others that kind of come up with initial idea, but I would love to hear from the group if anyone has an idea in terms of how to categorize things. So whether you could, the simple things you could categorize by like hosted solutions versus, maybe frameworks that run client side and our driven client side versus maybe chaos engineering tools that are focused on security. So having an idea of how to categorize this thing is definitely something I've been trying to tackle. So I'm asking folks, we could have probably like a five minute discussion on the call today, but there's a GitHub issue open and if you kind of have ideas of how to kind of categorize things, it would be great to hear because that's essentially going to drive the landscape that will be produced by CNCF for this work. So I don't know if anyone wants to take a stab at this. I know Sylvain, you had some thoughts that we chatted over email, but I'd kind of love to hear from the group if they've got a picture in their mind of how this should be categorized. I've got actually a good question, Chris. How did that work for other working groups like serverless? So anything, did they go through the angle of the market, of the tooling, what was the rationale for? Well, I mean, it was a lot of bike shedding for ever to kind of come up with the categories. I mean, first we started with a list of serverless projects and things, right? And then from there, we tried to break it up in terms of categories. And that kind of what makes sense. So that's kind of the approach we took. It took a long time. And I was trying to use that framework to apply to Chaos Engineering because obviously there's seems like there's an upstart of kind of hosted offerings, with Fuzzbox, Primalin, KSQ, et cetera.  Security context or, you know, some other context. So I'm just asking how to categories things from like what are people's thoughts on this? Yeah, I have some sense that focusing on the context, like whether it's security or something like that may not be the right way, even though it seems like it might to begin with. Yeah. Just because I think, yeah. I think like reading the Chaos book and stuff, like coming at it from the perspective of like either running experiments or I think Julian mentioned, like continuously running tests and that kind of thing. It's maybe more of the way to dissect it. Cause I think at some point you get into the concept of like duct debt and things like this, where it maybe isn't necessarily applicable to very clear domain. So, you know, more and more ways of applying Chaos. Like by its very nature, Chaos is ethics, therefore not. Easily customized, maybe. I don't know.  I also like, you know, there's some, you can maybe even say like whether it's actually in production, whether it's like, you know, how Netflix do it with sort of canarying almost how it gets applied versus what it's being applied to. Like this is what I was poorly trying to say.  So almost like what's the scope of how you're applying it? It might be a way to break it up because I think there's different stages in sophistication to where you apply each of those. And that might be a way to kind of step through the tools. Yeah, I think that's very true. I think there's a case to be made of here's the technology and here's the philosophy. And the philosophy might be a great place to start and then technology is a doctor, is it Kubernetes, is it fair, model, is it whatever? Yeah, yeah, I mean, you know, I'd also ask people to have some like, you know, empathetic thoughts from like an end user perspective if you're trying to like evaluate with tools out there and like, hey, I want this to stop the work against AWS or Kubernetes, you know, making it easy for them to find that, at least from that perspective is super useful. So I'd like us to also make sure that's somehow possible from like just an end user perspective. That's a great point. How do you get started? I've been told I have to do this thing at work. So where do I even begin? Yeah, yes, yeah. And I'm running on Azure or something. I want to make sure this stuff works there too. That type of perspective.  Yeah, there could be multiple kind of accesses of a filtering, you know, I'm not asking for like a complete, you know, solution, but for folks to kind of put their thoughts on that GitHub issue and for us to kind of keep iterating on this, eventually I kind of want to get to a state where we have kind of a rough agreement and then I could work with our design team to start sketching out how this is going to look and then we could kind of continue to iterate on that. If I may, I've been maintaining a Docker repository for that's called Awesome Docker. Yes. Been basically doing that for like four years and I can tell you the pain of trying to categorize a landscape that is shifting under your feet all the time. So with the other contributor, what we came out, the main idea was we split everything into use cases. So who is it for? Not what does it do that? Who is it for? And from there, most people find like the common terminology and can relate to keywords much easier and find their way and contribute to the list as well. So that's a way to involve the community around it. Yes. So this would definitely be like in an open source fashion where anyone could contribute their thing to the landscape. We already have, if you go to something called l.cncf.io, you kind of see what we've done for the wider cloud native landscape. It works pretty well because community members tend to police themselves, which is beautiful. It's a beautiful thing to watch to make sure that things are kind of categorized properly. But it's for us to kind of come up with the categorization scheme. So yeah, it's basically all the time I kind of want to spend on this one just because we have demos and I'm really excited to see them. All I ask from the group is to throw some ideas on the GitHub issue that I've linked to and we'll kind of go from there and try to do that work stream in async fashion as possible. Cool. All right, so moving on. So next up we have two community presentations, kind of see how people are doing chaos engineering in the wild. So first off, we'll have Eugene from Gremlin talk a little bit about what he's up to and then we'll have Sylvain to talk about chaos toolkit. But let me stop sharing my screen so Eugene could get going. Cool. Thanks, Chris. You there, Eugene? Yeah, sure thing. Actually, I'll share that screen and just move over to the slide. Yeah, sure. Give me a second. Yeah, no problem. I'll get going. Sorry. Oh, God. Here we go. OK, got it. That was good. Thanks, everyone. So hey, my name is Eugene. I've been at Gremlin since July last year. Just want to, whoa, is the slide OK? Seeing a little bit of artifacts around. Got it. Good now. Very good. Cool. So the company itself has been founded in 2016. Colton left that point in time and recruited Forney to be CTO to start working on this product to make chaos engineering available for basically the rest of the world since we've all seen it work at places like Google with their dirt exercises at Dropbox similarly with Tammy and her dirt exercises and also with Colton at Netflix Chaos Engineering and then Colton with Forney doing chaos engineering and making having a tool, building a tool internally at Amazon retail. So we know the value at the corporate level and so we're just trying to make it available to everybody else. Gremlin itself installs in a myriad of ways. One of them is a Linux package.  Or you can install it as a Docker container. Pull us from gremlin slash gremlin on Dr. Hub or as a Kubernetes daemon set. So I've seen a lot of our customers do that as well. We have a CLI interface such that you could SSH into any host to run gremlin experiments. We have an API as well for automation as well as a web app just to make it really easy for people to dive into all the types of failure modes that we could introduce into your ecosystem or otherwise just to properly scope your attacks. One of the things that I find very valuable when helping our customers scope out chaos engineering experiments is that they go, where do I start? You go, well, if you don't have this nice rich UI to say to give them all the parameters, it's really hard to get started because I could just blow up a whole auto-scaling group and I want to see what happens. Well, start small and we could help you scope that out properly. We also have a built-in scheduler. I think one of the things that we all hear a lot is about automation. And so putting things into the scheduler really helps you maintain that floor of resilience in any of your applications. Finally, we also have this HALT rollback feature or a dead man switch where if you think that you're causing a lot of damage and you really want to stop it from happening, we have a HALT like just click on it or otherwise use an API to stop the attack. And we'll be able to stop and get back to steady state. Alternatively, just to stop things from going wild and our client loses control to our control plane, you can then, a dead man switch on our client will kick in and then roll back to steady state automatically such that you don't have any uncontrollable chaos within your ecosystem. So that's it for this slide. Let me go ahead and get into the demo really quickly. Let's see. Let's just go ahead and put my screen. Here, I need to stop sharing. So again, just like. Chrome? Cool. Now go for it. You should have permissions now. Cool. Let me know when the screen shows up for everyone. Can I copy it? Yeah, works for me. Fantastic. So right when you log into our service, this is the UI that you're going to get. If you have clients already hooked up to our control plane, you could already begin to create your first attack. Otherwise, put things in the scheduler and finally just to manage your clients or users that's connected to us. I already talked about the way of installation. So I'm not going to usually talk about that with our prospects and customers. So I'll just skip on that and go right into the types of attacks that we could run. Right now, the client itself is focused on infrastructure level attacks. So things that happen on your host, things that happen on your operating system, things that happen on the network, all those things we have a good suite of attacks that you could run with Gremlin. So resource attacks, first off that I'll start off with, is things that happen on your host. We could consume host cores. So the amount of cores that you have on your host or your instance, for example, you can specify the exact amount of hosts that you want. We could specify the amount of disk space you want us to fill. What happens if our law of rotation doesn't happen? We internally got bit by bit. You should check out our blog post at gremlin.com. And finally, we could also introduce disk read-write activity. For those of you that have a lot of disk intensive tasks, this might be a good gremlin to run if you have a lot of heavy IO operations. And finally, too, we could also consume gigs of memory. Notice that every single one of these attacks, you can also save as a template. When you have this attack that you find that you're going to recall fairly frequently, some of these attacks might be a little bit more specific and highly targeted. So as a result of that, the configuration could take a little bit of time, save it as a template. That way, you could bring it back in the future, or at least throw it into the scheduler so that you can then just automate that particular attack. State gremlins here alter the state of your operating system. So for example, we have a process killer here where we can string match the process that you sent to us, and we'll just kill it perpetually. What happens if your web server like your HTTPD were to go away, or your Java or your Tomcat app were to go away? Does health check pick that up? And then otherwise, terminate the host or start recovering from it? Good thing to test with this. We also have a shutdown gremlin. So what happens in, say, public cloud, right? Like AWS, that failed health check, your instance is going to get terminated, or meltdown.  You don't know when it's going to hit, but it's going to hit. Use the shutdown gremlin for this. One of the key values that we have here is that if you use this in conjunction with our scheduler down here, and you say, oh, run this during business hours, right? Nine to five, we're running the shutdown or reboot gremlin five times a day. Well, you basically then would have that chaos monkey experience right out of the box for yourself right there. Final state gremlin that we have is time travel, where we'll break NTP and introduce clock skew. Many times I hear from our customers that when you introduce this in, say, your casserole cluster, terrible things happen. Maybe you want to see what happens in your own world for your data layer. Otherwise, things like day life savings time is also something to consider a certificate on your hostware to expire. That is good thing to simulate as well, or a leap year. Now, the final gremlins set of gremlins that we have are the network ones. And these tend to be the most valuable and most powerful ones because in a distributed system in AWS or any kind of cloud provider, the network tends to be the most fragile point. As you're breaking your applications from monolithic to microservices, your network is now basically part of your application stack, right? You expect it to be high performing, but really some things happen because, well, cloud happens, network devices have built in entropy to them. Definitely want to simulate what happens when things become degraded or otherwise unavailable. The black hole gremlin here drops out packet going from one place to another. So you can simulate something like a full service unavailability. Notice that all these network gremlins have the most amount of arguments that you can pass to it. And I really just want to highlight the concept right here that we could actually simulate full service outages. Now, some of you might remember this great outage that happened last year called the S3 outage. And we can simulate that for you out of the box just by adding that as a service provider right here. The next gremlin that we have is the DNS gremlin and we could break DNS for you. You want to test what happens if your primary DNS server were to go away. Do your host actually do secondary fallbacks to your secondary server? Definitely something to worthwhile to check. Otherwise, you can simulate bigger DNS outages like Dine DNS, right? Or Ultra DNS that happened a few years ago, or just maybe Route 53 being unavailable as well. These last two gremlins latency and packet loss are the ones that I would call gray states of failure. Your systems are running, but due to things like noisy neighbor or having to traverse through a lot of internet traffic, things become slow or otherwise degraded. So it's not operating at its most efficient point. So the problems usually manifest themselves in the form of latency, right?  You've seen the menus here, so I'll just go ahead and talk a little bit about it. You want to dial in how long you want to run the attack for. Sometimes your observability or your monitoring tools take a little bit longer for the metrics to show itself. So you can definitely specify how long you want to run the attack for. You can specify things that the IP address, IP address range or side block level.  Or if you want to have an external, your service has a third party dependency to something for messaging like Twilio, you can do that as well. If you want a whitelist particular traffic, it's just a carrot right here. So maybe you want to whitelist your monitoring just so you can have some observability into this chaos experiment. We could also support port ranges. And finally, you can also specify what protocol you want. Once you're done defining the attack, you now want to specify the targets that you want to attack. And by this, we're talking about the blast radius, if you will. So to help you with this, we pulled down for AWS instance metadata here where you can click on any of these bubbles to filter by say region or availability zone. And finally, we also support services that you could pass on to us as well so that your hosts are serving up a particular application. You can specify that. One of the things that I like to highlight here is that it's our concept of random. While most of the tools that we see say, do random, do it in prod, we kind of say you want to still be a little bit targeted. So our concept of random here is that we take all of the clients that you have installed with us and then three of filtering like say, I only care about things like things up, like our API, for example, you'll then pull and although my filter all the clients that are serving that particular service, and then you could then specify, well, I only care about maybe two hosts here. So go ahead and use that as my target. Or otherwise, you can also support a percent of our environment is impacted, right? So maybe I would say 50% of it is, sorry typo, 50% of it is going to get impacted.  We don't use it right now.  Once you've done specify your attack and you kicked it off, it'll take us over to our attacks page where you see all the current attacks and also all historically run attacks.  So you're gonna see a lot of attacks in the Gremlin plain, for example. Once you click in, you get to see the full attack definition. All client logging comes back up to us so that you don't have to remote into a host so to see what's going on. At any given point in time, you feel like, again, you've done enough damage or I need to roll this back because I made a mistake and I fat fingered my attack, for example. We have a halt button right here. Our client will pick that up within seconds and go back to steady state within seconds. Everything I've shown you, again, full feature parity with our API, right? We don't circumvent ourselves via the web app or anything of that sort.  Well, spin up a canary cluster, install Gremlin, run some resilience tests on it as well to get some confidence in the resilience of your systems. So that's the demo for Gremlin. Hope you all enjoyed it. Maybe if there's any questions around that I might be able to answer for everyone. Hi. Can you guys hear me? Yes. Yeah, yeah. This is Hemant from India. I work for VMP. I have experience of one year working as a case engineer. New to the group. I forgot to introduce myself in the beginning. So my question is, you were mentioning that you can write some tests to test to post the Gremlin attack. Is there any provisioning in Gremlin where I can switch these tests? Where you can, I'm sorry, do what to the test? Can I run these tests through Gremlin? Yes. Well, you do run everything through Gremlin because we have the client installed and then you can use us to orchestrate the attack for you. Okay.  Yeah, please visit gremlin.com. We'd love to speak with you further. Just go ahead and request a trial and we'll be on our way. Okay. Yeah, fine. Thank you. Okay. Well, there's nothing else. Thanks for the time. Hey, just one question. You're like, I was just curious for the, this is Deepak from Capital One.  Like, are you using any TCP libraries? What are you using behind the scenes? Sure. For Linux, if you're familiar with TC, it's something similar to that. Okay. Yeah, most of the production boxes I've seen like Linux OSS, so I believe, yeah. As long as we have access to run the TC commands, we should be able to achieve that, right? Right. I'll defer to Fornee to talk more about what's under the hood since he's the developer here. Yeah, all of our gremlins use like core Linux libraries to do the impact. So yeah, if you have the TC library, you're good to go. Okay. Most of your demo around the AWS end point, do you support any other remote machines? We support Linux and other computer environments. So if you run those environments, you're good to go. We currently do not have a Windows environment, for example. Okay. Can you schedule a tax against like the Kubernetes API, for example? I am not sure about the Kubernetes API specifically. Throw it away in here. Yeah, please do. No, not against the API right now. We're adding in a bit more container and Kubernetes support. Okay. Originally kind of built for bare metal and our, you know, EC2, that sort of thing. And now we're kind of iterating on that build right now. I think that's enough. Cool, thanks. Everyone, so I wanna get a little bit more detailed. Can you share more details about what are you planning around Kubernetes API with gremlins? I mean, I can't share exactly what we're planning right at the moment. But suffice it to say there'll be better Kubernetes support. How about that? Is there a timeline that can be shared? Not at the moment, no. Okay, thank you. Are there any plans to integrate with kind of any of the service meshes out there, like Istio or Conduit to essentially, as you're doing a slow rollout, also integrate kind of gremlin testing as part of that to ensure things are kosher before doing a full rollout? Yeah, it's definitely something we thought about. We're sort of just getting past the POC stage right here. So there's a lot of things we want to do, you know? And it's sort of figuring out where the, this squeaky wheel gets the grease sort of thing. So containerization has been a real big part of our past roadmap. Okay, can you go into a little bit of the telemetry that you get after you've run an experiment? I see like there were some logs on your dashboards. Do you get any sort of visualizations or anything like that? So right now we primarily, we've kind of like opted to stay away from integrating with monitoring just because it gets a little hairier when you start to take some of that information. Plus there are a lot of great monitoring solutions out there. So we tend to leave these sort of things to light step and data dog, those sort of things. I'm sure, you know, there's opportunities to expand into that space in the future. It's just not been, since it's not sort of our core competency, we've sort of let them do their thing and let things kind of line up in the monitoring dashboards. Does that make sense? Yeah, sure, cool. My question was actually centered around monitoring as well. So how do you guys interface or do you interface it all with things that are tracking like SLOs, SLAs to like make them put them on like a quiet mode or like would you even want that and like kind of subnote I'm new to this. So maybe that is something that you want to see if your SLAs are affected by such a thing. It's a fantastic question. Since we kind of stayed away and it's kind of hard to do, I guess SLO and SLA definition generically, a lot of companies do them kind of differently. We've sort of not integrated into that space just yet. And that's fine. Like I heard about your statement on core competency. I think that's great. But like being able to tie into something like Prometheus or like maybe making it so it's not going to go page like an entire engineering team while you're doing tests like this, maybe at least in a controlled setting, but... Yeah, no, you're totally right. I guess what we sort of, what we usually tend to advocate is over communication in that regard. So if somebody doesn't get paged, they know that they're getting paged because we're running testing. Obviously, yeah, you can turn off your paging, right? You can turn off whatever pager duty or silence these sort of things. Oftentimes though, actually we want to do this to see that a page actually goes off when something bad happens, right?  So it's kind of like unit testing your paging and I don't know, just the idea of making sure that your on-call knows what to do, testing engagement, spinning new people up. You can do it either way, right? That's a fair point. Yeah, no, that makes a lot of sense. Thank you. Right, I have to agree with Forney on this point. Many times when I run game days with our customers, it's not so much finding posts within the application or more so making sure that they have their observability, their monitoring, their paging dialed in tune. And a lot of times when they go, this happened, I never got a page for it. Yeah, you follow up here as real quickly to get that dialed in guy. Otherwise, it's gonna be, this is already in production. Okay, cool. I have another question. Oh, sure, one more question. Where, Chris? No, no, I'm just saying one more question to ruin and then just to be sensitive time till Sabane's presentation. Go ahead, ask your question. Yeah, so I would like to find out if there is any integration with CloudWatch events, like let's say if my auto-skilling group is going up and down too fast. Now, is there any integration with Gremlin where you could trigger some tests to give me some more details about it? Go ahead, Forney. I'm not sure I understand the question entirely.  I'm not sure that there's like a direct integration in terms of CloudWatch events. I'm not sure like what, I'm not sure what your hypothesis is here that you're trying to accept or disprove, I suppose. So let me ask differently. Has any customer asked for integration with CloudWatch events, particularly in the AWS land, because that's where sort of my state of my cluster, all the events, et cetera are thrown? Sure, people have asked, people like, I don't know if you know engineers, they ask for everything, they ask for everything under the sun. Yeah, it's been asked, we're slowly rolling out more integrations and sort of prioritizing what our customers ask. They definitely ask for that. They definitely ask for other sort of things as well. Sorry, I can't be more specific. No, that's good. Thank you. Yeah, no worries. Okay, cool. I just want to make sure that we're sensitive to time, but thank you Eugene and Matthew for the presentation. That was super cool. All right. So we've got about 20 minutes left. So it's about 15 minutes for Sylvain to present with some five minutes for questions. So Sylvain, are you there? Yes, I am. Yeah. Awesome. You can put the slides as well as you did for Eugene. That'd be nice. Yeah, I'm trying to go find that right now. Give me a sec. I'm afraid things won't look as... No, no worries. As they did for Gremlin. No, no, it's different tools. Eli, I'm not that very glad, Maros. Different tools. Okay, so hopefully you see everything. Yeah, so hello everyone. Right, so I'm going to talk about the KOSU kits and open source default that Rasmus and I have started in September, I think, last year. The idea was roughly that we saw that tools like Remlin, Pumba, or KOS Monkey obviously were there. But as we were trying to figure out how to apply the experimental part pattern that we had read about in the KOSU engineering book, we felt that those tools, while actually delivering the goods, weren't helping us forging the experiment, if you will. So we decided to create the KOSU kit to do that, basically. Yeah, so the KOSU kit does, by itself does nothing like Remlin does, or others.  So the KOSU kit wouldn't actually provide anything like Remlin, but does actually drive the API if you wish to use Remlin. For that matter. So basically it's just an open API for your experiment, if you will. It's a CLI driven. We felt like we wanted something we could automate that way. That's why we didn't care for UI at first, or initially. A target simplicity, I'm talking about the code itself. Well, we wanted something that other people could actually contribute to. And we tried hard to actually make things as simple as we could. So it basically, it's just a bunch of functions glued together in Python. Well, it's a bit more than that, but that's that rough idea. If you want to contribute just, you do need to know Python to a very basic level. What it does, it orchestrates existing tools or API. By existing tools, that means that if you have a binary that you want to drive from the KOSU kit, you can call it. But equally, if you want to call an API, you can also just call it, passing all the parameters the API requires, and simply it will call that for you. We already actually implemented a set of drivers. We call them drivers, but just extensions to KOSU kit, really. We don't claim we support all the API of those providers that will be foolish and just a lie. But we try to target API that people don't necessarily trigger very much, like stop a service or stop, remove just a Kubernetes service or things like that.  Well, those APIs are very powerful in production or pre-production or wherever you want to run them to actually impact your system, if you will. So for example, if you want to remove a service or if you want to terminate a pod, just call delete pod, basically that's it. If you want to destroy a pod, that's different. But if you gracefully just want to stop something, you can do it with Kubernetes. And we started to implement things like that for all sorts of providers. Azure with service fabric is a bit different because they already actually have KOS services native to the platform. So you don't actually call, you just call start KOS or stop KOS, much like Istio, I think, which has fault injection. And when realized, well, causing trouble is fine, but we really need some probes as well. Like you guys said earlier about coding your monitoring tool is fantastic, but we wanted during the experiment to be able to collect the data that mattered to us in that regard of the experiment so that you can support your analysis after that. So we have probes. Basically, we call, we query, you can query Prometheus or Umiyo if you use that as a central logging platform. And that basically all that is contained in the file that I'll show you in a minute. We've got a bunch of plugins for creating reports and sending Slack notifications. And finally, the future of KOS circuit is we're going to go more native in Kubernetes with Chrome job so that you can schedule things and just run, let them run. We're looking at operators as well to actually control a bit more the experiments when you run natively into Kubernetes, but that's just starting to think about that. And drivers in those are run times. We run in Python and we're not, we love everything. So if you want to run your extensions and go on Rust or anything, we're going to try to make it easy to actually call it from the KOS circuit as best as we can. And we are trying to aim for milestone one this year at some point. So that's it for a very quick review of KOS circuit. It's open source, it's Apache license. And now I'm going to try to demo something. If the demo dots are with me. One second, I will exit and so you could share your screen. Yeah. Perfect. Right, indeed. Share my screen. Should be good to go. Yes, let's speak that one. Right, so that's a website. Like I said, it's a CLI driven so nothing very fancy to show here. The idea is just to work through the important bits. Like I said, we try to create an open API. So the open API is, it's just a definition of the various elements of a KOS experiment. That's what it looks like, briefly. You've got a set of metadata, blah, blah, blah. What's interesting is you've got the steady state here. The normal in your system. So what we do is that is we use a bunch of probes, you can have as many as you want, to query for some things in your system. And what we're going to do is if any of them fails at tolerance here, it's just a bully and it could be something else, we bail the experiment. Because in our mind, if your system is not normal, at least in what you expect to be normal, and there's no point actually in going through to cause trouble because you won't be able to read, analyze, and make sense of what you see. So we bail immediately. But we run that steady state hypothesis at the end again, once we've caused trouble to see if we deviated. If that passes again, now that means two things. Either you ask the wrong questions, or you find a potential weakness. So at that stage, what you want to do is basically go into the report and see what happened and make sense of it as a team. Now you've got the method.  Usually you've got one or two actions because you want to make sense of what's happening. So if you change too many things, I guess it's similar to what Gremlin is doing. You can't create attacks, I suppose. You're trying not to create attacks that conflict each other. Otherwise it's probably much harder to actually make sense of what's happening. And then you've got rollbacks. We tend to call them remediation these days because to us rollbacks are strong promise that you can come back to normal state, which is not always the case if you're really broken in your system. But the idea is sometimes you want to come back to steady state. Now with Kubernetes, usually rollbacks are empty because Kubernetes is meant to actually support and deal with failures automatically. So you don't actually do anything there. Right, so that's it. It's a JSON file that is declarative and what happens is you define your probes actions. They all have the same format. So let's pick that one. It's a provider, it's in Python. It takes that module and that function. In this case, it doesn't actually have any parameters or arguments. In this one, you can actually specify the name or the label, things like that. They are just functions basically in the Python module somewhere, but you declare them and you can share them on GitHub and you can, basically see the, we wanted to have something on file so that you can really use that inside your CI CD pipeline as usual. It's just another source thing. Although I'm trying to not sound like a test, it's certainly overlaps with the tooling in some fashion. And you can have reference existing probes so that you don't have to actually duplicate things. Sometimes we do have a pause. I personally dislike that, but I couldn't see any other fashion except if I was doing synchronization with a stem telling me how it was doing. So sometimes it's a bit flaky that thing. So contributions are very welcome to actually improve the API definitely. All right, let's try to show an experiment here.  We've got that application, which is this one does nothing. That data that you see is pulled from a Postgres database. And what we want to see is under some medium load, can we actually kill what happens if the database master actually dies? And behind the scene on Kubernetes, what we're using is patch money from Zalando, which has a leader and follower for Postgres and will shoot switch from one to the other if the master dies. And that's what we want to prove because we expect that if the master dies, we don't actually impact our users. So let's see, it looks actually, probably it's more interesting. That's not the one I want. Right, can you see that? I'm not sure I'm zoomed enough. So please do tell me if not. All right, sweet. So what we have is exactly the same what I showed you before we select the application that we're interested in. That's, we checked that the pod is alive, the application must respond. And if that doesn't happen, the experiment bails immediately. Otherwise it goes to the method. And here what we do is we terminate the DB master and we don't have actually a function doing that. What we do is we terminate the pod, the pod that has that label. And luckily enough, we only have one. It's a demo, blah, blah, blah. Round is here means nothing because again we have only one that matches that label. But if you had many, it would actually pick one through that argument. And then we've got a bunch of probes. Now you might wonder why I'm going and fetch logs. During the experiment doesn't actually do anything, but it's interesting why when you do the analysis, because you can come back and look at if you had the logs that you were looking for in your application or in your various parts of the system. So for your analysis, sometimes it's nice to actually go and fetch them as you run the experiment. And that's basically it. So let's pray that this works.  I don't know if you see that, but there is a notification on the top right because we send that to Slack saying it started. And it basically doesn't do much. It runs things in order that, it reads them from the file. And that's why it does look like a test because it does, doesn't it? In this case, it should fail if I'm correct because the application will collapse. There you go. So here, the reason it fails. So what's interesting here is we see that first it did succeed. So the system was normal. So we went on and killed the DB master, but it failed when we run that again. And the reason is because in that specific case, my code was not good enough to actually reconnect, if you will, to the new database master. So when I called the application, it failed because the connection at that stage was tall. So what we want to do, and if you have a CD, what you do is you map probably that to a fix and then you push that to, you could use weave or something like that to say, well, okay, I fixed the thing now. So I'm going to release a fix, apply the fix. Let's wait for it to come back. Come on. There you go. It's already there. And now we're going to run that. What I did, but I don't have that set up right properly. Oops, it's not set up yet. It's not up yet. So in that case, actually, what you saw is the steady state bail the experiment initially because the system was not normal. I went too fast and probably the system was not yet ready. Oh, it is now. There you go. But what you do is probably you look up that with git cube or whatever and say, well, okay, I've released a fix, rerun that, all those things that you would do with any sort of test basically. And hopefully that fix does work and you've proven you had a weakness and you found it, you fixed it and you try it again. And that's before and after that you would want to see from chaos engineering experiments. Now there you go. It shows that the steady state now is met. So that means our application now is able to actually sustain that kind of loss. If the master goes away and the connection is lost, we are able to actually sustain that error. That's a kind of the failure that you won't want to see. That's a basic one. And if I have time, I don't know, I'm perhaps not, but there is another one I would want to show you. I'll stop now, but I don't think I have the time. Would be if you, let's say you have your, you're using GKE or something like that and you realize one of your notes, the virtual machine is actually, I don't know, security as security issue or something. What you want to do is, pull out a new notepool, right? New set of machines with a fix, but you want to see whether or not it's going to impact your users to switch from one node to another node. Well, that's an experiment you can run with a Chaos Toolkit. You're going to bring a new notepool with new machines. During that to Kubernetes, see the load spread from one cluster to the other side of the notepool and see if your application is actually impacted. That's the kind of thing you can do with a Chaos Toolkit because we, all we do is we drive existing APIs. We don't try to create new sort of chaos, you know, tooling because already they already exist and in various fashions like that. Right, that was my demo. Cool, thank you. We have about five minutes for questions. Anyone have any questions? I actually had one. I saw when it got to the end of the run it said like, let's roll back, no rollbacks to Claret. I'm curious like what the rollback would end up looking like for maybe an experiment like this doesn't have one, but I guess what is the JSON body of that end up looking like? So yeah, it's a good question. Why in steady state we use probes only? In rollbacks, you can use actions. Basically all you do is you try to revert something. So if I had the time to show you the notepool one, I actually delete, I create a notepool. So it's just a bunch of virtual machines really. And while that runs, I killed the notepool in the rollbacks. But in the example I showed you because I'm using Kubernetes, Kubernetes take care of the rollback if you will. Yeah, they don't revert those pods.  So yeah, and Kubernetes actually rollbacks are I wouldn't say meaningless, but certainly yes, less useful. Awesome, thank you. Thanks. Any other questions? Otherwise I will ask for volunteers to present at the next meeting. I know Paul has volunteered to talk about his work on spring and maybe Miko, powerful seal sometime. Any other volunteers to present next? Yeah, Chris, I can demo the LinkedIn stuff. Obviously it's a little private, but it still shows us some of the techniques pretty cool and actually probably builds on some of that spring work as well. Okay, I can also demo the Fumba, but again, it may be not next meeting, since we already have enough presentation in the meeting after that. Yeah, I just want to collect the backlog of things and I'll just schedule you. I'll try to do at least one presentation and meeting to Max. Okay, so write me. I'll write you on the backlog. Thanks. Any other volunteers? All right, well, that's good for now. So we have a couple minutes left. So just want to be sensitive to people's time. So thanks everyone for showing up. I want to continue to do all the white paper and landscape work as async as possible. Hopefully people could give their input on that while we kind of build that out. I think other than that, that's it. Anyone else have anything to say? Otherwise we could thank our presenters and meet again in a couple of weeks. Do you have a timeline in mind for the white paper and landscape? I know, really bold question. I'm just, I'm curious. Yeah, so like I love forcing functions. So like picking a date and like hammering towards it generally works well. I think it's going to take, it's going to take still some consensus building, but I would love to get something out probably in a one to two month timeframe. We're also going to have to give my designers on the CNCF side about two weeks to kind of make things pretty and professional and line up PR and all that stuff. So whatever we choose, we'll have to at least have a two week buffer for them to do that work. Yeah, sounds great. I was just trying to get a general feel. Yeah, so, cool. All righty, let's do it. Do it. Great, thanks. See you in a couple of weeks. Thank you. Bye-bye all. Thank you, Chris. Thank you.


Y Brithyn a'r Australia anwnt y fryd tryddiadau ym Tewsted. Brithyfrannu Minister Boris Johnson said that the deal would eliminate tariffs on all British goods and boost jobs and businesses across the country. Britain said it had agreed a cap on tariff-free agricultural imports from Australia for 15 years with the aim of protecting farmers. Also cars, scotch whiskey and confectionary will be cheaper to sell in Australia because of the agreement. The main elements of the deal were agreed by Johnson and his Australia counterpart Scott Morrison at a meeting in Downing Street late on Monday with the final agreement in principle due in the coming days. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


Our next step would be testing the DKIM records to make sure that everything was published correctly. What we should be able to do is just go out to our favorite method of looking up DNS records on the Internet and look up one of the records that we just created. If everything worked correctly, what we should see is that when we do a lookup for any of those domains and we look up a text record, then we should get returned a text record that shows V equals DKIM 1 and K equals RSA and P equals and a bunch of strings. This is essentially the public key that Microsoft has already published on your behalf to the Internet and we're essentially redirecting via that CNAME record to this key that Microsoft has already published. So if we see that when we look up the domain and look up the text record, then we know that everything was created correctly.


Majorly baseball seems intent on avoiding overlap between Thursday football and the primary games for MLB during the football season. Because once again, just like last week, they've got a really funky slate distribution for today where they've got the games scattered throughout the day. So as always, we're going to work our way around that by doing a split slate podcast for today, breaking down both the early only and the main slates for MLB DFS. Today, let's dive on in and get you set for a split slate podcast. Welcome on into the solo shot. That's right here on the FanDuel Podcast Network and NumberFire.com. My name is Jim Sonnis. I am a senior writer and analyst for NumberFire.com here to break down both the early only and the main slate for today over at FanDuel.com. The main slate locks at 7.05. The early only slate locks at 2.10 p.m. Eastern. I think the early only slate is better, to be honest. So I'll try to play that one as well. As always, in order to not inconvenience those listening later on, we'll do the main slate first, then the early only slate. So if you want to skip to the early only slate analysis, check out the episode description, whether it be on NumberFire, Spotify, Apple Podcast, whatever it may be, I'll put the timestamp in there for when the early only slate breakdown begins. If you're listening to this before 2.10 p.m., want to play the early only slate, jump ahead to that spot in the podcast, then come back and check out the main slate as well. We'll break down the main slate in just one second. Week number three is Monday Night Football, the match between the Cowboys and the Eagles. FanDuel is making it even bigger by giving new customers 30 to 1 odds on either team to win. Simply download the FanDuel Sportsbook app today and bet on the most anticipated matchup of the week. See for yourself why FanDuel is America's number one sportsbook. Must be 21 plus and press in Arizona, Colorado, Iowa, Illinois, Indiana, New Jersey, Pennsylvania, Tennessee, Virginia, or West Virginia. New users only. $10 first deposit required. Must wager and designated offer market. Max bonus $150. See full terms of that sportsbook.fanDuel.com. Restrictions apply. Gambling problem. Call 1-800-GAMBLE or visit fanDuel.com slash RG. In Indiana, 1-800-9 with it. In Tennessee, call the red line at 1-800-889-9789. In West Virginia, 1-800-GAMBLE or die net. In Arizona, call 1-800-NEXT-STEP or TEXT-NEXT-STEP to 533 for two again. Five head. Let's dive now into the main slate for today. It is a four game main slate with lock set for 7.05 PM Eastern. Unfortunately, there is some rain. Four game slate make it kind of dicey similar to the early only slate for yesterday where everything's kind of get wiped out. It's just one game here though. Rain is likely for the Phillies and the Pirates. And it puts that game in pretty serious doubt. The rain chances diminish as the game goes along. Doesn't look great. I'm still going to talk about a picture in that game because I like him a lot, but just note that that game is pretty gross. Pitching preview for the main slate, Lance McCullers is the highest salary pitcher on FanDuel checking in at $10,200. Aaron Nola is 9-1 and Steven Matz is $8,000. Now with Nola, he is in that rain game. So keep this in mind. That game could get wiped out. And I've got my concerns around Nola in general, despite if we just ignore the rain, their concerns aren't hidden specifically. And it seems like the Phillies do too. I still have to rank him first given the matchup. I think he's just too good not to put him first. He's facing the Pirates. They have an 83 WRC plus against righties. They don't generate much pop. And that's a good. And Nola is pitching well from a peripheral perspective. He's been leaning on his sinker more recently, which I never love. But he has a 36% strikeout rate over his past six starts despite doing that. And that's the good. Love that. Good strikeout rate. Great matchup. Love it. The bad is I don't think they trust him to face an order fully a third time through right now. Over the past five outings, here are Nola's batters faced in each game. It's been 1920, 21, 21, 22. And a reminder that two times of the order is 18 guys. So he's gotten that most through four guys a third time in the order. Once he gets the middle part of that order for a third time, they're yanking him. And it's working to their credit. It is working. The results have been solid. And he's getting tons of strikeouts. But it does hurt his DFS outlook. He has no quality start since he almost had that no hitter gets the Padres. So he's imperfect. I think last night is a perfect illustration of the importance of length because Joe Ryan had like a 97% strikeout rate for the twins against the Cubs. But he still got outscored by Ian Anderson because Anderson went deeper in the game. Pitch count matters a lot. And I'm worried about Nola's for right now. So he's not a must play as a result of that, even on a short slate. That is very much noteworthy. But I think that given, you know, it's not 100% certain that they're going to limit him to, you know, 22 or so batters faced. It's not 100% certain that the results may be bad again. I think there's still enough here for me to rank him first. So to me, Nola is number one, despite what I would say are fairly massive and concerning red flags in his profile. Second here is Lance McCullers. I'd be very okay putting McCullers first if Nola gets rained out. Like, I think that like he's fine enough where I can be like, okay, he's actually the top guy on the slate, not the top guy out of obligation. McCullers, no late concerns. He went 110 pitches his last time out. So clearly, they feel good about him. I don't mind the matchup either. He's facing the Angels. They are really struggling down the stretch. Their WRC plus against righties is down to 98. The strike area for them is up to 25%. And it's also good matchup for McCullers specifically because they don't walk that much. McCullers has been upping his curveball usage for his past 10 starts. It's a bit odd because his slider has been pretty good. And his strikeout rate is or his walk rate, I should say, is back up in the stretch. He had been getting the walk rate a little bit down a bit, but it's up back into 10%. So 10% is kind of high. And that means we want to use these guys against teams that don't draw as many walks. And he does get that here. Strike area for McCullers is 27%. His fly ball rate very good at 25%. If we look at that 10-star stretch, we do see McCullers having you get the quality start bonus five times. He has 3.22 ERA. So I wouldn't be opposed to ranking him above NOLA if you wanted to because, again, length matters a lot in MLB DFS. I just think the strikeouts in the matchup make me put NOLA first. I think they're both fully viable options. If you tell me that NOLA's game will not play, that's when we get a little bit hairy for this main slate. I honestly don't know where I would go for the third option. So if we get bad news in the rain, check back at 4.30 p.m. today for the Q&A. We'll talk about it then. It's pretty hairy if we lose NOLA from a pitching perspective for this slate. As far as the stacking goes, I do want to jam in the Blue Jays even if it means I have to lean on their value plays in doing so. They're facing Michael Panetta. This is their second straight start versus Panetta. And the first time Panetta was able to weave his way through some trouble, he let up just one earned run. But there were two more unearned runs against him. And I think Panetta might have gotten a bit lucky in that game. The Blue Jays put 19 balls in play in that game. That's a big number, or against Panetta specifically. That's a big number. Two of those were barreled, two out of 19. Ten of them were hard hits, more than half were hard hits. That should turn into more than one earned run. Now they're seeing him for a second consecutive start. I'm not expecting that to go a whole lot better for Panetta even though this one is at home for him. So I think the Jays should sit atop our list from a stacking perspective for today. Now with colors that tend to, that's not for aggressively high salary, but it's enough where we didn't need to find some value. You can't just go with Vlad, Semyon, et cetera, et cetera. We got to find some value here. So I want to rake them and just kind of give you my thoughts on these guys based on the way things play out right now before we see what the lineup looks like. My favorite of the non-high salary guys is still Alejandro Kirk. Kirk has a 170 ISO versus Rides. That's enough. He tends to hit more in the middle part of the order, which I will definitely take. So Kirk is number one. Number two is Gritchick if he plays. That's not a guarantee by any means because it is a Rides. So he could get pushed out of there. Do you like the power there? Number three might actually be Jake Lamb. Lamb has a 205 ISO against Rides. He's probably going to hit ninth if I had to guess, but in this offense, it's actually fine given the salary Lamb has. Number four is Corey Dickerson, just not as much power as Lamb, as Gritchick, as Kirk. And then Danny Jansen, if he plays over Kirk, depends on where he hits.  I'm just not sold and it sticks. So I think Jansen depends on where he bats. But for right now, if we assume it's Kirk who catches, I'd say Kirk, Gritchick, Lamb, Dickerson, the ranking of the value plays within the Jays. For the number two stacking option, I don't feel great about it, but I do think we should stack the Rangers here. And that's scary. They're really bad against lefties. And I've used multiple left-handed pitchers against them this week alone. It's just hard to pass up their matchup. They're facing Zach Lauther, who's getting his shot in the rotation for the Orioles. And it's gotten up to a rough start so far. His ERA is 8.74 since he joined the rotation for good. His skill interactive ERA equally scary at 6.08. And he's just had rough numbers across the poor from a peripheral's perspective. It is just a three-star sample, though, in Lauther's defense. So it's important to dig in a bit more to see if that's legit. When we do dig in more, though, we'll see that he had a 6.53 ERA in AAA. He struggled in the bullpen of the majors as well.  That's kind of the one positive here for Lauther and the one thing he could potentially lean on. We just haven't seen that in the majors so far. I think everything here says we should stack against him, even if it means we're doing so, with a really, really bad team. I think the good thing with the Rangers is that there are some individuals I don't mind. I know that that is the lowest bar you could possibly set, but that's not true for every team. So there are some individuals here I can get behind. Two of those are Adelaide Garcia and DJ Peters. Those two guys have plenty of pop. Peters has his flaws, for sure, from a strike area perspective, but he can hit the ball pretty hard. Andy Abanyez has started to hit the ball much better recently. He's been hitting third or so against lefties as well. So I don't mind Abanyez. I'm okay with Charlie Culberson and Nick Solak. So this can be very scary. It is scary. I'm frightened just talking about it, but I do think that the Rangers are a good stack for today, despite the fact they are wretched, wretched, wretched versus lefties. So the Rangers, number two behind the Blue Jays, and it does help that their low salaries make it a bit easier to get to the Blue Jays for today as well. That wraps up the main slate. Let's move now to the early-only slates. If you listen to this after 2.10 p.m., see you at the Q&A at 4.30, 4 o'clock for the Thursday Night Football Preview and tomorrow for the Friday Slate Breakdown. The early-only slate is a five-game slate locking at 2.10 p.m. Eastern. It's a pretty good one, though. There is no weather to discuss here, so there's no Nola situation. We are good to play this thing straight up, and there are three really good pitchers on this slate. We've got Max Scherzer checking in at $11,300. Logan Webb is $9,800. Adam Wainwright is $9,500. Chris Bassett checks in, $93.00.  Charlie Morton, Hugh Darmish, and Adrian Hauser are the others that $8,000 are higher. Now, not only do we have good pitching options for today, but I think one of the better ones is one of the lower salary guys in Charlie Morton. Charlie Morton is $8,600. I think he is a solid play for today, and I'm very okay being high on him. He's not as highly regarded as Scherzer or Webb, but I think he's in a great spot tonight, and a big part of that is the matchup. He's facing the Diamondbacks. They have a 79 WRC plus against Reides. Their ISO is 134, with a 25% strike out rate. It does help Morton that the roof is closed for today. It's been open the past three games, but that closed once again for today because it is a day game, but to hang with Scherzer and Webb, you need to be good. You don't need just a good matchup. You got to be good yourself as well. Morton is that. We are up to 13 starts on him since the velocity on his curveball increased. He has a 3.53 skill interactive ERA in that time. His strikeout rate is 28%, and the bat of ball bait is looking pretty good recently too, because his hard hit rate is 31% in this span. He's had some tough matchups in there. He had nine strikeouts against the Yankees, eight against the Reys, and he's had good results too, because he's allowed more than three earned runs just once in this 13 start sample. ERA from Morton at 3.00, so he can get strikeouts. He's in a plus matchup. Park not as bad as it was the past couple of nights, given the roof being shut. It's a really good combination. I'm okay being high on Morton here. Even with really good competition, I'll take that discount and put Charlie Morton number one for this early only slate. Between Webb and Scherzer, I am okay going with Webb over Scherzer by the tiniest, tiniest, tiniest hair. Scherzer is at course. It scares me just enough when his salary is 11.3. If he were the same salary as Webb, I'd probably go Scherzer, because I prefer the upside that Scherzer brings from a strikeout perspective, but I think that when you give me the discount, I'm okay taking the better park factor going with Webb. Webb is facing the Padres. They're not the biggest strikeout team, but I think they're a team that he could handle. We're up to 10 starts on Webb in his current state when he's been leaning on his sinker a bit more, and his numbers in that sample are absolutely absurd. He has a 2.71 skill interactive ERA with a 28% strikeout rate and a 4% walk rate. He does all of that while also having a 19% strikeout rate. That should not be legal. He has not faced the Padres in this time either, so they're not familiar with him. That's a good thing. Webb has 10 strikeouts once, nine strikeouts twice, eight strikeouts, and two others, and his ERA is 2.20. It's not just the peripherals that love him. He's a good pitcher. The results have been there too. The Padres are not a pushover. They have a 101 WRC plus against Reides, and their strikeout rate at 21% is very good. I just think that Webb is too good of an overall pitcher for me to pass him up at $9,800. I will be there tonight for sure, and I think that he is a great option. To me, it's more than one. Webb 2, Sherser 3, very comfortable having Sherser in my player pool. I just want a tiny bit less of him than I have in Webb, but if you're looking for just raw ceiling, I think Sherser has the slight edge of their overlogan Webb. As far as the stacks for the early only slate, you say Kikuchi. The velocity has always been a big topic of discussion with Kikuchi. I get excited every spring because their reports are that his Velo is up, and often it is, and there are really good spurts that it'll have at times as a result of that. The recent stretch for Kikuchi has not been one of those good stretches. His velocity has been down over his past seven starts, and it's not going well. His skill interactive ERA is 5.14 with an 18% strikeout rate. His hard hit rate is up at 55%. Again, League Irish, there's about 39%. So 55% not great. Shockingly, the results have not been great either. His ERA is 6.91. He's gotten clouded by Houston, which makes sense because they're a very good team, but he also let up four runs through the Royals in one start, three runs through the Royals in another. Even without Ramon Lloriano, the A's are a pretty good team against lefties. They've got a 105 WRC plus with a 174 ISO, and I think they can do well here. So I don't want to use batters facing Kikuchi because I like rooting for him. I've got him in a Dynasty League, where I'm trying to win a championship right now, so I don't really want to root against him, but I think it is the right thing to do here, and I'm okay stacking the A's against him right now. I'm guessing most of you listening know this, but it is worth pointing out just how good Matt Olson is against lefties. He actually leads the A's in both WRC plus and ISO versus lefties. His strikeout rate is 18%. That's absurd. So when you pull up Kikuchi's numbers versus lefties, you're going to see that he's done very well against them. I think their Woba is maybe 205. I might be quoting that stat wrong, but I think it's very, very low, but doesn't get a huge strikeout boost against them, does still let a fly ball to them. So the peripherals say, you know, it's not the worst idea to use lefties against him. I'm okay using Olson here. I know most of you know that Olson's good against lefties, but I do want to reiterate, don't just auto stack the righties on the A's against the lefty. Matt Olson is still a priority no matter who they are facing. The second stack for me is in Arizona. Again, it is a bummer that the roof will be closer today because it does downgrade the offense, but I still think we should stack the braves here. They're facing Madison Bungarner. He is really struggling in four of the five key categories that I log on my sheet. And it sounds like he's having trouble gripping the baseball right now. As a result, he has thrown fewer curveballs as past six starts. Makes sense because like if you're having a tough time getting a grip, you're not going to throw as many curves, you're not as confident in that pitch. And it's likely some really bad advanced numbers. He has a 5.24 skill interactive ERA in that time. His strikeout rate is 17%. He's letting up a lot of fly balls. The one area where Bungarner is still doing well is suppressing hard contact. The hard hit rate allowed is 33%. That's helped keep his ERA in check at 5.21, but he's gotten hit hard by some bad teams. The pirates scored four runs against him. The Mariners scored five runs twice. So yes, he did do well versus the Astros last week, but just three strikeouts there. And that's not enough to scare me off of stacking against him going forward. I think we should stack the Braves and all of their powerful righties here and feel pretty secure in doing so. When we talked about the Braves earlier against righties, I've been heavily on Adam Duvall above Jorge Soler. They're facing the lefty tonight. And I think that does flip where I would go Soler over Duvall versus a lefty. Soler's iso against lefties. It goes up to 297. That's much lower versus righties. Duvall is good against both. But I think that Soler, with the boost that he gets against lefties, deserves to be a little bit higher on our list. So I still love Duvall. I adore him. He has massive upsides. He's got a 58% fly ball right against lefties.  But against lefties, I'm okay. Ranking Soler a tiny bit higher between the two. Ideally, we just get both. That's the ideal solution here. But if you had to pick one, I'd put Soler a hair above Duvall. Just against lefties, against righties, very much Duvall against lefties, a hair favoring Soler. That is all that we have here for today on the solo shot. As a reminder, we do have our MLB DFS Q&A breaking down the main slate later on today. That's at 430. They'll be preceded by the Thursday at football preview. Brandon Gadoulos in breaking down the simulations for Panthers versus Texans. That is at 4 to 430. I'll be on at 430 to 5, breaking down the main slate. Hopefully, we get good news on the weather out in Philadelphia. If you've got more questions for me before 4pm, I am on Twitter at Jim Sonnis, J-I-M-S-A-N-N-E-S. You can also follow the FanDuel Podcast Network at FanDuel Podcast. Make sure you go subscribe to the Number Fire Daily Fantasy podcast feed. Tune in at 10 a.m. for the NFL DFS Heat Check podcast, or check it out on the Number Fire Daily Fantasy podcast feed on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. Good luck to all of you with both the early only and the main slates, and we'll talk to you once again tomorrow to wrap up the penultimate week of the regular season of MLB DFS. This has been the solo shot right here on the FanDuel Podcast Network.


Scott Walker concedes governor's race. Sheboygan County voter turnout tops 80 percent. City of Sheboygan passes 2019 budget. These stories and more on this edition of Community News Review. This is Community News Review service WSES TV news content divided by WHBL. Good day I'm Maddie Fister and this is Community News Review for Wednesday November 7th, 2018. Wisconsin's Republican Governor Scott Walker narrowly lost his bid for a third term Tuesday to Democratic State Superintendent of Public Instruction Tony Evers. It was the closest governor's race in the state in decades so close that Walker's Lieutenant Governor Rebecca Clefish said before the race was called that they would likely call for a recount. Under provisions of a law Walker sign last year candidates who lose by one percent or less can demand a recount. Evers margin on Tuesday was 1.2 percent. Governor Scott Walker officially conceded the race and released a statement Wednesday afternoon on his website congratulating Evers and thanking his supporters. Republican Representative Glenn Grothman has is being awarded a third term in Congress after he was declared the winner of the Sixth Congressional District. Since the 1960s that district has been in the hands of the GOP. Grothman's opponent Dan Cole released a statement congratulating him on the victory on Tuesday night in Grothman's garnered 55 percent of the vote. Cole received 45 percent. Incubant Republican State Senator Devin Lemahue came out on top in the race against Kyle Welton Tuesday night picking up 44,677 votes. Kyle Welton had 31,683 votes. That amounted to a 59 to 41 percent difference. Republican Terry Katzman of Usberg will continue representing the 26 assembly district defeating his challenger Rebecca Clark 58 to 42 percent. Republican Tyler Vorpigal will continue representing the 27th assembly district picking up 60 percent of the votes and Corey Riesler has been elected sheriff of Sheboygan County and he was appointed to the post by Governor Walker late last year when Todd Preby announced his retirement. Riesler picked up 33,642 votes. His opponent Philip Schaefer received 18,360 votes. 83 percent of registered voters in Sheboygan County turned out to cast their ballots yesterday. The unofficial election results from the county clerk's office show that the county leaned Republican last night. Scott Walker, Brad Chamille, Jay Schroeder, Leah Vookmore, Glenn Groffman, Devin Lemahue, Terry Katzman, Tyler Vorpigal all taking more votes than their Democratic opponents. Wisconsin may have a new attorney general to go along with a new governor after Josh Call declared victory Wednesday morning. Unofficial vote totals put Call ahead of the incumbent Brad Chamille by around 22,000 votes. In his victory speech Call said that he'll be pulling Wisconsin from the fight against the Affordable Care Act and to work as a watchdog for his constituents. Chamille has not conceded in the race yet saying he's waiting for more official vote totals before making that step. In addition to referendum questions on medical and recreational marijuana used and school funding, voters in several Wisconsin counties had their say on non-binding issues surrounding the state's dark store loophole as well. Both Portage County and the City of Merrill passed the straw poll question with overwhelming support. The same goes for voters in Brown, Green Lake, Manitowoc, Winnebago and Aragami counties as well. Lawmakers have been trying to close the loophole for several years but have run into roadblocks set up by big box stores who argue that their property should be taxed as if it is a dark or vacant. Municipalities say that the stores should be taxed at a higher rate because they require more services than a store that is closed. They also argue that the lower tax rate for the stores means residents end up paying a higher rate for their taxes to make up the difference. All told some 17 counties and six cities and villages support their version of the non-binding referendum. The information will now be passed on to state lawmakers in hopes that the tax loophole will be closed in the coming session. The City of Sheboygan passes its 2019 budget and the vote at Monday night's council meeting was unanimous to pass the 128 million dollar spending plan for the city. Last year's budget came in at a price of nearly 122 million dollars so the new budget will be up by 6.4 million dollars. As for the tax levy it is going to be increasing by 1.9 percent so the owner of a home with an assets value of $150,000 would pay $1,489 and that is up 19 cents from the last budget. And that does it for this edition of Community News Review. Join me again next week for another recap of our local news. News content for this program provided by WHBL in cooperation with WSCSTB.


Hello, my name is Negato Alamayo. I'm a research and development officer for the IPMS project in Ada. Welcome to the agricultural value chain exhibition in the Brazilian. The purpose of this exhibition is to transfer knowledge from input suppliers, technology generators, market agents and service providers. The purpose is just to learn from each other, the input supplier learners from producers, the producers from market agents. So it's vice versa lesson learning. The participants of this exhibition are NGOs, government agents who are involved in agricultural service provision, input suppliers, private and unions. And market agents like processors, Ada, dairy processing, Genesis farm, Holland dairy and poultry farmers. Also the farmers who are participating in this exhibition and the main objective as I said is to transfer technology, knowledge, marketing information and other activities. Thank you very much.


How narcissists react when you leave, when you leave the narcissist It's going to cause them anxiety sorrow and pain It's going to make them miserable It's going to make them suffer because they've lost their source of supply they've lost their source of stability and security and They are struggling without you because you were their emotional punching bag They took all their problems out on you They blamed you for everything They used you for money and for a place to stay And it's not easy for them to find someone who is willing to do that for them They may try to find someone to replace you But they will just end up with manipulators and con artists People who are just looking out for themselves People who will just use them for money or sex They're not going to find anything of substance They're not going to find someone who believes in their lies Someone who validates the illusions of their false self Someone who is predictable, someone who makes them feel comfortable It's not easy for them to just move on and replace you So when you leave they will experience the unpleasant effects Because they have lost their supply They have lost something that they were addicted to They're no longer getting their needs met Because it's not easy for them to find someone who can do everything that you did for them But they are arrogant and audacious They have an exaggerated sense of their own abilities and importance They think they're greater than they actually are And they are willing to take both risks Because they engage in magical thinking So they will blame you for everything They will tell themselves that it was all your fault And then they will actually believe that they can do better than you But it's not real It's all a fantasy that they have created inside their head It has no basis in reality So they will go forward with these false ideas and impressions in their head They will act like they're so wonderful And as though they've found the perfect person And they're so happy without you But it's all a facade It's all one big illusion They're never going to let you see what is really going on Because they can't be vulnerable They see it as a sign of weakness Which is why they're never going to let you know how they really feel They're always going to give you the illusion To make you think how they want you to think So that they can feel better about themselves So that they can get supply They want you to see them as their superior being As someone who is greater than you As someone who is very important And they will show an overly high opinion of themselves as though they're doing better without you But they're not really doing better without you They just have a weak fragile ego They have an inconsistent self-esteem An unstable self-image built on a weak foundation So they don't want to show you things that aren't going well for them They don't want you to know that Which is why they will go off and find anyone they can To show you that they are living their best life without you To show you that you are causing all of their problems You are the one who is to blame You are the cause of their suffering But it's all a fantasy It's all an illusion It's something that they've created inside their heads Because they can't accept blame They don't want to deal with the consequences of their actions They have too high an opinion of their abilities and worth Which is why they will never show you what they're really going through They will only show you what they want you to see But the truth is that they are going through it They are struggling without you They just don't want you to know about it But they're addicted to people People are their drug of choice They use people to make them feel better about themselves It's an addiction So you should already know when they're going through something Because they will move on very quickly They will be dating new people They will be going out with their friends every night Because they're just trying to find a way to feel better But it never lasts long Because people begin to see what they're trying to do They begin to see that they're just a pawn in the narcissist's chess game They begin to see through the illusion When you leave the narcissist It will cause a narcissistic injury They will get very angry And they will try to destroy you They will try to make everyone think that you are a bad person Even after everything you did for them And everything they did to you They're very good at playing the victim and making up a story That's how they got with us in the first place Thank you for watching I hope this video resonates with you Please like, comment, share and subscribe If you would like to donate My PayPal link is in the video description Coaching inquiries You can email me at coaching.naxify.uk Thank you for watching and I'll talk to you soon