This is covering the spread part of the Fandall podcast network Big thank you to Tom Vecchio for filling in for me the past couple of days Well, I was out for my wife's PhD graduation. Tom always does a fantastic job So I know you all were in good hands for those couple of days And I am delighted to be back here for today because we've got the matchup set for the conference finals in the NBA And also golf's second major the PGA championship coming up on Thursday here to break down both those is Brandon Gondola we're gonna pick his brain on both game ones and also preview this year's PGA championship Welcome on into covering the spread that's right here on the Fandall podcast network and number fire calm My name is Jim Saunas. I am a senior writer and analyst for a number fire Joined here as mentioned by Brandon Gondola check him out on Twitter at Gondola 13 find his work over at numberfire.com And Brandon I knew of references before we made jokes before about how you come on the show Wouldn't be on the next week and then next week is the week you did the winner But now with you being in the show every week We've ruined that streak and suddenly you're hitting winners with Jason Day 17 to 1 being the winner this past week So Do we have to have you on the show every day? Is that the next step in this? What's what's going on here because it seems like the mojo is flowing? Jim I love being on I love talking about this stuff, but please don't ask me to do this every day I'm asking you that right now. Why do you not want the people to win money? Why are you against the people? Why are you why are you in big corporate's pocket Brandon? I mean look when I when I get asked to do this show I spend a lot of time digging in making notes because I want to give Good recommendations and even whenever things inevitably don't work out, you know, some of the time I at least want to have a good rationale. So it's it's a time-consuming process and I think for my own sake I've learned the power of saying no Yet I say yes to this, you know every week. I've been the one encouraging you to say no to things However, I am mad that you have decided to deprive the people of your good thoughts. So we're fighting now We're officially feuding so this this might be a rocky podcast, but we're still gonna yeah first time that this has ever happened, right? We're still gonna talk to Brandon I guess while he's here about some NBA will talk to PGA championship gets you ready for all that here in Just one second a first day reminder to make sure you're subscribed to covering the spread Wherever you get your podcast because we got shows coming up every day this week and also Over on the Fandall YouTube page. So subscribe there if you like what you hear leave us a thumbs up over on YouTube Or leave us a five star rating over on Apple podcasts Are you looking at a stake in the PGA championship all weekend not just with your bets? But also with daily fantasy. Well Fandall has you covered with the PGA mega Eagle contest Which is now live test your knowledge of the PGA tour by putting together a six-person lineup While staying under the salary cap and using Fandall's live scoring feature follow along as you compete for a share of $350,000 with first place taking home a hundred K all for just nine dollars in the entry fee Whether it's household names like John Rom, Justin Thomas or lesser-known golfers You think could make a name for themselves this weekend the tee-off time is on Thursday So there are plenty of options for you to fill out your line-ups as you compete for first place Thursday will be here before you know it. So submit your line-ups on Fandall today eligibility restrictions apply go to faddle.com or download the faddle app for more details We're gonna get things off for today by talking about the NBA We're gonna go through both game ones in the eastern and western conference because no NBA talk on the show for tomorrow Talking about the preakness in instead then let's begin things off with the first conference championship Game one that is the Lakers at the Nuggets in the west that is coming up tonight We got the spread here as a Nuggets as six-point favorites total is 222 and a half and Brandon your numbers were high in the Lakers for most of their series with the Warriors there and obviously They got the win in that series, but now facing the Nuggets and there's six-point dogs here Though the Lakers love paid off there. What do you see here relative to the market for game one against the Nuggets? Yeah, kind of viewing the Lakers similarly where I like them for anyone unfamiliar with the process even though as Jim mentioned, I'm on the show every week You know, I I look only at relevant splits for teams based on who is healthy and who's in the lineup This team this Lakers team is just a lot different When they have unsurprisingly the bronze James Anthony Davis and D'Angelo Russell all playing together in that split they're 16 and 5 overall which is Not a whole lot of games that obviously that sample is growing, but it's You know It's a better sample to be looking at than a full-season thing or you know any sort of arbitrary cutoff otherwise Other 14 and 7 against the spread in that split as well Now the Nuggets to their credit are Unsurprisingly great with Nikola Jokic and Jamal Murray Murray is questionable with an illness I Have not been able to confirm Like how serious that is I'm assuming that he is going to play now. Frankly. Yes, they're better with with Jamal Murray It's about two points per 100 possessions of a difference so long as the constant is that Jokic is is playing Not even that he's just on the court, but just that he's active He is that he's the true difference maker So yes, that is that is a fairly substantial number If this were the regular season I would take a wait-and-see approach and see if I you know still wanted to go that way But whenever someone's questionable, I still run the numbers and then if I see any value on a particular side That is only going to benefit from the news that like that player is out Then I like it and I'm good with it and that's what I'm seeing here on the Lakers I can see here you have the the betting stats pulled up and it looks like a lot of interesting trends here on the difference between the percentage of money on the spread and the percentage of the bets on the spread The money favoring the nuggets here, but you know for my model assuming Murray plays the spread should be Four and a half in Denver favor, which leaves a point and a half for the Lakers So I'm I'm interested in the Lakers spread just like I was game one for their series against the Warriors gym I said I see the case for the money line Back against the Warriors and you were much more willing to take that on I do see slight money line value on them even with Jamal Murray active the the reality is just that Denver is fantastic, you know, we know they're playing at home But the Lakers have just been a really good team. I always again just sort of prefer going with the spread here But the money line certainly in play as well The money line right now if annual sports book plus 198 on the Lakers The spread is plus six and minus 108 there So it sounds like for you based on the way You're seeing things the better value here is in the spread at plus six versus the money line of plus one at one ninety eight Is that correct? Yeah? That is that is correct and just for my personal preference if I can get an underdog With just taking the points at you know relatively You know odds around, you know minus 110 That's just 10 tends to be what I prefer because I'm a very pessimistic person by nature And so for an underdog to win I feel like it's less likely than what my own data shows That's just that's my own personality and my own internal biases that I try to work through out of curiosity Are you willing to disclose the win odds you have for the Lakers here? Um, if you're not that's okay. I'm just curious I'm help trying to decide for myself if I want to take the money line of the spread What would you need it to be? So the implied odds at two to one are 33 percent if it were 36 percent or higher I would take the money line. It's 36.7 which implies basically plus 172 plus 173 in that range Okay, we're in the money line. We're doing it again running it back What could possibly go wrong Brandon's official recommendation is the Lakers plus six and minus 108 But if you are not a coward plus 198 on the money line for the Lakers here against Nuggets if you're not gonna come on every day I'm taking full freeway to just roast you even when you're providing good data You know usually roaster one for bad things, but hey, you know our podcast our rules, right? Like I said, I come on here. I try to say what I see in the data And from there, you know, I can't tell anyone to do anything or not do anything. So correct Always gamble within your means always gamble responsibly and you know use data to decide where you want to go with me Personally, I'll go money line of plus 198 Brandon likes to spread at plus six game one in the eastern conference Is the heat and the Celtics that spread right now is the Celtics minus a total here is two ten point five and Brandon Jimmy Butler keeps on doing the dang thing keeps on pushing the heat through the playoffs He's gotten them now to the eastern conference finals, but it's a matchup with the Celtics Celtics are tough They've had some tough tests already. They knocked off the box and stuff like that the Knicks as well Can the heat keep it rolling? What's your read on game one here in the eastern conference? So this one's kind of interesting because I I ran this game With I basically have like Bookmarked the splits for teams that I use and then I just tweak it from there It saves me time and I ran it without thinking because I was you know, oh the heat Nothing new here in terms of injury and then it's like, oh, but I still have it where Tyler hero is active and They've got some weird splits with Jimmy Butler BAM out of bio and Tyler hero where They have a winning record, but the net rating is like a slight negative And so I re ran it with with Butler and BAM active But hero completely inactive and there they've been better in terms of net rating So I initially had this spread it I think like 11.3 in Boston's favor and then once I re ran it it is Now like 7.8 so It's really interesting and that's why sometimes You can't just always assume Players out team is worse. I'm not saying anything against Tyler hero. It just sort of is you know, maybe something structurally With the team who's who's playing more the way that they're playing anything like that Plus this team has just been really locked in and sort of overly efficient in this a lot of this spread We're here has been out for the playoffs. So, you know, it is it is kind of a Strange one and that sample now of those games with hero completely out is over 1500 possession So I think that's a pretty stable number there. So the spread I thought was going to be in Boston's favor Now I think it's too close for me to want to get to as for Boston themselves, you know with Jason Tatum Jaylen Brown active. They're really good So the thing that my model is jumping jumping on is actually the over I've I saw this total first at 211. I don't know if that was exactly where it opened, but it's down half a point And so I'm actually viewing it The other way I know it always feels hard to love the overs with the heat But they've been hitting overs in the playoff a lot more than people realize they have some good offense Boston can definitely Light it up and we know we've seen You know, frankly, we've seen Miami play some teams that are not Fantastic offenses in the playoffs, you know with with the honest out like that hole that hole for you know A good portion of the early part of that series Milwaukee was like a sub par offense New York Not necessary like I mean they've they've had good offenses was but they were they just looked completely lost and we're missing Seen like every shot that they had in that in that series. So for me, I think the over makes sense I have this one going over pretty comfortably my total here is 217 so It's important remember that the market is accounting for heat having typically low totals your numbers are accounting for that as well So I know that like the sentiment is, you know, they tend to have lower scoring games But the market is reflecting that with the total being two ten point five And also I think based on what you are running that split with no hero with Jimmy and with Bam being active a Lot of that probably comes from this postseason run Which implies to me that the spread with the Celtics here by 7.8 is accounting for the fact that Butler is an alien and It seems to me that should lower the fear a bit of the situation again It implies I know bet but it also to me lowers the fear of okay I'm not missing out on the heat plus eight here because that's accounted for in the numbers. Yeah, I have them Going over in sixty six point seven percent of the games in that split without hero. So like again, it goes back to Just because player players out doesn't mean teams worse and just because you know Good offensive players out doesn't mean you bet the under because the under is reflected in that So, yeah, I think that this offense and maybe their defense too has been a little bit Surprisingly over friendly, even though it doesn't feel that way right. Absolutely. Okay So the two bets Brandon likes to the two game ones are the Lakers plus six and then the heat Celtics over two ten and a Half the number on that is minus 110 right now Let's shift gears here and talk about the PGA championship coming up this week It is the golf's second major of the year out at Oak Hill Country Club in Rochester, New York It's not hosted the event since 2013. So Brandon, what should we know about this course before filling out some bets for this weekend? Yeah, it's always tough whenever we don't have a lot of Data to go off of with the course. I mean this has hosted a few times 2013 as you mentioned 2003 as well But, you know, frankly No shot link data and that's tough PGA's I think also just generally play harder than people realize they play a little bit more like the US Open The winning score was 10 under in 2013 and 400 in 2003 at this particular course and it's it's just kind of tough and what makes it tough is that it's pretty pretty long for a par 70 and For me one thing that really really stands out Is the average green size at 4500 square feet PGA tour average is around 6,000 square feet So these are definitely smaller greens and with the added length for the par 70 smaller greens Then just almost in literally any every case always it's better to be long off the tee Than it is to be short off the tee and you need to have a good irons to hit These smaller greens and hold them now with with that being said I've been you know digging into and I try not to do this too much because I find that it tends to be more Misleading than anything and I know this is probably a big part of people's process But like listening to what the pros are saying about the course once they get there and you know every time there's a US Open It's like oh drop the ball an inch off the fairway and I need a shovel to get it out Basically, and that's tough. It's not how it plays always so, you know, it's just kind of one thing that I find to be a little bit more harmful than anything but One of the things that I really heard the pros saying is that the the rough itself is really different it's like really thick blades of grass and so I think it was max homa justin thomas basically saying it's better to That would make sense because listen to the nailing up podcast and so This guys are basically part of the nailing up crew at this point, but um you know, they're saying it's It's going to be beneficial to be hitting fairways and While that's always the case I feel like whenever we hear oh you got to hit these fairways and it's good to be long But if you're long and in the rough you're you know in a in a bad spot And then it doesn't always end up that way and it tends tends to be just whoever's hitting it farther So I'm just giving that information out there. I'm not doing a ton with it to say oh, I need Right, I need to downplay distance and just really look at driving accuracy Point being is there's not a whole lot to go off of that. We can say with certainty What we can say is that it's a major majors, especially the pga's are always all around tests Small greens so better iron play is going to mean you can gain greens on the field But also with small greens you're inevitably going to miss them If there is tricky rough and tricky lies around the green you got to be able to have those good You know get the ability to get up and down have good wedges so I just basically said we need distance or accuracy off the tee We need good irons. We need good wedges and of course you need the putter So basically what it comes down to is you need to have everything this week And that's pretty much how I play every major And we were talking about guys who have everything that right now seems to mostly pertain To john raman scottie chef or they had the co-favorites of fan dual sports book They are plus 750 right now before I dipped down to rory macaroy 13 to 1 and those are short numbers But as we've seen recently brandon even in these elevated fields, we've seen value in some of the favorites at times So a short number does not mean a golfer is not a value when you look at those favorites right now at their current numbers Any value for them for you right now? Yeah, short numbers don't always mean that they're bad values Um, just like I said the things about like the nba not always being what you what you first think and for me, honestly I would not put scottie cheffler in the complete Does everything well right now because the putter is a bit iffy Uh, so for me, it's john raman is the only one who hits all those boxes and I do have John raman is a slight value Um, I have a 12.9 percent, which means about plus 675 as jimman say value is value um, so i'm not going to hate anyone who wants uh To go at john raman plus 750 he's got two majors to his name now. He's probably I don't really know how you'd argue. He's not the most complete golfer right now, especially with cheffler and his putting concerns with rory Just not quite being rory speaking of which rory's not rating out very well for me I just kind of cooled off a bit hasn't played a lot lately I would not be super surprised if rory came out and played well, but I don't know if this is necessarily the place. I would think to pick rory Where he's got a grind out hole after hole But I know he's got that in him. I just don't I you know, we don't see it often over 72 holes So among the favorites, uh rom is a value according to the model And I know that if you want to bet him you got to figure out how that impacts the rest of your card I'm aware of that Are you taking rom yourself or no? so I'm very interested in it. Yeah, but there's a trio And really a duo right behind like in the second tier and so I got to figure out what my process is uh So basically weighing what the better value is whether that's taking rom a plus 750 or Relying on some guys with some longer odds and potentially having more outright bets out there Yes. Yes. That's that's what it comes down to Okay, so I will decide I will decide here Yeah, but I'll talk a lot about other outrides. I'm interested in and that we can go from there Okay, so rom is a value plus 750. I trust the model even though you don't uh, so I think that rom makes a lot of sense plus 750 So the guys you're weighing right now beyond john rama plus 750 which other outrides show value to you at fan to what the moment It's shocker zander schafer I have him at 15 to 1 He is 17 to 1 on fanto sportsbook. He was 24 to 1 Which is a pretty drastic swing Pretty much overnight from 24 to 17 He just does everything well, which is again what i'm looking for The price is good. He's got four straight top 15s in his past four majors You know the only thing you can really knock with sander is that he quote unquote doesn't win but I think people who would say that are Maybe like overstating How much you can control winning a golf tournament? Like it's not just it's not just up to you. Um, I also like his buddy jim. Uh, patrick cantlay at I have him at 18 to 1. He is 20 to 1 on fanto sportsbook He's another golfer who does everything well. He is starting to play a lot better in majors, he's got three straight top 15s at majors 14th at the u.s. Open last year T8 at the open and then t14 at the masters this year Why not putting particularly well? So there's two names in the mid-range there And then one name who uh, we probably haven't talked about a lot lately But he's got some majors to his name as well If we think that we need golfers who hit fairways and have really really good iron play I see him on your screen there. I bet you can kind of figure out who it is No, scroll past them already. Ah, dang it Accurate great irons majors to his name. Yeah, call him more cal Uh 34 to 1 He's not golfing particularly well in terms of the putting But if you pull up whatever your preference of choices in terms of You know event logs, you'll see that he is striping the irons Uh, we know that he's accurate So I think that I think what it's coming down to for me is pretty much like Ron plus more a kawa as much as my two main Main outrides or zander and cantlay And the more I talk about it the more I feel like john rom's going to win So I will say that I will I'm betting john rom This week Even if it means i'm overlooking that second tier And once I get down into the 34 to 1 range, I can jump back in Yeah, I think for me I If i'm structuring this the way I think about it from a NASCAR perspective Which I know is not totally analogous to golf But it's kind of somewhere in the way the odds are structured if I have a A a driver a plus 750 outright I'd be okay adding one guy in the mid-range whether it be zander or cantlay I'm gonna guess you're gonna go zander personally But then I'd also be okay with more kawa 34 to 1 Three outrides in like three separate tiers. I think is okay. It's the fourth one might be where I would Well, I would be a little bit more nervous But it sounds like you're on the same page here where you're okay Taking one from each tier and filling things out that way Yeah, I mean look There's a probably a math like I mean, there's a mathematical way to approach it. There's also you might think like So yeah, we know like you need to have the right return to make it worthwhile If you just bet everyone you will have a bad time, right? We like we know that But Let's say I had calling more a kawa at something already just like 15 to 1.  Yeah, like so There's basically not like a one-size-fits-all answer when it comes to this stuff. So It's just something you you kind of have to learn on your own and figure out what works for you While being smart So the values based on the model are john rom plus out of 50 zander shawflate 17 to 1 patrick cantley 20 to 1 Call him or a kawa 34 to 1 you can kind of decide Which of those guys you like most if you want to go all four I think that's at least justifiable not my personal preference, but uh, you know, do whatever makes you happy I wouldn't do that personally, but um, I think it sounds like you want to settle on rom zander more kawa, correct? Yep Okay, let's focus now on the non-outrights and we've got 16 000 markets already posted for this Looking at the non-outrights, which ones to you are the best values Uh, I got a top 10, uh, tony finnell which Top 10 tony. Yeah He's plus 210 to top 10 I scored off a bit in majors, but not substantially. So the putter being Improved and fixed means that he has effectively no weaknesses in his game So my model sees value in him in the top 10 market specifically um, he's an even value in the outright market, but You know with for my model with schaeffler and rory Pretty heavily over value to the top that makes that second tier really appealing And I don't want to ignore that just because I have interest in genre. I think that's the wrong way to go about it I'm usually not in the head-to-head game Oh, I don't want to be jumping you all around but sungjae in minus 118 over tiro hatton I think this course suits both of them pretty well hatton tends to play well at tougher setups But for sungjae, he should be in playoff the t And then he has good irons from there and just a good combined short game So I think this is a good spot for sungjae in to be in somewhat, uh, contention Uh, and then jumping in two groups. I got three groups. I like Love groups, uh, especially in majors. It just makes it a lot more fun Uh, especially, um early on in the tournament before you can get too excited about your Your outrights and and again just because someone's top top five after day one does not mean he won the tournament Um, so just just be you know be mindful of that, but Sungjae in plus 215 in group d over matt fits patrick tiro hatton and cam smith Again laid out the case for why I think sungjae in can play well here. Um That's nice, uh Jason day group c Over cameron young victor hovelin dustin johnson It's basically just a medley of ball strikers there, but Days in great form as we've talked about it's a good number Uh, he's also, uh a good play for top ozzie. I didn't jot down what his, uh odds were there, but um I saw a value in that and then last one going back to a play. I like calling more a cow a group e over Uh, jordan spieth who is not he's very far from a hundred percent. It sounds like max homa Who's playing well in major like playing better in majors? Uh and samber and so i'm never Quite as sold on uh as I used to be with him. So Uh, I think those three groups specifically with day sungjae and more a cow up I'd feel really good with tracking that throughout the tournament With the more a cow the group that is plus 220 over spieth homa and burns Do you like that more than the outright for more a cow if you had to pick one? Which one do you lean towards if you had to guess? I mean, I don't want to pass up a 34 to 1 number on someone who can play at a You know world-class level like more a cow. Uh, so and I think the other picture going with the outright is that if your model views Schaeffler macaroy guys like that is being a bit overvalued that the actual like value in that number at 34 to 1 is likely better than the actual value at plus 220 in the group Yeah, I mean look my model It just sees certain golfers is like overvalued And that has a trickle down effect on the rest of the odds. I think a lot of the live guys are Shorter than they should be because of the what they did at the masters and that's all impacted so like You know sometimes I recommend a couple taught like multiple top 10 bets And it's not because I think all of these guys will finish in the top 10 It's just that there's individual value on them, right because other golfers are Substantially overvalued right and I think I've kind of seen that with the live guys too It makes sense given what happened at the masters where they were super competitive and stuff like that But some of them if we look at their form on the live tour Might be a bit overvalued based on what they're doing right now So uh, the group bets is brand to mention in addition to tony finow top 10 at plus 210 sung j.m minus 118 over teal hatten as well sung j He had a week between the pj championship and the wells fargo where he You know eighth season good form He went back to career there and then No rest for sung j.m. I don't think his body would allow him to take a week off But apparently he is just uh going out there win attorneys You know snatch and trophies because that's what sung j.m does That's a wrap it up for brandy gandula for today check him out on twitter at gandula 13 If you want his full pga sims go over to numberfire.com and brand I'll talk to you later on today to talk some dfs for the pga championship too. Thank you as always swinging by Yeah, thanks for having me as always Alrighty, we'll see if brandy can hit another outright once again this week after having jason day last week and just hitting An overall good stretch here with his recommendations here on the show before we wrap up for today Gotta go back through last week's recommendations here on the show And of course that does start with brand and recommending jason day 17 to 1 For last week's event the atnt byron nelson Day golf pretty well the entire weekend and did eventually climb his way to the top of the leaderboard pretty tough Field there too because scottie sheff was in contention other pretty solid golfer So you will kim was there but jason day does get the win at 17 to 1 other outright So brandy were on taylor mcgummery at 46 to 1 tom hoagie at 50 to 1 also top 10 to those guys Plus 4 10 for mcgummery plus 450 for tom hoagie those didn't hit but uh day did once again other top 10 So brandy were tom kim plus 210 adam hadwin at plus 500 They both piled for 34th and last week's event final one was dylan woo top 20 at plus 4 10 woo miss a cut but Again with the day outright at 17 to 1 should have been a good week for all of you And should have covered all those other recommendations So good week by brandy once again on the pga side of things the ucl Semifinals the last week we had talked about those two weeks ago with austin cast you can find them on twitter at austin cast and austin One and one of the ucl recommendations first one was man city of arale madrida plus 110 They drew and there's somebody final that was in a in a market that did include the draw as a as a potential bet Hit was inter over ac malon at minus 120. That was metai. No bad market Inter won that one pretty handily two nil they were up They scored both those gills before the twelfth in able to coast from then on So good hit by austin there one and one overall in the week more epl talk coming up on friday the austin With only a couple weeks left here in the epl this season I have no k week on the mass car side of things starting the truck race on friday I liked william byron to win at plus 250 byron finished fourth So no dice on that one But uh the top fives were steward freason at plus 450 and christian ecas or sorry parker cligerman at five to one Freason finished runner up So the top five that did cash at plus 450 christian ecas won the race cligerman had a mechanical issue did not finish So no in there, but uh a profit via freason at plus 450 in xfinity I had outrides on kyle larson at 2 to 1 austin hill 28 to 1 larson got a speeding penalty with about 40 or 50 laps left went back to 30th and Got some help via well-timed cautions But he got to the front and he passed john hunter neiman check on the last lap for the wins some contact there so neiman check did wind up wrecking, but Larson able to get the win there despite his speeding penalty, which is always a good feeling to win even when Things may not entirely go your way Obviously if larson won hill did not win, but he finished fourth I liked him top five at plus 375 mentioned that on the show as well So larson the winner at 2 to 1 hill top five plus three 75 The other top fives that did not hit were chamler smith at plus 275 Brandon jones at plus 375 and daniel hemmrich at plus 750 and in cup The one recommendation here on the show never came close that was cori legioi top 10 at 11 to 1 legioi okay speed in practice Issue in qualifying and then he was pathetic during the race just really really bad So never came close on that one william byron Was added to the betting guide over a number fire after qualifying a plus a 50 So again, I'd encourage you to check out those over on number fire to add weekend bets because I came to the show here after qualifying Hopefully we're able to find that betting guide over at number fire and get the byron Outright at plus a 50 for the cup series race, but no dice in the one here mentioned the show It's still via the larson win an extended The top five on freeson the hill top five nice weekend overall On the racing side of things more racing thoughts coming up on thursday because we've got the all-star race this weekend We've got f1 in imola, I believe and We also have the truck series race at north wilkesburg all coming up this weekend We'll talk about that coming up on thursday tomorrow. We're gonna talk about the preakness We're gonna have christina black or a fan dual tv on once again to get her thoughts on the second leg Of the triple crown to get that right as it is posted Make sure you are subscribed to covering the spread wherever you get your podcasts and check us out over on the fan dual youtube page big thank you once again to brandon gandula Check him out on twitter at gandula 13 find his pga sims over at number fire dot com I am on twitter at jim sonnis j i m s a n n e s You can also follow the fan dual podcast network at fan dual podcasts want to thank you all for tuning in for today Good luck to you with your bets in the nba for tonight the pga this weekend We'll talk to you once again tomorrow to break down the preakness This has been covering the spread right here on the fan dual podcast network


How's it going everybody forced here rip in 2021 prism football first off the line one box number 20 random teams There's a results link in chat. You can always find them on the website as well at any time Let's get started and let's see what we got. I Don't think so Anthony Maybe the next time it's in Chicago. I'll have her come with us. I'll be cool Rookie's JC Horn Penny Sewell Got a Nick Bolton rookie Navy camo number to 25 for the Chiefs Good stuff to a 25. It's silver rookie for the Titans is Caleb Farley. Nice start to the break Rookie's Frank Darby and the Sean Wright Red shimmer bills Dawson knocks the 35 Bill bills purple for the Jetson Michael P. Ryan to 125 JK Dobbins hype I don't know though both my brother-in-law is living Philadelphia. Maybe she's just fly up. She's just go hang out Philly Got a burrow second year Rookie's a wussu kora moa tutu at well blue ice for the Rams Tyler Higmead and 99 and silver for the Cowboys Tank Lawrence Rookie's Gary Brightwell Justin Fields Orange for the bills Josh Allen a 249 bills have it a solid break sake one Barclay Rookie's Brevin Jordan Travis ETN Jr silver for the Vikings the Neil Hunter right bumby right Quinn minors Anthony Schwartz blue shimmer Falcons young haiku Number to 25 blue wave Vikings down been cooked to 199 and Titans silver Roshan Evans Come on now big hit here. Let's see it Half a box to go Rookie's Trey Nixon Trey Nixon and Palmer blue wave Jets rookie Zach Wilson boom and Jets crush it in both of the one box first off the lines tonight Travis T 49 of 199 Get that one mag. You got locked down Aaron Donald Rookie's Patrick Jones the second Go here's the first set Broncos purple ice know a fan to 225 and emergent rookie Kellen Mont Rookie's Dwayne Eskridge Joe Tryon blue wave Falcons Matt Ryan 199 Red shimmer rookie on Jones Yeah, buddy, you know my hands starting to shake. Whoo. Oh my god beautiful color match Monster hit Kevin H Caleb not now trying to make me I'm trying to look cool. All right I Got trailance rookie the nighter. Sorry guys. These rookies are like stuck together far more Jets blue shimmer Denzel men's 25 Blue wave Rams can makers to 199 Herbert fireworks That's not a big Mac that's a McGriddle. I like that I like that Still not six. We got a gold shimmer coming up here The rookies Najee Harris Elijah Mitchell Gold shimmer bears rookie Dazz new some to 10 and Ed Reid auto flashback to 149 goat safety right there Yeah, the Mac Jones whoo Mac John. Yeah, it just reminds me of middle school or high school I don't know when that how old I was in that came out I can't remember college train McKinney red wave for the Vikings is Kirk Cousins To 149 in a new recruits rookie Mac Jones Holy cow that is gonna do it. We got some no huddle breaks coming up. Thanks again everybody


Well good morning everybody. Thanks for being out here with us today. We know that, you know, as the weeks tend to go on, we're on day three of the summit and the nights tend to get a little bit longer. The mornings get a little bit more difficult, so we're happy everybody could make it out here. We have this big room to fill, so plenty of seats. So we're excited to be here today to talk a little bit about Watcher. I'm Joe Cropper from IBM. This is Ann Ball from Intel. Gina Meal from Becom. And we want to talk a little bit about the resource optimization service for OpenStack. We're very excited to be here. We want to give you a rundown sort of of what are some of the key features and goals and initiatives of Watcher. Where have we been in the past from a historical standpoint? And where do we see this project going in the future in terms of, you know, what do we accomplish in the Newton and where do we see again going in Okada? Also shown on here is the OpenStack logo known as the jellyfish for the Watcher project. For those of you that may be wondering, well, what does a jellyfish have to do with resource optimization? The jellyfish is actually the most energy efficient swimmer of all animals. And so we thought that that was a good pairing of data center optimization and whatnot. And if you want to read more about the anatomy of that Wikipedia has a lot of good information, I don't pretend to understand all of that. So what is Watcher? Watcher is a flexible resource optimization service for OpenStack clouds. We all know that OpenStack has done a good job in terms of when you're getting ready to place a virtual machine initially, put it out in the cloud, you know, we use the Nova scheduler. That handles initial placement. What happens over time is that clouds tend to become imbalanced.  You know, workloads start to spin up, become very busy, other hosts may be idle. And so how can we better optimize our environment? So dependent on, you know, do you want to do balanced terms of CPU utilization, memory utilization, energy sort of awareness, there's many different optimization strategies that you could do. There's many commercial offerings that do this. I'm sure many folks are familiar with VMware DRS, you know, we're looking at trying to bring similar technologies into open source economies like OpenStack. In addition to providing several out-of-box optimization strategies, one of the things that we want to try to accomplish is provide a flexible framework. So we realize that many different cloud providers, people whether you're running a private cloud, public cloud, you know, there's probably different ways that you may want to optimize your infrastructure. And so one of the things with Watchers, we want to have a nice framework that's flexible so that you could plug in your own custom optimization scheme. So if you wanted to have some proprietary things, that's perfectly fine. You can use Watcher for sort of that overall optimization framework. So it also can integrate with other external engines as well. And Suzanne will talk a little about this later, but there's some nice plug points so that through your optimization routine, if you want to call out to other, we use the term scoring modules, there's ways, again, nice interfaces that you can tie into some of these systems. So again, think of Watcher out-of-box value that's being provided, several optimization schemes that you can use, but again, flexible and powerful so that you can fit your own routines in there as well. So one of the other things we're very excited with Watcher is that, you know, we have many contributors from all over the globe. In fact, by definition, when, you know, we, I was excited to, you know, learn about Watcher from the folks here at Beacon back in the Vancouver Summit. And so, you know, it was started by their team based out of France. They did a lot of great work.  Walmart has since joined, you know, Survionica. I mean, many, many folks here up on the screen, ZTE, and it's a global, it's really a global team, and that's great. We're getting a lot of interesting perspectives from all over the place. And so the team, you know, very diverse in nature. We have a lot of new ideas from many different backgrounds. So hopefully, you know, we're always welcoming more people. We're very excited, and, you know, we're out on IRC, and we'd be happy to have additional folks come in and join us. But again, a very diverse set of contributors, and that's been very exciting to be a part of. So a little bit about some of the key features, and we sort of touched on this a little bit, but one of the things that was some of the out-of-box optimization routines that we provide is one of the approaches is VM live migration. So for instance, as different hosts become very utilized, I have a whole bunch of workloads on host A. I need to get them over to host B. How do I solve that problem? I can invoke VM live migration. So most hypervisors in the OpenStack ecosystem support this operation. We can invoke that, and to try to rebalance the cloud. Again, a very, very flexible infrastructure. So if there's other sorts of operations that you would want to plug in, again, VM migration is just one example. You could also powercycle compute nodes, for example, via Ironic. Maybe you want to eventually do right sizing of a virtual machine, shrink it down, grow it up. There's many, many different ways, depending on what your overall optimizations goals are. And again, Watcher provides that nice flexible framework to tie those in. There's also two modes in which Watcher can run that's very useful. So there is sort of what we call a one-time execution mode, or sometimes called one-shot execution. And that's the first mode there, single mode, where maybe as a cloud administrator you want to run one optimization loop. You can go ahead and run that just one time. And that's sort of an on-demand sort of execution mode. There's also a continuous mode where I want my audits to be running continuously in the background. So it's very asynchronous. Think of it like a disk defragmentation process. It's always running silently. You don't really recognize it. It's just happening in the background. So we expect that probably most users of this would end up going down that ladder path. That's the way a lot of some of the commercial technologies work. But again, you have that flexibility in terms of how you want to run Watcher. So how does Watcher tie into the rest of the OpenStack ecosystem? That's one of the key things that we kind of want to try to make sure that people understand here is that think of it kind of like a hub-and-spoke model where you have Watcher in the center, and it's leveraging the other projects and the services that they provide. So a perfect example is when we want to optimize the data center and I need to invoke VM live migration, right? Watcher doesn't go off and orchestrate that or rather doesn't implement that itself. It rather delegates that work off to Nova, which has already done that and tackled that problem. So we're going to leverage the services provided by Nova to do migration. For in terms of gathering metrics, right, there's Solometer, Manasca, some of these other projects that are already doing that. Watcher is not metrics collection. We instead delegate that work off to those projects. Of course Keystone would handle all the authentication. We have Oslo for all the common libraries and routines. So again, depending on how you want to optimize the service, you could call out to any of these other sorts of other projects. Again, if you wanted to start doing bare-metal operations, you would tie into Ironic. So that's sort of the relationship between Watcher with respect to the rest of the OpenStack ecosystem is we want to leverage those services to optimize the environment in whatever way may make sense for your data centers. And at the end of the day, right, this is enabling some new ways to reduce your TCO and that can really be defined as, you know, some people are looking to get the most, maybe energy efficient data centers. So that may be one way to reduce your TCO. Other folks maybe want to be getting, you know, getting the most work done. Maybe your TCO is defined by your memory utilization. So there's many different goals that you're trying to achieve and at the end of the day, as those dynamic clouds and resources, you know, change over time, again, the idea of Watcher is to come in and every time an optimization loop's run, things are in better condition than they were before. Okay? So this slide sort of talks about the overall optimization loop and so, you know, if you were to take a step back outside of the code for a minute, this is sort of the high-level processes that we're trying to cover with Watcher. I'd like to start down at the bottom of this loop in a monitoring component. So this is the phase where all of the metrics are collected into the system. Again, this is happening asynchronously, as I talked about. This is coming in from Solometer or Minasca. Again, you could plug in other metric systems if you wanted as well, but the data's coming in. Then the next phase in the optimization loop, we move into the analysis phase. So this is something that, again, this is a very theoretical picture. So we need to continually, in Watcher, we need to continue to work on this part of the loop. But in theory, one of the things that we would do here is data aggregation. So you would be looking at a lot of the information coming in from the metric systems, start aggregating information. Maybe you have very granular metrics and you want to sort of, you know, summarize those or aggregate them down into sort of a time series format to sort of reduce the overall data. So this is where the data aggregation would occur is in the analyze phase. So this is perhaps where you're starting to, you can tie into some other analytic systems. Again, Suzanne will touch on this. We did a lot of work on this piece and this Newton release. But where you could start hooking into another system, profile data, perhaps identify trends or future predictions as to, I look at all these metrics, what might the past tell me about the future so you could profile your information. That all feeds into the optimization process. So this is where, okay, I've sort of, I understand the landscape of my data center. Now I want to try to optimize it and the input to the optimizer is a number of different pieces of information such as constraints. Maybe there's certain virtual machines that need to be co-located or anti-co-located. What is my overall objective? Again, do I want to pack up a certain host and fill it up with VMs or do I want to redistribute my VMs based on, again, CPU or memory utilization or some combination thereof? So the optimizer is ultimately deciding what steps need to be taken to improve my data center. And then that feeds into the planning phase and the planner is ultimately figuring out, okay, here's all the, for instance, migrations that need to happen. The planner is sort of putting together, think of it kind of like a graph. You know, maybe certain operations, certain migrations can occur in parallel. Maybe some need to run serially. So it's putting together sort of the master plan that are from, you know, state A to state B and state B being better or more efficient than the initial state. And then the last piece of that is the supplier. So this is where all of the plan has been put together. Now I need to go ahead and execute that plan and turn it into reality. And again, this is a, think of it like a loop that will run continuously over. And again, the idea is that every time this loop runs, things are more effective than they were previously. So it's a very, very important thing to realize that just because you run this one time doesn't mean it's perfect and it's going to remain perfect. It's rather a very continuous sort of set of steps that we expect to need to happen. So this next chart here talks a little about the overall architecture of Watcher. And there's some very common things with respect to some other services in OpenStack. So for instance, you have a Watcher API process. You were leveraging the OpenStack message bus. So again, this is very similar to other projects. And I tried to put some numbers on here to kind of help sort of follow it. So if you look in the lower left-hand corner, this is where we have the metrics collection occurring. So this is, again, as I talked about, where we have Solometer, Manoska can be used, Mutual Exclusive, one or the other. That information then feeds into, we've got a clustered data model. And this is sort of an in-memory representation. That was something that was done here in this release that can be updated that the optimization process can ultimately leverage to, again, to query this current state of the system. Step two, or really the second component here is where the administrator starts to interact with Watcher. So as an admin, I have a CLI interface. So if you look in the upper left-hand corner, it also ties into the OpenStack CLI. So it's OpenStack Optimize that calls into the Watcher CLIs. I can run my audits and optimization processes there. There's also a Horizon plugin. And all of these will flow into, when you make that request, it'll flow into the Watcher API. So sort of in the mid-center there. The Watcher API, and then, of course, can delegate that work off to some of the other components. So, for instance, number three, this is where you have sort of the overall optimization or optimizer for Watcher. This is where the sort of the planner lives that we talked about on the previous optimization loop. This is the component that is actually making the decisions about what steps need to be taken to optimize the data center. And then number four is leveraging the cluster data model to ultimately figure out, okay, what does the state of my cloud look like? What VMs are on what hosts, so on and so forth. It leverages all that information to make its decisions. And then number five, we've got the Watcher Action Applier. So this is, again, that component that is taking all the information applying everything, and that leverages up in the upper right-hand corner, the components in box six. So this is where you would call out to some of the other services in the ecosystem. So, again, whether you're doing migrations, you would be leveraging the Nova service for that. Eventually we want to tie into Neutron and Cinder. So the dotted lines represent more of that's a future set of actions we would like to take. There's a number of optimizations in the OS settings, different what volumes are attached to which host. There's a number of things that we can do there longer term, so that's kind of how this fits together. So the next chart I would like to turn over to Suzanne to talk a little bit about the Watcher History, the roadmap, you know, what we accomplished in Newton and where we see ourselves going in Okada. Suzanne? Thank you. So I'm quickly going to go over what Joe said, the Watcher History and where we're going. So, the first time I heard about the Watcher was at the Vancouver Summit where Beacon presented it and like Joe mentioned earlier, IBM and Intel were very interested in this project. So in September 15 we kind of had a formal meeting over at Beacon and that's when we kind of kicked off the initiative. At that point we were really focusing on making sure that, at least from an Intel perspective making sure we brought in a small amount of what I would call strategies even though it's simple that still would allow us to actually test the infrastructure and make sure that the infrastructure could handle some of the optimization that we were looking for. And I think at this point now that we are in October 16th the infrastructure is actually a very good state and so one of the things that we're looking for is more strategies people contributing more strategies so that it's becoming more and more useful for the community. One of the things kind of a big thing that happened since we met last time in Austin is that we're now an official project. On May 31st we became part of the OpenStack Big Tent. Yes. Thanks everybody. Thank you for everybody for participating and doing this. So one of the things I'm going to talk about over the next 10 minutes is really all the great work we did in the Newton release and how far we've come since we became part of the Big Tent and Jean-Emile is going to talk about our plans for the OCATA release. So if we look at some of the the accomplishment for the Newton cycle one of the things that was of a lot of interest for at least Intel was the watcher scoring module. So the way it is today you know we want to achieve some goals we've implemented some strategies and those are part of the plugins that are within watcher but a lot of the data scientists work on a different set of tools that are kind of part of an external framework and so the idea here was to integrate with external scoring engines so that we can take those into account when we actually execute strategies and try to achieve goals and I'll quickly go over this in a couple more slides just to give you a better visual idea of how this actually works. The other thing that we've accomplished is we added the active mode so as Joe mentioned earlier the way that it had been up until Newton was that the admin would trigger manually an audit and get an action plan and then would have to kind of carry that out by hand. The way we have it now is that we have this notion of continuous audit so the cloud is actually can now continuously be audited while it's action plan automatically being carried out and while we still I think it's important that we still have both modes in that not everybody is going to want all actions to be carried out automatically and also looking at from an internal perspective the way our admin works is that they kind of need to trust the system before they're going to let you do anything do some automatic migration and so this is why we kind of have those two modes and eventually the way I envision this is that some of the easy tasks kind of no brainer tasks people are going to just say yes please carry those out automatically without me approving them moving one of your bigger applications around you are going to want to make sure that it really pays off before you want to do that and so I see really both modes being very valuable so actually getting back to the value of you know the action plan or of your optimization one of the things that was added into a watcher this time is this notion of effect if you Cassidy indicator and what that really means is that when you create when you have a strategy the strategy writer can actually put in this the notion of what is the type of efficiency that a certain thing is going to give him or her and just as an example and what this is actually giving you is when you run and audit and you get an action plan back you can actually see what are the actions and what is the efficiency that you're going to gain by applying this action plan so it kind of motivate the admin to want to carry out an action plan if you don't know what your optimization gives you there is really no reason to really think you're going to get anything out of it and I was just talking to some member of the watcher team we've been running some scalability test on an Intel cluster with like 25 compute and as we ran that we ended up creating 177 VMs migrating them around so that we suddenly got 23 out of the 24 nodes free and it had an efficiency indicator that would kind of show that this was worth doing one of the other things that we've been focusing on and I was telling you about that around more value added optimization strategy and I have a slide where we kind of list some of those things that we've added for Newton some of the other things that kind of core features we've added to watcher that might be kind of less obvious to the user but good in terms of efficiency and performance is a local cluster state model and what we've done here is we've created that and where before it was actually created for each audit here it's actually in memory and being updated from specific services as needed and the last thing is you know one of the things that we've been doing is scalability test so 30 node doesn't sound like that much but there is a big difference between running on 5 and then 30 and so it's one step one of the things we're going to also look at is through the kind of the open compute initiative we can get a larger cluster and we've actually submitted a request for even a larger cluster so a lot of us are trying to be ready to run watcher in production and so we do want to be able to make sure it's scale to a decent size these are the strategy we currently have in watcher and again this is very pluggable so anybody who wants to contribute their own strategy are more than welcome to do that and like Jean-Émile mentioned yesterday not all strategies has to be open sourced we do have customers that are doing strategies and then just keeping them for themselves and not outsourcing them we just think it's important that at least watcher has a base of strategies that allows you to get value out of watcher as you know pretty much out of the box so as you can see there is many companies have contributed to the strategies and it range everything from like looking at server outlet temperature and doing threshold to VM migration to basic consolidation and workflow stabilization around VMs and so I won't go over each of them you can read them and they are also on the blueprint but one of the things that is interesting and I think that's one of the powerful things about watcher is I really look at it as an orchestrator with a data analytics engine and so as you're looking at so you can actually have as we move forward we're also looking at maybe having more of a data analytics stack in there so that we can do clustering and classification right there real time around the fingerprinting of some of the workloads so that we can do better placement and also measure a contention of workloads so this is one of the things that I personally start with very cool and I wanted to highlight here is that we have people who are actually part of the watcher team writing blogs about how their contributions are making a change in their environments and so this is I think the first blog I've seen of somebody who actually have been using open stack watcher with their specific plugin and showing that in this case they actually have a more efficient deployment and so you know this is also for all the watcher participants this is great for us because the more we talk about watcher the better the more people learn about it and are aware of our existence so going back to the watcher scoring module so one of the things we were talking about earlier is that in many cases and maybe I'll just go to this one first and come back so if you look at where watcher fits in the ecosystem it's really kind of optimizing an open stack cloud based on strategies that are implemented up until today they were really part of watcher themselves one of the things so the trusted analytic platform and this is just an example of an implementation it could be a different external service but its scoring engine can be published into the watcher scoring module and then it's kind of being used just as the other strategy and what we created here was kind of a nice tie with external analytics platforms through well defined APIs and the reason we thought this was a very interesting use case is really because we wanted the data scientist to not have to touch the cloud and we wanted the admin of the open stack cloud to not have to understand what a plugin is doing or what needs to be done in order to integrate a plugin the other thing that this is giving us is really how do I do this little bread thing there's a button right here oh yeah it might not work so one of the things was really about keeping the data scientist working with a tool that he or she is really good at and letting the administrator feel safe that nobody was actually touching or messing with the cloud the other thing that this allows us to do in this case is actually having the model be trained and learn outside the open stack ecosystem and close to real time publish the scoring engine and it would take action if I go back here so going back to this like I said the scoring engine is really what we would call kind of a generic machine learning service and it has a standard API to interact with any external analytics service in the case of a TAP which is open source as well and is an effort that is led by Intel but hopefully more people are going to start contributing we just focus that as our first example since we knew of we had experience with both TAP and the watcher piece and I will pass it on to Joimine so what are the plans for the Okata release so first of all we want to work on the odyscope so right now we have an audit this is done on the whole infrastructure and sometimes depending on what you want to optimize this is better to just scope the optimization on something for example we would like to be able to optimize an availability zone or a no cycle gates and sometimes we just want to focus on storage sometimes we just want to focus on network so the idea behind the odyscope is just to be able to scope the audit on some resources available in the open stack and the other thing that we are looking for is to improve action plan storage in watcher so in the watcher app layer we are using a workflow engine called Taskflow and we want to leverage concurrent actions of Taskflow in order to be able to migrate several virtual machines at a time because in the watcher planner for now we are able to schedule several actions at a time but we cannot store this information in the current database so we want to be able to do that for many reasons for performance reasons for security reasons and so on and the other thing that we want to work it's a graph based cluster models so right now we are using a flat structure of the infrastructure this means that we cannot for example modelize efficiently network topology and sometimes we want to work on optimizations like have many links between services so the idea behind cluster based cluster model is to be able to modulate network topology and so on according to what we want to optimize this is the best thing to use another thing that we want to do in Ocata release is add workload characterizations quality of service is something that matters a lot for us and for many of the customers that we have one way to understand all the virtual machine are using the resources is to use workload finger printing or workload characterizations know how the virtual machine are using the resources allow us to for example proactively load balance the loads but we can think for many other use cases use notification in watcher so right now when we perform the edit this is done on any other open components are not aware of that and for example watcher set wants to be aware that we are doing an action plan to the systems and for example Nova wants to know that we are doing some things so we want to let the other open component to react to some events in a fashion event fashion way as we say many times we want to add many new strategies one of the key feature of watcher is playable architecture this means that if you are if you have some optimization problems we think that watcher is the best place to do all that we try to we provide everything you need to just focus on your optimization problems so if you have an optimization problems and you want to work with us we will be really happy to help you so this is the strategies that we plan to add in the Okata release so first of all Wal-Mart on Intel wants to work and to use finger printings in order to guarantee service level objectives so the idea behind that is to some of the workload that we are running in the infrastructure are critical for the business some of them are less important we can imagine for example some continuous integration jobs that are not critical and we can kill them in order to guarantee the service of critical systems another thing that we want to add in the Okata release is to work with ZTI that's an elastic extension of strategy sometimes sometimes when you choose initially the flavor this is not a well choose and we want to be able to add for example some vCPU or RAM to guarantee the service so thank you very much for the for us we have a wiki with many documentations for example we will explain you very well your own strategies we have an ERC meeting every Wednesday and if you want to see what's in action we have a video online thank you is there a mic if you ask your question we will repeat it yeah we will repeat it that's fine I mean yeah I can take a so I think the question was maybe is there some other projects that are doing with respect to self healing networks and maybe doing some of those sorts of operations how does Watcher tie into some of those so that's a really interesting question because when you talk about the whole idea with Watcher is providing this generic framework and I guess this is my take and others can feel free to add to this but it provides a nice framework for optimization the types of optimizations you may be doing right now they are mostly compute centric so we are starting around for instance CPU utilization and balancing or having workloads that are sort of packed up on a host or doing round robin sort of deployments eventually with how Watcher if you remember back to one of the architectural pictures I showed you could tie this and link it into Neutron or Cinder or some of these other things so I see this is really providing a much broader scope in terms of whereas some of these other projects may focus on very specific sorts of things that are relevant to maybe their project only and again depending on how if you look at your overall data center there could be a number of different ways in which you are trying to optimize that and again I see Watcher as sort of a nice utility or service you could start running that again has these generic out of box routines and others could then plug in their own implementations and I think that you know we are again I guess the short answer to the question is a very broad you know the Watcher system can be very broadly defined again some of the other ones are maybe a little bit more specific I don't know if this is energy to me anybody want to add to that? So we are coming at Watcher from workload kind of optimization and you know for example finger printing of the application with phases and trends being able to predict as I am launching my next app is there going to be contention with existing apps that's really where I see Watcher I don't say that you know self healing networks is anywhere in that category and you know self healing networks is to me what I would call a niche you know it's kind of a smaller piece but I am really looking at you know how do I increase the utilization of my overall cloud from let's say the 20% service CPU utilization to you know 50 or more towards the same type of utilization that large service providers are getting just because they have a much bigger mix of workload than customers in my opinion many other projects are rule based on what is more about analytic models for example you have an application we will learn the basements of the application how it works usually and after when we learn how this application is working we will say okay now we see that compared to the history this machine are not the same behavior and you can learn that you have to think about how many other projects are okay if this virtual machine is above this threshold do that and we have more learning ways to do things right the overall framework exactly any other questions yeah I think the question was about running watch with all the versions of OpenStack or what level does it support I think it's Miteca Mitaka we really went under heavy development back in Mitaka and obviously now with Newton that's where we would really recommend that people start with the current release in the watcher configuration file you can specify what is the current version of Keystone so you can yeah sure sorry there's a question just there can this be used for initial VM placement so that's a great question can watcher be used for the initial placement of the VM and the short answer is really no in fact we're looking at that's what the Nova scheduler does when you initially place it and that would continue to be so in the future down the road what we want to use watcher for is that post VM deployment optimization process you look at the workloads in the cloud you're going to have long running jobs and short lived jobs so even though it looks like you have the optimal initial placement over time suddenly you end up with a lot of fragmentation and we're focusing on kind of the fragmentation and making sure that we optimize the cloud as it's running given that we feel currently that that's something that's missing and we need time to learn how the virtual machine is running so anything else thank you so much join us on IRC if you're interested appreciate it


Companies don't have unlimited resources nor unlimited demand for their products. Because of this, they have constraints which might limit production or demand. When companies are faced with constraints, they need to focus on the items with the highest contribution margin per constraint. For example, a company can produce three products, product A, product B, product C. The production constraints are 5,000 machine hours. They can't produce any products beyond the maximum usage of 5,000 machine hours. So how do they decide which products to produce? We might focus on producing the products with the highest contribution margin. Based on what we've learned so far, that seems logical. Here we see the contribution margin for all three products. Based on this data, product C has the highest contribution margin of $25 per unit. If we were not constrained by machine hours, that logic makes sense. But since we are constrained, we really need to look at the highest contribution margin per constraint. So with the additional data of machine hours needed to produce a unit, let's figure out the contribution margin per constraint. So product A requires two machine hours to make one unit, product B four machine hours to make one unit, and product C five machine hours to make one unit. So we could produce 2,500 units of A, 1,250 units of B, or 1,000 units of C. Once we factor in the constraints of machine hours, we see that product A gives us the highest total contribution margin. And is the product that the company should emphasize or prioritize. In summary, when faced with constraints that limit production or demand, make the products with the highest contribution margin per constraint.