All right, everybody. It's five minutes after the hour, so we just want to be prompt and respect everybody's time. I'm Aura Young at UNC Charlotte, and this is Sheila Rabin. Did I pronounce that right, Rabin? That's correct. You did. Good. Yay. Her presentation is entitled, Connecting the Dots with Persistent Identifiers for ETDs. And Sheila is from Larassus. Is that how that's pronounced? Larassus. Okay, that sounds a lot prettier. Okay, so the presentation is going to be about 15 minutes or so, and then there will be time for Q&A. During the presentation part of this, just remember to keep your cameras and microphones muted, and then when we move to the Q&A, you can unmute to ask your question. And then, you know, you could also put comments in the chat if you want or questions in the Q&A, and if those appear there, I can read those to Sheila. So take it away, Sheila. Perfect. Thank you. And thanks, everyone, for joining this session. Again, my name is Sheila Rabin. I'm the Program Leader for Persistent Identifier Communities at Larassus, and that includes the Orchid US Community and the Larassus Data Site US Community. This session will provide an overview of how persistent identifiers, and in this case, specifically Orchid and DOIs, can be used in ETD workflows to support fair scholarship and also gathering information needed to assess institutional impact with a focus on current trends as well as challenges and opportunities for adoption. And I think some of you may already be using persistent identifiers and already familiar with these things, and some may not be, but to make sure we're all starting on the same page, just a brief review about what persistent identifiers are, or PIDs for short. So PIDs are basically unique labels or references that allow us to disambiguate people, places, and things in the research and scholarly landscape, regardless of changes over time, to help us track and gather information about research and scholarship and the entities that are involved. So for example, if we're looking for a specific person or author, we can use Orchid ID to uniquely identify the person that we're looking for to make sure it's the right person, even if there are multiple people with the same name, or if the person's name has changed over time. And if we're trying to identify objects that were involved in research, or maybe the research output itself, we can use DOIs or digital object identifiers to indicate precisely what object we're talking about. And if we're trying to identify where certain research took place or what organizations were involved, we can use the Research Organization Registry or ROAR ID to uniquely identify the institution in question. And these are just a few examples, but with these and other persistent identifiers, we can disambiguate people, places, and things regardless of language, naming, or changes over time. And the more we can use these PIDs across the research and scholarly landscape, the more we can answer questions about things like what organizations participated in the research, who was involved, how many publications came out of it, who's collaborating, and all of those kinds of questions. And by using multiple PIDs together, we can help to make research and scholarly content more fair. And that stands for findable, accessible, interoperable, and reusable. So PIDs not only help to identify specific entities, and that helps with findability and accessibility, that also kind of when things are more findable and accessible, they're more likely to be reused. So the graphic that you're seeing here is from an article that I have cited that talks about the interconnections of persistent identifiers in what we call a PID graph. So you can see here that PIDs allow us to find the network connections between people, organizations, funders, publications, data sets, and software, for example. And if PIDs are used in ETD workflows, then ETDs can also be part of this ecosystem. And so for ETDs specifically, I'm going to focus on ORCID and DOIs. Many of you are probably already familiar with ORCID, which stands for Open Researcher and Contributor Identifier. So again, ORCID IDs are unique persistent identifiers for people, specifically people who are involved in research or other contributions. So anyone can get an ORCID ID for free. And the ORCID organization is a nonprofit, community-driven organization that serves the entire global community, and they manage the ORCID registry with support from organizational members across the globe. And so ORCID allows individuals to distinguish themselves from others, regardless of what their name is or changes in their name over time. And it allows them to keep all of their affiliations and activity information in one centralized place, similar to what you would see on a CV or a resume. And ORCID also has an API or application programming interface that allows for transfer of data between an individual's ORCID record and local institutional systems. And I think many institutions are probably already collecting authors' ORCID IDs for ETDs. If you're using the ProQuest ETD submission system as an administrator, you can enable an ORCID field where students can manually enter their ORCID ID. And I'm also aware of the Vario ETD submission system, which I believe works very similarly. People can enter their ORCID ID within those systems. But if you're using other systems or other workflows for collecting ETDs, I would love to hear about it. So feel free to put that in the chat, for example. One thing to note, though, is that manual entry of an ORCID ID does leave room for potential error. So if somebody is typing in their ORCID ID and they accidentally get one number wrong, that's going to kind of defeat the purpose of having that unique number for that person. So the best practice is to make sure that you're getting the correct ORCID ID for each author. And that's to use basically the ORCID API to collect authenticated ORCID IDs, which you can do if your organization is a member of ORCID. For example, University of Virginia has an ETD repository that has an ORCID API integration, so students can authorize University of Virginia to get their correct ORCID ID, as you're seeing here. And that way, they can make sure they have the right ORCID ID for each person. And also, ETDs can be added to the works section of a person's ORCID record. Either by the individual entering that information themselves, your organization can add that to their ORCID record using the API. Or if you're assigning DOIs to your ETDs, which we'll talk about more in just a minute, then your students can actually use the ORCID search and link wizards to authorize either data site or crossref to add their ETD to their ORCID record for them automatically. And we'll talk about DOIs, like I said in just a minute. The image that you're seeing here is just a screenshot of my thesis from my ORCID record, and I entered it myself, and that appears on my ORCID record now. So in terms of benefits and challenges around ORCID, ORCID is beneficial because it serves as a shared standard for uniquely identifying individuals, and organizations can benefit from using ORCID to streamline collection of data about research and scholarly activities, as well as also assert information to people's ORCID records to confirm affiliations and other activities associated with the institution. And all of this is designed to save time and reduce administrative burden by allowing information to be entered into ORCID once and then reused often wherever that information is needed. Some potential challenges for using ORCID are that each individual must take action. A central tenet of ORCID is that individuals have full control over their ORCID record, and individuals have to register for their ORCID ID and make sure that they're using it. So getting this message out to researchers can be a challenge to ORCID adoption. And also to get the most value of ORCID beyond ETDs, there really needs to be kind of a partnership and collaboration between multiple organizational stakeholders, such as, you know, the library, the research office, sponsored programs, central IT, and that can sometimes be a challenge at some organizations too. So besides ORCID, you might want to think about assigning DOIs to your ETDs if you're not already. DOI stands for Digital Object Identifier, and it's usually expressed as a URI hosted at doi.org that corresponds to a metadata record about that object. So this example that you're seeing here is a DOI for a presentation about ORCID and HINE Online. And if this resource gets cited by others, but let's say the URL changes over time, the resource will still be accessible because it has a DOI and we're keeping that URL metadata up to date. So the idea is that it can always be found in the future, and we can avoid people running into like a 404 page not found error by having this resource migrate on the web. So for DOIs, there are a few organizations known as DOI registration agencies that manage the logistics behind DOIs. So the two organizations that are most used in the U.S. are Crossref and Datasite. Crossref most commonly supports DOIs for like journal publications, that kind of thing. And then Datasite is more geared toward research data, but also other types of resources that you would find in an institutional repository. So something like a thesis or a dissertation. And Crossref and Datasite are both supported by member organizations that want to assign DOIs to their local materials. So each member organization must submit metadata that corresponds to the item they're assigning a DOI to. Including a URL that points to the landing page. So I've got kind of the metadata form for DOI here. So you would enter the URL. And then also something cool to note is that when you're entering creator metadata, you can actually use the person's ORCID ID to uniquely identify the creator rather than just their name. So that's one cool thing about ORCID and DOIs is that you can use ORCID IDs in your DOI metadata and DOIs can be found in ORCID metadata too. In terms of the benefits and challenges with DOIs, they do provide a shared standard for permanent identification of content and objects. And when DOIs are assigned to content, whether it's ETDs or something else, we can more easily manage those local assets, track usage of those assets through machine actionable, disambiguous citations, and ensure that the content is permanently accessible over time. Ultimately, again, saving time and reducing administrative burden. The biggest challenge when it comes to DOIs is making sure that the metadata related to the object, specifically the URL, is kept up to date over time, as well as the persistence of the object itself. So DOIs are supposed to be reliable forever. So ensuring continuity and sustainability of that DOI metadata maintenance is really key. So as I mentioned, these these PIDs work together. They can each be included in the other's metadata. And that will help to link people and their ETDs or other objects together in a shared persistent way over time. And as I mentioned previously, if you are assigning DOIs to your ETDs, if you include the author's ORCID ID in your DOI metadata, and that author has connected their ORCID ID with either the crossref or data site search and link wizard within ORCID, then that author's ETD can be automatically added to their ORCID record through either crossref or data site. It depends on which registration agency you're using to assign the DOI. And aside from ORCID and DOIs, I want to also briefly mention ROAR, which stands for Research Organization Registry and is the relatively new and entirely open and community supported identifier for organizations. So if possible, you'll also want to use ROAR IDs in your ETD metadata to identify your institution. And ROAR IDs can be included in DOI metadata. And soon they will also be the primary organization identifier used in ORCID as well. So again, it's a good idea to use all of these persistent identifiers together so that the metadata is connected and discoverable. And the more persistent identifiers are used, the more we can see relationships and impact via these kind of pig graph connections. So you've got an ETD with the DOI there, that's linked to the author, that's linked to the organization, and so on. And you can see kind of all the connections between different resources, people, and organizations.  My colleagues in Australia did this, and they looked at metadata from ORCID and DOIs to see what organizations and what countries were involved in coronavirus research. And so the different colors represent different countries, and we could drill down into this data even more to see the specifics of who was involved. So this is just one example of the possibilities that are there when we all use persistent identifiers. And if you're not involved in ORCID and you want to take advantage of the ORCID API, we do have a consortium for institutions in the U.S. that are ORCID members, nonprofit organizations, can join. It's called the ORCID U.S. Community, and it was formed in 2018 as a partnership between several library consortia that you're seeing here. And right now we have over 150 members that are participating. So if you're interested in this, let me know. We also have a similar consortium for data site DOIs. So if you're not already using DOIs and you want to start doing that, let me know because we just started this consortium this year. Both of these are administered at Lyrasys, and we'd love to talk to you if you're interested in this. And I think that leaves us some time for questions, but also definitely feel free to contact me. My email address is here, and also I had posted in the chat some links to materials from this session so you can have access to the slides. There's also a handout. And that's it for me. Thank you so much for your time. Thanks, Sheila. And thanks for going ahead and putting those materials in the chat for us. That's super helpful. There's a question there from Catherine Flynn. I don't know if Catherine wants to unmute herself and ask. Or I can, let's see, Catherine says, can you compare the handle system with DOIs for the purpose of identifying ETDs? Is there a difference in perspective with respect to ORCID? Yeah. So with respect to ORCID, you can use a handle and that's fine. The thing that makes a DOI different is that there are kind of more entities involved that are connecting to DOIs and also indexing the metadata behind the DOIs. So DOIs are generally more discoverable. There are a whole bunch of different kind of external services that other kind of vendors or other companies run where they're actually indexing DOI metadata in their search services. So DOIs are a little bit more open in that way because all of the metadata behind the DOI is open. Whereas the handle is a persistent identifier, but it's not really linked into all these other identifiers. For example, behind a DOI, you can have your ROAR IDs linked, your ORCID IDs linked, and that's really what contributes to seeing these connections between entities. Whereas with the handle, you're not really getting those additional connections. But DOIs are based on the handle system. So they are persistent identifiers. They're just not as connected with the broader landscape and not as discoverable as well. So hopefully that answers your question, Kathy. Yes, very helpful Sheila. Thank you. Any other questions or comments? And also if anybody is already using ORCID and DOIs in your ETD workflows, I would love to hear from you. It's because I'm always just interested in what people are doing. And the other thing is if you're using some system other than like the ProQuest ETD or the Vario ETD system, I would love to hear about that as well. And hopefully this session was helpful. Okay, great. Thanks, Roxanne. Yeah, I mean, any questions that you have about persistent identifiers in general, even just, you know, feel free to contact me. I'm happy to provide more. This is just a brief snapshot kind of. See, John, we deposit directly to our IR and then ProQuest harvest them from there. We have an ORCID field, but it isn't mandated that students create one yet. Yeah, I've heard a similar thing from other institutions where they give students the option to provide their ORCID ID, but it's not mandated. And I think that's fine. I think students are already kind of stressed out enough with the whole process of submitting their ETD and getting ready to graduate, giving them yet one more thing that they have to do. I can see why you would want to avoid that. But if they're willing, if they have an ORCID ID and they will give it to you, then that's always a great thing to include. All right. Well, it's 25 minutes past the hour. So time for us to wrap up and head to the next breakout session. So thank you so much, Sheila. Thanks, Aron. Thanks, everyone, for attending. Bye. Have a good day.


Thank you, Janis, for this really touching introduction. In fact, we had the dream to do it the other way, but this time it didn't work, maybe the next time. We don't want to fail better, but to fail less. And I would like to congratulate you for what you presented to us. The whole initiative had so much energy, and I think it's absolutely necessary to do that. The passion with which all of you presented the endeavor of Europe and of restarting Europe. The passion and the energy which you personally also invested in that initiative is, for me, a reason for admiration, and I thank you very much for that. In fact, we struggled together in summer, during the last some weeks. We struggled a little bit between each other because you wanted me to be part of that movement. And I said no. And then you said, well, OK, then you have to explain. And I will do that in very few words because I think it's already late, and you won't be very interested in these words. But and what I certainly do not want is to calm down the enthusiasm and the energy and all that what has come up. But and of course, Europe is in a really big danger. What we see presently, and I totally agree with the analysis in your manifesto, that democracy has been replaced during the last years by, you say very much, bureaucracy. I would say technocracy because bureaucracy, I don't see any democracy which could do without bureaucracy. We will always need a bureaucracy. And I'm too old to deny that. But we have, of course, the main point, and there we agree, of course, is that this bureaucracy should not be, instead of politically decision making, that it should be transparent to a certain degree. Not all the bureaucrats can be transparent, but the decision making should be transparent. So I agree with you and what you say and your claim for transparency. I'm really very much looking forward and very curious to see what will happen when you publicize your claims for transparency for the reasons, for the institutions you mentioned. Now comes a little different in the analysis. Of course, the financial crisis was the start of de-democratization of destroying to a certain degree the democracy in Europe. But this has been the result of political decision making. Where I disagree is that in a certain way, in your manifesto, you see a necessity between the institutions of the European Union and the policy which has been made. No, I don't think that the institutions by themselves, or with all their weaknesses, of course, have really brought about neoliberalism and austerity, but it bears the political majorities we had in Europe. And these political majorities have to be changed. There we agree again. These political majorities have to be changed. And I'm particularly unhappy about the responsibilities the German government has in that deterioration of the European Union and desolidarization of the European Union. I think that the lack of solidarity has started with the Chancellor Merkel saying that there is no bailout for neighboring states, whereas there was a bailout for banks. This was the start of desolidarization. And this is a political decision making. And therefore, I think, with this blindness towards all the social disasters, consequences of austerity policy, this is what has to be changed. There was a saying of the German philosopher Adorno, wer vom Nationalsozialismus oder vom Fascismus spricht soll vom Kapitalismus nicht schweigen, who speaks about fascism should not silence capitalism. One could also say who speaks about rightist extremism should not silence austerity policy. This is a very close connection. There is a strong German responsibility. Unfortunately, and this is hard for me, I'm convinced social democrat for the values of the social democracy, for good traditions of the social democracy. But I have to say that in the Grand Coalition, this policy of austerity, which in the program has always been denied, has been supported by the Social Democratic Party. And that was extremely desperate. So I'm very unhappy about that. But I will tell you, I will tell you, the party is more than the leaders of the party. And I am traveling around the party, and I'm having a lot of meetings with the party. Until now, during the last months, I have never met a party meeting which contradicted my position and which supported the leaders, not one. This is interesting for the situation. Now, the present refugee crisis, as I see it, is not certainly the reason of the dramatic situation of the European Union. It is a catalysator of the dramatic situation of the European Union. And when I hear German politicians telling the Turkish government that for moral reasons, they should open their borders for the refugees from Aleppo. But at the same time, close their borders for these same refugees towards the European Union, I can't say what is that as a political and a moral behavior. Simply cannot stand such a contradictory position. And we should never allow ourselves to get used to that. We have to protest such a moral contradiction.  I mean, this is completely crazy. And we should not accept that. The difference is that I think we have to change the policy. Of course, the policy has also introduced procedures and institutions, for instance, as a European senator, which tried to judicially fix one policy, calling it not political, but just judicial. And this is, of course, this is a trick. This is not to accept. But again, it is a policy. So my crucial question is, how can we implement the goals which you pursue and which I share? And to implement the goals, I think we absolutely need partners which kind of bring about a chain from organized civil society or even less organized civil society, as I see the young lady over there and was there. And that reminded me sometimes in 1968 that it's nice, that it's absolutely necessary. 72 is a certain distance to that. OK, so to kind of bring about a chain, and I think we need all help and all cooperation from other parties, from the green. I have openly always spoken out for red, red, green in Germany. We need it from the trade unions. We need it from organizational powers, because without these organizational powers, we will not succeed. We have to do it. But of course, on the other hand, we need your initiative, because I've never seen in the last years that a political party would have really made something new or has taken a new initiative. It's coming from the organized civil society. Two more points. One, I have always been a reformist. So this is not really interesting. I know. But this is my conviction. And I know from the one hand that reformists, if they want to be successful, they absolutely need a radical movement. It's completely a reformist by themselves won't achieve nothing. They need a kind of motor, a need of movement, a radical movement, and sharp movements. This is indispensable. On the other hand, sometimes these radical movements also need reformists, because they could, in a way, also become either a little bit sectarian or a little bit populist in generalizing everything. So this is not just to have an equilibrium, but this is my experience of policy. For that purpose, we created a number of people from the Greens, from the left, from the social democracy, from the trade unions, a new initiative, Restart Europe. This is very close to your analysis. And we would like to cooperate with you. I don't think it would be good to be part of you, but to cooperate with you. And as far as I see, there are two very important things to do now in order not just to get out to have had a wonderful, overwhelming event, but then what comes after. You already said there will be these kind of attacks against the establishment, OK? But I think what would be good would be that in the following weeks and months, we would have all over Europe two kinds of events. One, which would discuss democracy, because what kind of democracy do we want? Anzio Urban spoke about that. I have been a professor for political theory and democracy, so I have dealt with that for about 40 years. So this is an important, not only theoretical point. And we have to try to agree upon that. At least not about everything, but about essential elements of what we understand by democracy. This is the first point. And the other point is to organize with all the artists and members of your movement to organize events where, again, the idea of solidarity, of Europe, of democracy, of justice, of freedom would come up to my minds, because this is really the reason why I'm extremely thankful to you. In a time of cynicism in which we very often live, in a time of resignation in which we very often live, you counteracted. You said, no, we will reanimate the real roots of European democracy, of European Union. And you, in this way, kind of encouraged us all, also myself, to not resign but to go on. I thank you for that, and I would like to cooperate with you. I have always liked the word of partnership. My husband is sometimes laughing at me, but even in a marriage, I like partnership to be equal in inequality, be equal, and not the same. So partnership, I like it. And I would be very glad if we could cooperate with you. Thank you again.


DBS presents Our Miss Brooks starring Eve Arden. Our Miss Brooks is a schoolteacher. To be specific, she teaches English at Madison High. Connie Brooks is pretty enthusiastic about her work, too, in fact, in her own words. Although teaching isn't the most profitable career in the world, you must admit the hours are appalling. But there's always my secret heartthrob, Mr. Boynton.  But he'll come around. Even a biology teacher must sooner or later get a little biological. Meanwhile, I can dream, can't I? Yes, Connie Brooks can dream. Even now, she's in the middle of the sweetest dream of them all. The one that comes right before 7 a.m. Hold me closer, Mr. Boynton. There. Now kiss me. Oh. How does that make you feel? That's what it does to me, too.  Miss Brooks, you'll be late. Kiss me again, Mr. Boynton. Miss Brooks, you have to go to school. For this, I don't have to go to school. Oh. Oh. Good morning. Well, if it isn't my favorite landlady. Oh, good morning, Mrs. Davis. What in the world are you dreaming about? Oh, nothing much. Just a school. I was giving an English lesson. Well, from the way your lips were puckered, I thought you were taking a bugle lesson. Better get up here. Today's the day you're supposed to find out about that new job as head of the English department from your new principal. Oh, that's right, Mrs. Davis. For three years I've been waiting for that job. Three years of scrimping and scraping to get along. Now it's all going to be different. With this raise, I'll be able to run down to Miami once in a while, and after I've had the job a while, I might even go abroad. Paris. The Riviera. Beerits in the spring. The Casino at Monte Carlo. Just how much more money does this new job pay, Miss Brooks? $6 a month. You better watch your step at Monte Carlo. Money goes pretty fast down there. Money goes fast anywhere. I haven't been able to catch any for years. Now hurry and get dressed, dear. I have a lovely surprise for your breakfast. Another one of your surprise recipes, Mrs. Davis? I hope it's not clam fritters again. You see, dear, come along. Dear, here's your surprise. Armenian pancakes. They've been setting for five days. What else could they do? I mean in goat's milk. It takes five days for it to get good and sour. Sour goat's milk?  Don't pay any attention to the smell. Oh, please, Mrs. Davis, no. Well, just one bite. Tell the truth now. Aren't they delicious? I don't want to hurt your feelings, Mrs. Davis, but if I were the goat responsible for this concoction, I would hang myself by my own beard. If you don't mind, I'll have to pass out the pancakes. But, Miss Brooks, it's a crime to throw out these pancakes. What's the crime? Carrying concealed weapons? You've got to have some breakfast. Could I squeeze you a persimmon or two? No, thanks. I'll grab a kumquat on my way to work. Hey, it's funny Walter Denton isn't here yet. He knows I wanted to get to school a little early this morning and meet the new principal. Rather convenient to have one of your pupils drive you around. Yes, my Chevy's still in the shop. I had a little accident Saturday. I ran into a parked car. Oh, that's too bad. I hope you reported it to the police. I didn't have to. They were sitting in the car. Oh, that's good. I'll get it. Oh, Miss Brooks. Come in, Walter. Well, Walter Denton, how have you shot up since I saw you last? You saw me yesterday, Mrs. Davis. My, how time flies. Come on, Walter, I've got to get down early. The new principal takes over today. What's his name, dear? Mr. Conklin, Osgood Conklin. Osgood Conklin? Well, I've known him for years. We went to school together. Really, Mrs. Davis? What kind of a man is he, anyway? Well, the other children used to call him Stoneface because he never laughed. Oh, fine. Well, I shouldn't say never. I did hand him a laugh one time when we were out ice skating. He was practically in hysterics. What happened? I broke my leg. He sounds about as friendly as a subpoena. Correct any nonsense of this new school, Martha. Or my name isn't Osgood Conklin. I've heard all about their lack of principal and discipline, and I won't have it. Do you hear? No one is going to interfere with my making Madison High a well-run school. No one. If anyone gets in my way, I'll crush them. Step on them like so many ants. Squash them. That's nice. Pass the marmalade, dear. And help yourself with some more toast.  As I was saying, Martha, I'm sure that the faculty at Madison High is totally incompetent.  Irk? Irk? Drink a little water, dear. It'll go away. No understanding, no cooperation.  It's awful. Awful. Please, Osgood, can't you talk without barking? Honestly, sometimes I think Prince is the only one who can really understand you. Prince?  Look at him over there. Dead to the world. Well, it's getting late. Now where's my hat? Confound it, where's my hat? Please, dear, don't bark. I'm not barking, Martha. Once and for all, I don't bark. I understand you. Now be sure to drive carefully on your way to school. Oh, don't tell me how to drive the car. I'm not, dear. It's just that after all the work you put in, polishing it on Sunday, I'd hate to see this. Stop worrying. I did the work, didn't I? Ah, look at her out there. Nothing takes a wax polish like a black touring car. Well, Osgood, you better get started. You don't want to set a bad example for your new teacher. I'll show them a thing or two. I'll show them. Ruff, ruff, ruff.  Goodbye, Martha. Before we get to school, Miss Brooks, there's something I'd like to talk to you about. It's a girl. Naturally. Who is it this time, Walter? Well, she's the baker's daughter, Penelope Miller. When I kissed her for the first time the other night, I knew she was different. But, Walter, you've kissed a lot of girls. What's so different about Penelope Miller? She tastes like caraway seeds. Oh, brand. She's probably built like a pumpernickel. Now, look, Walter, I've got a lot on my mind today, what with trying to make a good impression on the new principal. Well, all I want you to do is help me write her a letter, Miss Brooks.  I can't understand it. And I figured you being an English teacher, as well as a woman, well, you'd know how to make her think I was brainy. You know, intelligent.  You know what I mean?  Don't blame yourself. Penelope just doesn't appreciate yet that a man is the thing to be treasured. Well, will she appreciate it? When she gets to be my age. Oh, I couldn't wait that long, Miss Brooks. What? Well, I'm sorry, Miss Brooks. I guess I'm not very mental at that, but you will help me out, won't you? I'll come over to Mrs. Davis' tonight and we'll write a letter together. What do you say? Well, I don't know, Walter. Walter, look out. That car. What car?  Big black touring car? Not quite as big as it was. Why don't you watch where you're? My fenders. My shining fenders lying in the gutter. Walter, put the man's fenders back on. Oh gee, Mr. I didn't mean to... You didn't mean? Why didn't you look where you were going? Well, gosh, it takes two to make an accident. A brilliant observation. But it just happens that I was only going 15 miles an hour. You should have been going 30. We'd have missed you by a block. Now, see here you red-haired joy rider. It was probably your fault. My fault? Why don't you learn how to drive that hopped-up hearse of yours? Hopped-up hearse? Now listen here, young woman. I've tried to control my temper. But if you want to play rough, I can get plenty rough. Walter, I've got to run along. I'll leave you to straighten out barking boy. Barking boy? That's the second time today I've been accused of barking. Young woman, I'll have you know I do not bark. Who's your friend? Go home, Prince. No classes haven't started yet. Let me see. Pick up my mail first and then... Oh, hello, Mr. Boynton. Hello, Miss Brooks. Isn't it a coincidence that we're in the same mailbox? Not an overwhelming coincidence. You see, your last name begins with the same letter mine does. Well, that's a start. You have such a quick mind, Mr. Boynton. Well, it is thorough. Personally, I think you tax it too much. Don't you think you need more recreation if you know what I mean? Well, carrying on my biology experiments is recreation enough. You don't know what I mean. Of course I also collect stamps. Oh, that sounds exciting. There's no end to the possibilities. Have you ever tried your hand at beadwork? No, I don't believe I have. Is it fun? Fun? Why, it makes you just tingle all over. Well, we must string a few together sometime. And basket weaving can be thrilling, too. Really? Yes, if we're both in the same basket. So much for the world of sports. Miss Brooks, if you don't mind my changing the subject, are you going to be busy tonight? Busy? Me? Mr. Boynton, I couldn't be unbusier. Well, I'd like to come over after dinner, that is, if we can be alone. Alone will be absolutely isolated. I hope you don't think I'm too forward, Mr. Boynton, but I've anticipated this moment for quite a while. Remember the day about five years ago when I first came to Madison High, rounded a turn in the corridor, and bumped smack into you? Oh, yes, I was teaching chemistry then. You put quite a dent in my Bunsen burner. Yeah. Well, you know, that was the day I first suspected that we'd be more to each other than just fellow faculty members. And when were your suspicions confirmed, Miss Brooks? On our very next date, when you took me to lunch. Two years later. Gad, you were a fast worker. I don't blame you for kidding me, Miss Brooks. I guess I'm not much of a whirlwind romantically. Then most scientific people aren't. You see, the study of evolution alone tends to slow down any of the mere intemperate reflexes. You must realize that a tremendous period of time was involved before the single cell divided itself in the sea and adapted itself to the land and the air. Countless centuries passed before lower forms of life and new shapes and generations before the mammal family produced the ape family and before the ape family produced the human family. What have you been waiting for me to do? Slip back a notch? Well, what time do you think you'll be able to come over tonight, Mr. Bunsen? Mr. Bunsen, Miss Brooks, let us not tarry. Your new principal, Mr. Conklin, is due at any moment. Oh, we'll be sorry to see you go, Mr. Darwell. Yes, you've been a wonderful principal, Mr. Darwell. Why did the Board of Education decide to have you transferred? Ours not to reason why. Ours but to teach and dive. As the great Socrates so aptly phrased it, if you've got to go, you've got to go. Of course, I am genuinely sorry to leave all medicine high, but then, with teachers and teachers can't afford sentiment. We can't afford anything. As the great Professor Einstein so aptly phrased it, murder, ain't it? You know, I still hope I can land that job as head of the English department, don't I? Well, that will depend upon the impression you make on Mr. Conklin. I'm taking him on a tour of inspection as soon as he arrives, Miss Brooks. Your class will be the first one visited. Oh, the first class visited? Oh, gosh, Mr. Boynton, if I'm to impress Conklin, I'll have to hurry and get things in order. I'd better go in and erase the children and see that the blackboards aren't throwing spitballs.  You look sort of faint here. I'll put my arms around you until you study yourself. Oh, no, you won't, Mr. Boynton. Just because you happened to catch me at a weak moment, I'm not letting you put your arms around me. My father told me about men like you. And why are you putting your arms around me?  All right, now, class, please let me have your attention. As many of you know, our new principal, Mr. Osgood Conklin, takes over his duties today. So if he should drop in here at any time, there's no reason for any of us to be nervous, self-conscious, or head of the English department.  Now, to take up where we left off yesterday... Pardon me, Miss Brooks, but Mr. Conklin and I just happened to be passing by. Oh, I come right in, Mr. Darwell. This way, Mr. Conklin. Mr. Conklin, this is our Miss Brooks. How do you do, Miss Brooks? Glad to make your equatum in it. Oh, thanks, Mr. Conklin. Glad to make your equatum in it, too. Oh, you two have met. We sort of ran into each other this morning. Darwell, this is the young lady in the accident I told you about. Oh, Mr. Conklin, I have an idea. Why don't we skip English and drop in on the... Now that I know just who Miss Brooks is, I'm particularly interested in watching her conduct her class. Go right on, Miss Brooks. Well, all right, Mr. Conklin.   Well, I want you to tell me whom. No, who? I'd like the name of the author of the following stuff. It's Romans countrymen, lend me your ears. I come to bury Conklin, not to praise him. That is to bury Caesar. Hand, please. You've all got them, you know. Just look at the ends of your sleeves. Winona, I can always depend on Winona. Who wrote those lines, Winona? I don't know. I just want to leave the room. Never mind the blindfold, Captain. Just give me a cigarette. Come in, Miss Brooks. How is everything? Well, frankly, Mr. Boynton, I'm a little tired. I just lost two out of three falls to Mr. Conklin. You've met the new principal. What's he like? He looks like he was weaned on a vinegar popsicle. Mr. Boynton, I just dropped by to see what time you're coming over tonight. Tonight? Yes, one of my students is stopping by for a few minutes. I've promised to write an intellectual letter for him to a girlfriend he's trying to impress. Penelope Miller. Penelope Miller? Yes, she tastes like caraway seeds. If you could just let me know what time you're coming over. Well, I'm not sure about tonight at all right now. I'm quite worried about Violet. Violet? Yes, the white mouse I use in some of my experiments. Steady, Violet, dear. Steady, dear. I'm just going to hold you for a minute. Mr. Boynton, if you could just... You know, I don't like the feel of her stomach. Mr. Boynton... It's lumpy. Well, Mr. Boynton, you told me this morning... Well, frankly, Miss Brooks, at that time, I didn't know about Violet's condition. You understand. I have to... I know. You have to sit up with a lumpy mouse. Well, she's terribly peeked lately. I don't know what it is. I think I'd better have a look at her cage. Hold on a minute. Will you hear? Miss Brooks, you dropped! Just stop that screaming! And let go of your studs! And this, Mr. Compton, is our biology laboratory. Why, Miss Brooks, what are you doing on that desk? And where is Mr. Boynton? He's under the table with Violet. Violet? So that's what goes on in the biology laboratory of Madison High. Oh, but Mr. Conklin, I'm sure... So am I very sure. Come, Mr. Darwell, I'll be back when Violet is out from under the table. Oh... Got it, Miss Brooks. Poor thing was scared to death. Here. And look at her, isn't she sweet? Isn't Violet a beauty? She's ravishing. And may I tell you something else, Mr. Boynton? What's that? You make a lovely couple. Principal's office, Osgoode Conklin speaking. Who's calling, please? Mrs. Davis. Margaret Davis? Oh, yes, the girl I used to go ice skating with. How's your leg? Do you want me to come over to dinner? Well, I'm afraid I... Say there's a teacher living with you that you want me to meet. Miss Brooks. Well, I'd like... Miss Brooks! Now look here, Margaret. I've already met that redhead. Mr. Conklin. Hold the phone, Margaret. Yes? I'm Matilda Denton at the school board. I have reason to suspect that my boy, Walter, a pupil at this institution, has fallen into the clutches of one of your female teachers. What? Yes.  And here, this note fell out of his pocket when he came home from school. Let me read that, please. At last, I've got what I want. Red hair and a tough, sturdy body. Red hair. Good heavens! Well, Mr. Conklin, have you any idea who this nefarious woman might be? Yes, I have, Mrs. Denton. Pardon me. Hello, are you still there, Mrs. Davis? Well, I haven't been to a Turkish bath. No. No, I haven't been to a Turkish bath. Now listen, I have reconsidered. I shall be delighted to dine this evening with you and Miss Brooks. Mr. Conklin, I'll give you just 24 hours to find out who my boy is traipsing around with. Listen, Mrs. Denton! Listen, Mrs. Davis! You'll get to the bottom of this matter quickly, or there'll be a new principal here at Madison High. Quiet, both of you! Don't you bark at me! I'm not barking! Do you like your dinner? Very interesting, Mrs. Davis. I've never tasted this kind of meat before. Just what is it? It's our usual Monday night supper. Seal burgers. I dig these dishes into the kitchen and see about the coffee. I make Bulgarian coffee, you know. It's strained through a grapefruit rind. Now then, Miss Brooks, let's get right to the point, huh? What would you think of a teacher who would allow a student to become infatuated with her and then lead him on? I think she was pretty terrible, Mr. Conklin. Who's the teacher? Well, we haven't any positive proof, but the boy's name is Walter Denton. Well, I think they both ought to be arrest... Walter Denton? Yes, Miss Brooks. You can't deny that you were in the car with young Denton this morning. But he was just giving me a lift until my car is fixed. I never see the boy at any other time. Are you sure about that, Miss Brooks? Oh, I'm positive, Mr. Conklin. Must be my laundry. Your laundry at 8 p.m.? I deal with the owl laundry. They only come out at night. Excuse me, Mr. Conklin. I'll be back in a minute. All right, Miss Brooks. Hi, Miss Brooks. I keep you waiting. Yes, but not long enough. Look, Walter, would you come back some other time? Come on, let's get into the living room. No, Walter, no. I'm anxious to get that letter started. You're not so loud, Walter. Mr. Conklin is in the dining room. Oh, the new principal? Yes, and if he finds you here tonight, we'll both be out of here. Well, no, it's good. We'll have our coffee in the living room. I'm not great. Quick, Walter, hide. Get behind those curtains behind the window. Oh, yeah? Just a minute later. Get in back of them. Who was it that rang, dear? Oh, it was just a wrong number, Mrs. Davis. On the doorbell? I mean, the wrong house number. You seem quite nervous, dear. Oh, I'm all right. Come and get some coffee. It'll calm you down. Thank you. The Bulgarians drink it flat on their back, you know. I'll be flat on my back any minute, and I wish I was in Bulgaria.  Well, it is rather warm in here, don't you think? If it isn't too much trouble our good, would you mind pulling back those curtains and opening the window? Oh, no, not the curtains. No trouble at all. I'd be only too happy to open the window. And I'll be only too happy to jump out of it. There we are. Well, where is he? What's become of him? What's become of who? Bobby Breen. He used to send me. Come on over to the couch, Connie. You're still overwrought. Well, thank you. I'll lay right down here. Oh, no, thank you. I'll get you a pillow. You know, I keep pillows in the window seat just for emergencies. I always say you never know when you need them. By hello, Walter. Here you are, Miss Brooks. Just make yourself... Ow! Margaret, Margaret, what's the matter? Walter, get... Just as I thought. Miss Brooks, where are you going? I thought I'd run down to the Belgian Congo for the weekend. Sit down, Miss Brooks. Young man, what were you doing in that window seat? If you'll only give me a chance, Mr. Conklin, I can explain. Go ahead. What were you doing in there? Hiding. Walter, tell them just why you came here tonight. Well, I came here to see Miss Brooks. I thought we'd be alone. Oh-ho! Oh, no! I thought she was only going to help me write a letter to my girlfriend. I see. Now, let's hear you explain this, Miss Brooks. Here, read this page from Walter's diary. Mine? What is this? At last, I've got what I want. Red hair and what a tough, sturdy body. Walter! I wish everybody would stop saying Walter. Look, this isn't even my writing. Here, look at the other side. See, that's my biology notes from yesterday. I asked Mr. Boynton to loan me a piece of paper. Mr. Boynton wrote that? Miss Brooks, don't you get it? Get what? Red hair. It's you he's writing about. Mr. Boynton? Me? Just what he wanted? Tough and sturdy body. Well, I am strong. Surely you're not pleased, Miss Brooks. I'm not? I mean, I'm not. Oh, Mr. Boynton. Mr. Boynton. I thought you said we were going to be alone, Miss Brooks. You too. What's happening around here? Haven't you heard? I've been made queen for a day. Boynton, I'd like to know whether you wrote this or not. Let me see it, sir. Yes, I wrote it. I was supposed to go into my diary. What's wrong with it anyway? She is strong and I did work hard to get her.  It took 23 generations of crossbreeding to get a red-backed mouse like that. Red-backed mouse? Mouse? Amazing. Miss Brooks, I'm afraid I've done you a grave injustice. You most certainly have, Mr. Conklin. You've placed your own meaning on an unfortunate incident. But I... You've accused me of misconduct with no proof whatsoever, and you've acted in general like a narrow, bigoted, unfair person. But, Miss Brooks... Mr. Conklin, I never want to see or talk to you again as long as I live. Not even about the job as head of the English department? Mr. Conklin, I've done you a grave injustice. Let's sit down on the love seat and talk this thing over. Well, we'll take it up first thing in the morning, Miss Brooks. I've got to be getting home now. Come on, Walter, we'll take the bus together. Oh, we don't have to take the bus, Mr. Conklin. I've got my car outside. Your car? After our collision this morning? Oh, after I left you, I hit another car and everything snapped back into place. Well, good night, all. Good night, Walter. Good night, Mr. Conklin. Good night, Mr. Conklin. Well, now there's just the three of us, Mr. Boynton. Mrs. Davis and you and I. T, it's a beautiful night. Look at that moonlight streaming through the windows. If one would take a hint, there'd just be two of us. Two of us and one sofa. I said if one would take a hint, there'd just be two of us. Well, here we are, just the two of us. Good. How about a little gin rummy? Mrs. Davis three across, but I'd rather have lost to Mr. Boynton. He's certainly naive, my little biology boy. But though he's shy, he's glad of I, and I'm sure he'll soon realize that the greatest thing he'll ever learn is just to love and be loved in return. How often have you picked up a newspaper and read about an automobile accident? Chances are you think of accidents like that as always happening to someone else. If you could count on that, there'd be nothing for you to worry about, but chances are also that those very people you read about had the same feeling until something actually did happen to them. All it takes is that one brief moment of carelessness, but it can cause a lifetime of anguish. In almost every automobile accident, there are one or more violations of the law, yet those laws are made specifically for the purpose of preventing accidents. Our Miss Brooke, starring Eve Arden, is produced and directed by Larry Burns. The script was written by Al Lewis with music by Wilbur Hatch. Next week at the same time, Columbia Will Gunn presents another adventure in the far from grassed life of our Miss Brooke, starring Eve Arden. Bob Stephenson speaking. This is CBS, the Columbia Broadcasting System.


All right, let's give it a try. So welcome to this talk. Today, we're going to talk about data service design and how to scale data services. So why this talk? We've been automating data service for Cloud Foundry for now, I think, two or three years. And we've learned that it is a challenging task because there are so many possibilities. Also, something we've seen and observed is that early stage development is often very driven by feature demand. So it is very important to ship certain features to the customer. Of course, this is important. But also, we should think of software development in general comparable to driving a motorcycle. So driving a motorcycle, if you're not familiar with that, is challenging because you're not just sitting in the car and you drive around, but you have to know what's directly in front of you. There are stone. It could be the end of your journey. So you have to keep on looking into the next turn and then directly in front of your wheel again. And you'll keep on changing these two perspectives. So this talk is about how do you do that for software development? We would like to find some architectural bottlenecks and learn from them and see how we can improve them. So the mission is actually to find a way to develop Cloud Foundry data service that work at scale. So what do I mean with scale? I mean, we have people here in the audience representing big IoT platforms, for example. They are very likely to scale beyond a few service instances. So how are we going to do that? When looking at data service design, there is a vast space of possibilities. So there are many designs you can actually come up with. Design decisions include attributes such as what are you using as a service instance? Are you doing shared instances, serve from a cluster, or dedicated instances? What kind of resource types are you applying? VMs versus containers? Are you provisioning virtual machines on demand, or are you pre-provisioning them? How about your failover strategy? Do you want to have one replica of data or several? So depending on your particular requirements, there are a lot of design decisions to be made. And they have impact on the quality your service is going to offer. So for example, what is your desired time to repair? I've seen people talking about keep it simple. And data services, they should be no more complex than building a cluster is complex. So maybe we should keep it simple. But on the other hand, we have to deal with outages, hardware outages on regular basis. So we want to deal with them. We want to have minimum service impact. So you always have to make trade-offs when designing a data service regarding those quality attributes. So in order to think of scaling data services in general, we have to narrow down the discussion and be a little more concrete than that. Because otherwise, we'll just be lost in a vast space of opportunities. So I think when coming to that particular design and asking for scale, the definition of what a service instance is is the most important question. Are you going to serve this shared database from a single Postgres database, for example, as a service instance? Or is it going to be an entire Postgres cluster? So that actually makes up the nature of your service. Basically, it makes up the nature of your service. Also interesting is how many service instances are you going to operate in the long term? Is it only 10 or 100 or 200? Then basically, the challenge isn't very big. But if they look at what Heroku achieved, like with some of their services, Postgres, for example, the non-production Postgres, I think they have a million of service instances. So how do you do that? Also a challenging question is, how many concurrent users are using your platform? For example, if you have a fairly slow development pace where you ship new apps on a rather infrequent scale, then maybe the question of how many service instances you're creating at a certain time isn't very high. Where when everything is automated in your company and you're creating and destroying service instances automatically, you might have a different requirement for parallel service broker operations. So looking at scale, I think it makes sense to think about common data service design patterns and look at their architectural scale. And within a 20-minute talk, sadly, it's not possible to cover all the ifs and thens. So I see Dr. Nick here. We cover something you do with Dingo Tiles. So you're free to interrupt me after. So I see it coming. So three major design patterns we've recognized so far is the shared cluster. So basically, a virtual machine or a cluster of virtual machines split up into some kind of data service specific instances, such as databases, dedicated containers, and dedicated virtual machines. So when you look at their scalability capabilities, looking at a shared cluster is like the following. You have a set of virtual machines. Most likely, they are distributed across several availability zones. Why are there three of them? So in order to cover the outage of an availability zone, you still want to be able to provide a quorum by having two nodes being left in the cluster so that they can agree upon a new master, for example. So you have those three virtual machines. And you will slice up those virtual machines into different service instances, serving the databases as a service instance. So while this approach is fairly simple to do, all you have to do is wrap your MongoDB cluster in a Bosch release and write a service broker creating databases. It's also very cost-effective. So because what's the overhead for a service instance? Barely nothing. But at some point, your cluster will be full. And also having a threshold for when a cluster is full is hard because it's not the number of service instances that make up the utilization of that cluster, but it's what you do with those service instances. And so while this has a very low cost per service instance, and apparently a simple service broker logic, of course all you have to do is create a database when a new service instance is requested, or a database user when a new service binding is requested, you have pretty weak isolation because most of the data services, well, if they come with multi-tenancy capabilities at all, they are limited in doing that. Sometimes you are able to see the database names of other customers or even the database scheme of other customers. And sometimes there is no multi-tenancy capability at all. So beside of the weak isolation coming with a shared cluster approach, you also have the problem that the basic architecture cannot be taken as a common way to approach every data service. It's not a generic thing, and especially when designing a framework for integrating a large number of data services, that is a particular bad approach. Also it comes with the structural limitation that once your cluster is full, you have to somehow answer the question on how to scale out. So one of the obvious options would be to just have a second cluster and fill the second cluster with instances. And while this surely can be done, it also causes your simple service broker logic to become more complex. Because you have to deal with challenges such as fragmentation. So after a while, database instances are created and delete, and you have a fragmented cluster. So in this case, you can see cluster two is not really utilized, but it still consumes all the infrastructure resources taken by the virtual machines. So you end up having a placement problem where you have to decide on where to put a new service instance, and which causes the desire to have a strategy for cluster rebalancing. So if that scenario gets worse, the second cluster is basically not needed. So you wanna have something that rebalances those service instances transparently so you can tear down the cluster and free the infrastructure resources. This is all doable. It's possible and maybe in the future that's the way to go if combined with the proper context. However, it feels somehow like what Cloud Foundry does for service instance for application instances already, like you have this placement problem and so on. So yes, looking at the conclusions from this is you come up with two major challenges. First, you have a scalability issue. So with a little more complexity in the service broker, you can address that. But the isolation issues you are ending up with, they don't allow for a generic solution. So one way to get around that, especially if you wanna have cheap service instances, is using containers as they come with very little overhead compared to para-virtualized or fully-virtualized virtual machines. You have a better startup time and still you have a better isolation. So what you can do, for example, is again provide two hosts and this time virtual machines are equipped as Docker hosts and whenever you create a service instance, you create either a single container or a pair of containers. So in this scenario, we are using a clustered container solution. So you have to introduce the complexity of having a replication. So yeah, you have to create containers and you have to equip the containers with appropriate configured replication. So two process processes are actually running and you have replication going on, so good thing. So a new service instance is created, you just create a new pair of containers. So while this is a good approach and it's much better than a shared cluster because it has isolation and it also is pretty generic, all you have to provide is an automation to spin up a data service instance, but once you've done that, you can basically translate that to a lot of different data service types. So it's already a smarter solution. So but you also run into the same problem because at some point the cluster is full and you need more of those Docker hosts. So the same structural limitation applies. You have to answer the question, what to do when the cluster is full? So you also have the same service broker challenge. So of course you can just add new virtual machines and use them to create more service instances. So with that being said, problem is what happens if your clusters fall in the middle of the night and you have customers from a different time zone and they wanna create new service instances, but they can't. So that's something I as a platform user wouldn't like to happen. So I think that in the long run, the on-demand provisioning is somehow avoidable. So if we go down that road and look, how can we actually delegate all this complexity of the placement problem as well as the isolation, as well as the challenge of orchestrating the creation of several virtual machines? We can have a look at the third common data service design pattern which is about the on-demand creation of dedicated service instances, which could be single virtual machines, but also clusters of varying sizes. So in that scenario, comparable to the shared cluster, what we have is a set of three virtual machines. In this example, comprising a MongoDB replica set spread across three availability zones of your infrastructure. You're not using that database to carve it up into different service instances, but you take it as a service instance. So facing an organization with production requirements towards data services, most likely they either have DBAs running around in their company, already applying some automation magic with Chef or Puppet or whatever automation technology they use, so our solution needs to compete with them. Positioning would be around, let's automate the 80 to 90% average use case of the company by allowing you to create on-demand different clusters of MongoDB here or Postgres or whatever data service you prefer, either a single virtual machines, as you can see in the lower right, or as clusters of virtual machines. And of course, according to the Choose and Service plan, different sizes of virtual machines. A good thing and a very strong isolation you get is you get the isolation that comes with parallel or full virtualization, which is a little more resilient than the container-based isolation, comes with more overhead, but also has certain advantages. So the question could rise and how can this be a simple solution? And the answer to that is we have to delegate the heavy lifting, because there's a lot of complexity in how to orchestrate the creation of a large number of clusters where each cluster has a certain complexity. So a possible architecture for such an approach has already been built. Pivotal is working on something like that, and we've done that two years ago. So in that case, you have a pretty generic service broker that has a data service specific plugin called the SPI whose responsibility is mainly managing the creation of credentials and everything that's service specific, talking to a deployment component that actually manages Bosch deployments. So what it does is it chooses, it picks by the given service plan you have a certain Bosch release and creates a manifest file from it. So basically you say, I wanna have a single server, small or you wanna have a cluster, large. So the Bosch release has all the magic in it that covers the replication of a MongoDB cluster Postgres is more of a challenge because you have to add a cluster manager. So that will be all we in the Bosch release. So with that approach, all you have to do to create a new data service is you have to create an SPI. So how to create a credential for a newly created cluster during a service binding, for example, as well as creating a proper Bosch release. All the complexity then is handled by Bosch. I mean, Bosch has been built to create and run and maintain life cycle of large complex distributed systems. So let Bosch do the dirty work. So with Bosch taking care of virtual machine orchestration, we can actually use the infrastructure to solve problems such as placement and fragmentation because whether a virtual machine hose is fully utilized or has free spare. I mean, that's a problem we've solved many years ago. So what are the remaining challenges? Because we wanted to create 1,000 service instances. Think of 1,000 service instances being clustered. You end up having 3,000 virtual machines. So there are some challenges here. How to get there? The most naive approach would be that we are going to spin up 1,000 service instances and just see what happens. But that's way too expensive for a small company like us. We've just 50 people thinking about cloud-friendly stuff. So we are not a pivotal company. It just takes the resource. And I don't think it's meaningful because before you actually do that experiment, you have to prepare yourself in how to do that. Personally, I'm a lean, I'm a fan of lean management and also a fan of the lean startup. It's a paradigm. So what we actually do is we wanna create a build, measure, learn loop to enter a process of learning as an organization because there are certain things we don't know about the environment we are operating in. So there are many small and little question that tease us all the time because we are unsure how a system might behave in one or the other scenario. So the goal is to find a product market fit. And this translates to our scenario as we've been using our existing MongoDB, which by the way has been released for PCF today. And what we wanna end up having is a MongoDB that supports more than a thousand service instances. So how do we get there? The next questions we have to answer is what do we actually need to measure and what can we learn? So applying this paradigm, obviously, answering those questions is key. So we ended up searching for hypotheses of potential bottlenecks, which can be answered by just looking at the dependency tree of the architecture. So you can derive some of these potential bottlenecks and obviously each of our component could be a bottleneck or Bosch itself could be a bottleneck as the creation of virtual machines is handled by Bosch. So if you know Bosch a little more into detail, you know that it runs on one or several virtual machines, so the director could be overloaded in CPU or IO weight or whatever. There could be not enough workers so that you have a queuing of Bosch tasks or maybe at some point with thousands of virtual machines, the heartbeats coming from those virtual machines could actually outgrow the capacity of your NATS message bus. And the creation of virtual machines is also a heavy task to be executed by your infrastructure. So at some point, depending on the size of your infrastructure, you might upend up trouble with it. So now there's a customer and the customer needs to implement a certain solution, you know, promise to their customers. They need a proper runtime, a proper data service solution on their infrastructure. Do we already know when those things cause trouble? No, we don't. And therefore we define experiments to find out how the system behaves when we scale out. So in order to do that, we have to think about what are the quality attributes we would like to expect. And arbitrarily, from just, you know, observing our own patients, we came up with something that's about three minutes. I would like to have a new service instance being created on demand in around three minutes. Fair enough, if there's, you know, a lot of concurrent users, I might wait up to let's say nine minutes, but after nine minutes should be done on average. So it's obvious that the question of how many data services are there going to be in total, somehow influences or is influenced by the scale of my data service architecture. And also the number of concurrent creations of service instances or update or destroying them is determined by the system scale. So not by the architecture, but just by how many Bosch workers I have, how big my Bosch is. So in order to have an experiment and looking into that systematically, we have to identify relevant metrics and locks. One of the most important things, of course, because we rely on Bosch is the execution time of Bosch tasks in all its variations. So similar to a Kanban board, you can defer, differentiate the lead time and the cycle time. So the lead time would be, I wanna create a service instance. Let's assume a single server instance for, purpose of simplicity. So it ends up having a Bosch task creating this virtual machine. So how long does it take from service create until it's done? Because when doing multiple of those create operations at the same time, you might have a queuing in Bosch. So the cycle time, the time a Bosch task is executed will defer from the overall time of creating the service instance. And also, of course, the difference of that would be the wait time, the task just sit in the queue and wait until some worker has time to execute it. And in order to learn about potential bottlenecks around that, and maybe also because to learn why a certain Bosch task took so long, we also need system metrics from all VMs and components participating here. So gathering them required us to co-locate our lock stage on all the VMs and scripting the Bosch CLI to take relevant timestamps. So feature requests to the Bosch team would be very nice to have a more easy approach to collect this data. So scripting Bosch is a big thing, I guess, and it would be nice to have metrics from Bosch. Maybe there is a way to do that, but in the preparation of this talk and yeah, it could be, would be possible way. Yeah, I would love to talk about that later on. It's an interesting topic. So however, we definitely have to gather this information. So now our experiment looks like this. So we have the product, we have the metrics, and we have theories, so hypotheses around what bottlenecks may occur. So what are the influencing factors because this doesn't exist in a vacuum, but it is executed against a certain deployment of your data service on a certain infrastructure. So looking at the architecture again, you see there's a service broker, there's a deployer, there's a Bosch. It's a little simplified. There are a few more components, but for a creating service instance, that's mainly the components that are hit. So the scale of these components is important. Scale of your Bosch and scale of your infrastructure. So obviously it's a difference whether you have three workers or 10 workers or just more of them. What we are aiming at is finding out a scale out formula as a rule of thumb formula. And it's not a precise science here, but I would like to be able to tell a client to say, well, this is the scale and it's suitable for that many service instances. And you can create 10 of them at the same time and they all will be done in that amount of time. So find a system scale that matches a certain SLA. So we did some experiments. I'll go through three of them before coming to a conclusion. We did the first experiment on our in-house vSphere. It's a fairly small one, around 700 gigs of RAM, which is just a half a dozen physical machines, I guess. So when we started with a very small deployment, so with a small Bosch, three workers. And what we can see is that the creation of a single virtual machine when having one concurrent create service happening in parallel, that we are done in two and a half minutes, which passes our quality attribute. With 10 being created in parallel, we can see that the actual execution time of the Bosch task is already increased to three minute and 20 and that it takes six minutes in total. With 25, you wait up to 17 minutes on the creation of a single service instance on average, which is way beyond what we actually desire. So the outcome of that iteration was that we actually have the ability to create 10 service instances at the same time if you're willing to wait up to seven minutes on average. On average here means we had values between five and nine minutes. We also confirmed the assumptions that the utilization of our core components is barely nothing, so they are not going to be a bottleneck in the near future. And that scaling Bosch is the dominant factor. Obviously, we started with a very small Bosch deployment, so that was natural to happen. So the conclusion was we adjust the scale of Bosch for the next iteration. Still on vSphere, we just scaled the number of Bosch workers, assuming that the queuing time would be reduced, but what we've actually seen was that what we've seen is that the execution time heavily varied. You can see that the actual execution of a Bosch task, the creation of a VM suddenly took like eight minutes, and that was unexpected, because it clearly tells you that there's something happening on the infrastructure level that caused the VM creation to be delayed like that. And as you can see and as expected, the overall creation time goes a little down. So you are faster in creating those 25 instances on average. So the outcome was that there's a large derivation on the completion of the tasks caused by the infrastructure. We had learned that even a small infrastructure can be an influencing factor when creating service instances in parallel pretty early. So the conclusion was to see where the limits of the architecture are, we are going to move that to Amazon and see how that changes, because we've been sure that it's really the infrastructure that causes those delays. So the same experiment with, like in iteration two, we performed it on AWS, and we've seen that the creation of a virtual machine, the execution of a Bosch time, it's pretty constant. They are somehow equipped to do that. And you can also see that the average time for the entire creation of 25 instances on average just goes up to five minutes when creating 25 in parallel, which means that there's barely no queuing time for Bosch. So that would be okay, that scale would be okay. If you would like to create 25 service instances in parallel and wait around whatever, seven minutes to create a service instance, observed, we can see that AWS is more stable when it comes to dealing with more load, obviously. And also that small infrastructures may become a limiting factor. So if you expect to create a lot of service instance, for example, as part of your CI pipeline and you want to deploy them on demand, you definitely have to take care of your infrastructure as well. So yes, that is the SLA we came up with. And the next experiments we are going to make is we'll stepwise increase Bosch, increase the number of parallel instances to be created and see how is the relation between those two because we want to come up with this formula to scale out Bosch depending on the number of service instances you want to be able to run. Conclusion from our experiments was that, sadly, it took longer than expected because I actually planned to show you how to create a thousand service instances. But we are pretty positive that the architecture we've chosen is solid to do that because we haven't had any architectural bottlenecks hit so far. And we also learned that the number of simultaneously service broker operations is the first thing we should look at. It's not the total number, it's the number of service broker operations happening in parallel that should care us more.  So this scale out formula should somehow have a balance between your infrastructure resources, your runtime, your Bosch, your data services. So we think that the ground work here is done and we will keep on doing these experiments and stay tuned. We are going to block and post about that because I think that's a valuable contribution to the entire Cloud Foundry community. So thank you for your attention and feel free to ask questions.


The Jack Benny program, transcribed and presented by Lucky Strike. You know, friends, nothing, no nothing beats better taste. And remember... Lucky's taste better. Cleaner, fresher, smoother. Lucky's taste better. Cleaner, fresher, smoother. For Lucky Strike means, lime tobacco, richer tasting, lime tobacco. Lucky's taste better. Cleaner, fresher, smoother. Lucky Strike! Lucky Strike! Which cigarette is the right one for you? That's easy. The one that tastes better. Because a better tasting cigarette will give you more enjoyment. That's right. Nothing, no nothing beats better taste. And Lucky's taste better. Cleaner and fresher and smoother. Here's why. First of all, Lucky's are made of fine, light, really mild tobacco. Yes, L-S-M-F-T, Lucky Strike means fine tobacco. Then too, Lucky's are made better to taste better. Made round and firm and fully packed to draw freely and smoke evenly. Made to give you a cleaner, fresher, smoother tasting smoke. So friends, for the one thing you want most in a cigarette, for the better taste that brings greater smoking enjoyment, be happy. Go Lucky. Make your next carton, Lucky Strike. Lucky's taste better. Cleaner, fresher, smoother. Lucky Strike! Lucky Strike! Regent Haaland Palm Springs, California. The Lucky Strike program starring Jack Benny. With Mary Libby's... Ladies and gentlemen, I bring you a man who after one week in Palm Springs has become a picture of health. He was on the golf course Tuesday, Wednesday, Thursday and Friday looking for the ball he lost on Monday. Thank you, thank you. Hello again, this is Jack Benny talking. And now, ladies and gentlemen, since this is our second week... Wait a minute, Jack, wait a minute. Jack, did you really lose a golf ball? Certainly, Don. I even asked you to help me look for it all over the desert. And now, ladies and gentlemen, since this is our second week... Oh, Jack, Jack, something tells me you tricked me. I tricked you? Yes. As we were coming past Roger's table, you said, Don, you'll never find the ball that way. Stoop over. I did, you threw a saddle on me and for the rest of the day tried to rent me out for a dollar and a quarter an hour. He found out. I thought I was being subtle too, you know. I can't... Oh, hello, Mary. Hello, Jack. Hello, everybody. Mary, why didn't you show up for rehearsal this morning? Well, if you must know, for one thing, I was busy moving out of that hotel where you're living. But, Mary, I've stayed in that hotel for the last two weeks. It may be small and crowded, but it's a lovely place. Some lovely place. This morning, a guest ball me off for using the roller towel. Why? He was sleeping in it. The height of the season, people have to sleep where they can. As a matter of fact, I happened to know that last night, some people had to sleep in the police station. Jack, that was the orchestra, and the height of the season had nothing to do with it. Say, Mary, you're kidding about the orchestra being arrested, aren't you? No, I'm not, Don. Well, for heaven's sakes, what'd they do? I don't know about the others, but the police found Remley lying against the curb, and he hadn't put a penny in the parking meter. Mary, stop making up jokes. Now, you know the boys in the back... Oh, hello, Bob. Hiya, Jack. Hello, Mary. Are you still enjoying yourself here in Palm Springs? Oh, uh, pretty good. What do you mean, pretty good? You're living at one of the swankiest places in town, the El Mirador. Well, that's right, Bob. And you know, during the war, the El Mirador was a hospital, but it isn't anymore. Well, I wish someone would tell the waiters. Why? Well, last night, I ordered borscht. Borscht? Well, didn't it taste good? Who knows? They laid me on the table and shot it in my arm. You're kidding. Kiddin', look at this muscle. It's a potato. Well, how do you like that? Then for dessert, they gave me an anesthetic. Well, Bob, that had nothing to do with the dinner. Everybody who lives at the El Mirador gets an anesthetic. Yeah, but why? That way, they can give you the bill and you won't come too to go through banning. That explains a lot of things. Yeah, it really explains a lot of things. Yeah. Like what? Well, when I drove up to the place a bellboy came out, carried in my wallet and left my bags in the drive-in. Sorry I took your line, then, Bob. Anything happened when you do that. I take his lines, he takes somebody else's. That's because we don't rehearse, you know. Well, anyway, at the El Mirador is really one of the nicest. Come in. Telegram for Mr. Jack Bunny. I'll take it, boy. Here you are. Oh, just a minute, boy. Have you got change for a $5 bill? Change for a five? I think so. Good, good. Here's the $5 bill. Here's your change. One, two, three, four, five. Okay, boy. You can go now. Thank you, Mr. Bunny. Thank you. This is my lucky day. Uh, wait a minute, boy. What do you mean this is your lucky day? Mr.  What are you so happy about? When you do business with him and break even, it ain't bad. Who's the telegram from? Just a minute, I'll see. Hmm, it's from Dennis Day. Says, sorry I can't be on the program today, so I'm sending a substitute singer to take my place. The reason I'm missing the program is because I'm eloping with Marilyn Monroe. However, I'm silly enough to be back with you next week.  It's six cents a word. It's ridiculous. Say, Jack, why did he say he's sending over a substitute? I can sing. Why, certainly, Bob, that's exactly what you're going to do.  Now, who can that be? Come in. Well, Bing. Just call me substitute. Bing, I'm surprised. Actually amazed that you're the one that's taking Dennis's place today. Why, Jack, what's so amazing about that?  Wait, wait a minute, Jack. Dennis isn't paying me anything. The kid and I worked out an exchange deal. An exchange? I do a guest shot for him today, and he caddies for me tomorrow. Well, Bing, I don't like to cast aspersions on your business ability, but I think Dennis got the best of you on the deal. No, he didn't. Jack, you see, tomorrow I'm playing a match with Ben Hogan at $100 a hole. Wait a minute, you can't beat Ben Hogan. He's the best golfer in the country. That's what I want with Dennis. He'll drive Hogan nuts. Oh, oh, oh! There's some writing. I got three holes in there. It's a little redundant. You know, uh, you know my whole gang, don't you? Oh, yes. Hi, fellas, and... Hello, Mary. Hello, Bing. Well, I guess I know everybody except, uh, who's the fella standing over there? I'm your brother. I didn't recognize you. How are you, Robert? I'm fine, Bing, because I haven't seen you for months. In fact, not since I started working on Jack's program. See, no wonder I didn't recognize you, kid. You got a lot thinner. Wait a minute, Bing. If Bob lost any weight, it's not Jack's fault. Certainly not. Bob's working for peanuts and peanuts are fattening. Thank you, Mary. You know, Bing, it's quite a coincidence having you on the program. Only three weeks ago we had your sidekick, Bob Hope, as a guest star. Oh, really? How was old Sickle Snoot? Sickle Snoot? Why do you call Hope that? Well, his nose looks like a bagel with one bite out of it, I think. You think that's me? It does. You know it does at that. Say, Bing, you and Bob Hope have made an awful lot of pictures together, haven't you? Yes, and don't hit that word awful so hard, but it just kind of glossed that out. Anyway, Beagle Beak is a little mad about it now because you know, in every picture we make, I get the girl. Oh, is that what makes him mad? For heaven's sakes, Bing, with everything else you have, why are you so interested in money? Believe me, you can't take it with you.  What are you doing down here in Palm Springs? I've been doing some broadcasts, Mary, and I've been writing my autobiography. No kidding. Yeah, finally finished all the writing. I've titled it, Call Me Lucky. Say, Bing, the story of your life must be very interesting. Tell me about it. Well, I was born in Tacoma, Washington, and, oh, I tell you about it. Jack, you can read it in the Saturday evening post. Oh, yes, the Saturday evening post. Sure. That's only 15 cents. Comes in eight installments. Oh, well, tell me about it. Well, Jack, this thing starts in the February 14th edition of the Saturday evening post, and you can read it there. I know, but I want to hear the whole story at once. I don't want to wait eight weeks. Well, all right.  See, this is 1953. 14 from 1953. Hmm. That would make you 39. Bing, you can't be 39. What's the matter? You got a patent to do something? No, it's just that, uh, that, uh... That finder's keeper. It is not. Look, Bing, do you have a copy of your autobiography with you? Yeah, got it all right here, just as it appears in the post. Well, look, I'll tell you what. Suppose I read the story while you sing your song. Well, what makes you think he'll sing a song? What makes you think I won't? Your heart and let the love shine through Open up your heart and make my dreams come true Why do you just hide behind it, loosen up the chains that bind it Open up your heart and let me in Baby, I've been mighty lonesome Baby, I've been mighty blue And the reason for it all is plain to see Every first day I met you, you've been walking in all my dreams It's time you gave a little thought to me The sunshine and the pelican loves the sea And the meadowlike loves to sing his happy song Not one of them gets his lonesome As a love-sick bird like me And it's all because my chick had it done me wrong Why don't you open up your heart And let the love shine through Open up your heart and make my dreams come true Throw away the key that fits the telemind The one that gets it, open up your heart and let me in Open up your heart and let me in That was wonderful, and I just read your autobiography and it's really interesting Say, Jack, I've got an idea What, Mary? Well, since we've got Bing with us, why don't we dramatize his life story? Say, that is a good idea.  Don't worry, we'll work it out. Eight installments And now, ladies and gentlemen, a special preview of the life of Bing Crosby As it appears in the Saturday evening post Hello? I have a long distance call from Mr. Jack Benny This is Jack Benny speaking. I'll take the call It's collect Collect? Look, Operator, I'm not taking any collect call Just a moment I'm sorry, Mr. Paley, but Mr. Benny said he isn't Jack Benny Mr. Paley? Oh my goodness, Operator, certainly I'll take the call Very well, Mr. Benny, go ahead Hello? Hello, Mr. Benny, this is Rochester Why? Rochester, you tricked me I had to, boss, I'm in the garage in San Bernardino and I haven't got any money The garage? Something wrong with my car again? Rochester, answer me, is there something wrong with my car? Just a minute, boss, this is such a long story, I wrote it down Never mind that, just tell me what happened Well, I was on my way down to Palm Springs to pick you up Uh-huh And as I was coming through Cucamonga, I was driving along the railroad tracks When suddenly I noticed the super chief was trying to pass me Trying to pass you? I accepted the challenge, but for the next 22 miles we were side by side Rochester, how could you keep up with the super chief?  Boss, if you see four flying saucers with hookcaps, they're yours That's terrible, Rochester, are you hurt? No, I was protected by the ironing Rochester, you had the ironing board in the car, why? If you found out I was just sitting there driving, you'd be awful mad I would not, anyway, before you leave the garage, find out how much it'll cost to fix my car Oh, I already do, fellas, look at it and they each gave me an estimate The first said $17.50 and the second fellow wanted $800 Well, that's quite a difference $800 out of the question for fixing up my car What'll the fellow do for $17.50? There it is Rochester, you didn't really have a wreck, did you? Well, of course Then why did you make up such a story? Well, I knew I'd be late getting down to Palm Springs So when I started to make up an excuse and it got away from me Well, that's ridiculous No, it isn't, I sold you a sad evening post in Hayden Starman All right, goodbye Goodbye, oh, say, boss Now what? The director of your television show called and he's already hired 700 dancing girls for your TV show next Sunday Rochester, I'm not having 700 dancing girls on my television show next Sunday Boss, you know that and I know that, but let's lure the listeners Oh, yes, thank you, Rochester, goodbye And now, ladies and gentlemen, we present our dramatization of the Saturday evening post autobiography of Bing Crosby Call Me Lucky, Curtain Music 2014, it says here The newborn baby was called Harry Lillis Crosby Harry Lillis was a precocious baby and learned to speak quite young At the age of three months, he said Da Months, he said Da, da, da And at six months Da, da, da, da, da, da, da, da, da, da, da Child of school age and he was a good pupil And a clever one, too While other kids brought the teacher apples, he brought her minute-maid orange shoes When he received the nickname he made famous,港 because his family lived next to a cherry orchard And he was very fond of Bing Chariots Fortunately, he didn't live next to an orange grove, or today he might be known as Naval Crossbowl. Another blessed event took place in the Crosby home. The newcomer joined brothers Bing, Larry, Ted, and Everett, and he was named Robert. Bing took care of little Robert and tried to teach him to talk. Come on, Bobby. Say mama. Dog. Come on, Bob. Say mama. Dog. No, mama. Say mama. Mama. Shepherd of this. Brother Crosby thought Bing was old enough to have responsibilities, so she decided to give him an allowance of a dollar a week. When it came time for him to receive his first dollar, Bing said, Mother, may I have my allowance? Well, certainly, son. Here it is. Oh, but, Mother, I'm supposed to get a dollar allowance. How come you only gave me 90 cents? Brother Everett gets 10%. Today on his weighted class, he ran into his best friend, Robert Leslie Hope. Hope suggested they play hooky, which they did. They went down to the corner fruit store and swiped apples, and they went around tipping over ash cans and breaking windows. This was the start of their first picture, the road to reform school. Bob shared the same room at Gonzaga University. They shared everything. They even took their Saturday night baths together, and they enjoyed it because it gave them a chance to harmonize. Are the dustiest, the winds are the gustiest, the gates are the rustiest, the pies the crustiest, the songs the lustiest, the folks the trustiest, way back home. The trees are the sappiest, the days are the nappiest, the dogs are the happiest, the kids the scrappiest, the jokes the snappiest, the folks the happiest, way back home. I don't know why I left the homestead. We crossbiz had such fun. Yeah, but Bing, we drove the neighbors crazy, they had to move. Yes, one by one. Bob was the littlest, Sister Kay the prettiest, Larry was the dumpiest, Mary Rose the plumpiest, Bing's clothes the dingiest, Everett the stingiest, way back home. Let's light a lucky strike, that's sure a smoke I like. My folks are tearing them, and they're comparing them. Yes, it's a favorite smoke, of all the smartest folk, way back home. A lucky is round and firm, that's more than just a turn, it's made of fine tobacco, there's 20 in the pack, no pups is ever rough, it's luckies we all puff, way back home. Lucky strikes are better tasting, and there are no loose ends. That's why boy greased the sponsor, this is my butter and eggs, my grain of pressure smooth as smoke, you'll be proud to give your friend. We folks are the happiest, my brothers are the snappiest, Everett the daffiest, Bob is the pappiest. We're happier than two, and I'll come back with you, way. The mission was to become a singer, with an audition in Los Angeles. Your name is Harry Lewis Crosby. Yes sir, but most people call me Bing. Tell me, have you made any phonograph records? Yes sir, I've made lots of records, I've made them for a company owned by Rudy Valley, but I think he's jealous of me. How can you say Rudy was jealous, he let you make the records, didn't he? Like you, I'm going to give you a chance. Here, learn this song, and tomorrow night, you'll sing on a coast-to-coast radio network. And the following night, for the first time in history, the rich baritone voice of Bing Crosby was heard as he sang. Crunchy munchies hit the spot from the cannon, they are shot, they will become your favorite dish, they are better than cavill, are they? Way to success, and with fame and wealth, his interests became diversified. One day he witnessed the following scene. I'll buy that race horse. That's a very good horse you're buying, Mr. Crosby. Why, but tell me, what does he go the mile in? Well, I don't know, he never quite made it. Look, Mr. Crosby, your horse can win its first race if you tell the jockey that's riding it to holla giddy app and throw this little electrical switch on the saddle. Oh, is there a battery under there? No, it turns on his hearing aid. Hello, horses, he had gone into pictures. His movie career was always successful, but it became more so because of three brilliant decisions. He made going my way, he made bells of St. Mary's, and he turned down the horn blows at midnight. He stood zenith on a night in March in 1945 when he won the Academy Award. His acceptance speech was quite modest, as he said. I want to thank everyone who helped me win this Oscar. Even though I have supposedly reached the top as a singer, I want you to know that it's not been easy. I've had to overcome many hardships, poverty, disease, hunger, Cuomo and Sinatra. Television, movies, radio, frozen food, inventions, cattle, and oil wells. Yes, the world was his. And I wish he'd give it back already. This is Bing's true story. We'll be back in a moment, but first, nothing. No, nothing beats better taste. And remember...  For in a cigarette, nothing. No, nothing beats better taste. And LUCKY'S TASTE BETTER CLEANER, FRESHER, SMOOTHER You see, LUCKY'S BETTER TASTE really begins with the fine, light, truly mild tobacco that goes into every single LUCKY STRIKE. S-L-S-M-F-T LUCKY'S STRIKE MEANS FINE TABACCO. Good tasting tobacco, of course. Then too, LUCKY'S also taste better because they're made better to give you a cleaner, fresher, smoother tasting smoke. So friends, remember how important better taste is to your enjoyment of a cigarette and remember that LUCKY STRIKE gives you the better taste of fine tobacco in a better made cigarette. But most of all, remember to pick up a carton of LUCKY'S tomorrow. Yes, be happy. Go LUCKY. BE HAPPY GO LUCKY GET BETTER TASTE TODAY I want to thank you very much for taking Dennis Day's place on the program. I was glad to do it, Jack. Tell me, Bing, is Dennis really going to caddy for you when you play golf with Ben Hogan tomorrow? That's right. And you and Ben are playing for $100 a hole? Mm-hmm. Well, do you mind if I join you?  What makes you think you'd win? I can't lose. I'm going to caddy for Hogan. Oh. It's written by Sam Parran, Milt Joseph Burke, George Balzer, John Packaberry, and produced and transcribed by Hilliard Mars. Be sure to hear The American Way with Horace Hyte for LUCKY STRIKE every Thursday over this same station. Consult your newspaper for the time. Jack Benny Program is brought to you by LUCKY STRIKE, product of the American Tobacco Company, America's leading manufacturer of cigarettes. This is the CBS Radio Network.