Hi everyone! Today's story is the Everything Seed, a story of beginnings. I hope you enjoy the artwork as much as the story. Have you ever watched a seed grow? Have you ever noticed how it begins so small, so still, so quiet, like a gift wanting to be opened and how slowly it wakes up? It begins to unfold, growing into something larger and larger and larger. Then you know that whatever comes from a seed usually ends up looking very little like the seed it came from, which is also true of the very first seed. Once long, long ago, way back before the beginning, so long ago there was no such thing as time because there was no one there, no one there to count it. Everywhere was a huge, deep, mysterious place, like something waiting to happen. There were no stars, no sun, no moon. There was no place like Earth, not a drop of water or a single tree or a rock or a flower and no living beings anywhere. But in that deep, waiting space was hidden the tiniest point of something no bigger than a seed. It was not a flower seed. It was not an elm tree seed. It was not a seed of corn, although all of those things were included in the seed, we call it, and everything's seed because that is what it became. No one knows where that first seed came from or how it was planted or how it knew in the way that only seeds seem to know. How long to wait for just the right moment to sprout and grow. But all at once this tiny seed cradled and nourished in the rich soil of space woke up, broke open, and began to unfold, unfolding, unfolding in blossoming forests into an enormous blazing ball of bright light, like a great grandmother's sun, and the universe was born. Hope fluttered the galaxies like a storm of snowflakes swirling and gathering into the brightest, most blindingly beautiful cloud of star, and out of those star clouds world our own star, the one we call the sun and our earth and the moon. And all the round spinning planets we have learned how to name. And this is the secret of that tiny seed.  We were there with all the stars and planets, all the rocks and oceans, plants and animals and people. Everything that is now, ever was, or ever will be, was inside that first tiny seed. So whenever you hold a seed in your hand and wonder what it could become, imagine how you and all that is here once came from the tiniest speck of an everything seed before it sprouted and grew long, long ago in the way back beginning of time. Now if this were an ordinary story, it would end right there. But this story of the universe keeps unfolding. What once began in a blazing blossom of light continues every day. New stars sprout open in the deepest soil of space, new plants and animals appear on the earth, seeds of many kinds are scattered all over the earth to help us remember. And new people are born every day with the spark of that first light still alive and burning deep inside waiting like the everything seed to shine in ways that are yet to be known.


Russia begins to recruit women into the army. Russia's Defense Ministry has launched a recruitment campaign targeting women for roles as doctors, nurses and cooks in the military with possible deployment in occupied Ukraine. Sign a contract with the Russian Defense Ministry in the same ranks as men, read an advertisement in the western Siberian region of Omsk. The independent news website 7plus7 said it called the hotline indicated in the recruitment ad where it was told that women below the age of 50 are encouraged to sign one-year contracts with the military and that minimal professional training is required. Journalists were told that new recruits would serve in Russian regions, including the partially occupied Ukrainian regions of Dnetsk, Luhansk, Kursen and Zaporizia, which Moscow annexed in September 2022 following widely disputed referendums. Russian Defense Minister Sergei Shoigu said in March that 1,100 women were involved in combat operations in Ukraine, one-third of whom have received state awards. Overall, Russia's armed forces have 39,000 women within its ranks, including nearly 5,000 officers. The prisoner's rights organization Russia Behind Bars and Ukrainian officials said in March that the Russian military had begun to recruit women for battlefield deployment.


Tena koutou katoa.  Ki ora. I recently worked at Te Papa as a UX designer in the digital product team. In that time I looked at how to improve accessibility within Te Papa and part of that was looking at how to incorporate NZSL or New Zealand Sign Language into the museum. This presentation is going to cover some of the things that we learnt by integrating NZSL into our projects and also a research workshop that we ran with deaf participants. So why is New Zealand Sign Language important? It's an official language of New Zealand and that means it's recognised and it's written in law. Also Sign Language and Deaf Culture is referenced specifically in the United Nations Convention for the Rights of Persons with Disabilities Article 30. This article also references museums. It's a language and it's a culture. The majority of people who are born deaf and learn NZSL, it's their first language. NZSL is a very different grammar and structure from English. This means that when they try to interpret things like video captions or audio transcripts, it's like trying to understand English as a second language. While captions and transcripts are great for many reasons, providing communication in NZSL is actually the best way to communicate with this community. So what did Te Papa do? What have we done so far? The first project that we looked at was to acknowledge and celebrate New Zealand Sign Language Week in May this year. We told four stories of significant pieces of portraits in toy art. They were interpreted by Theresa Cooper, who is deaf, into NZSL. The stories were published on the Te Papa website and through social media. These are some photos from our process. Originally we planned to film the curators telling the stories about these portraits in English and to have Theresa Cooper then interpreting those stories into NZSL. We had a hearing interpreter standing just off the camera interpreting to Theresa so she could understand what the stories were. We used a steady cam camera rig intended to give this sense of immediacy and intimacy because it was sort of bobbing around a little bit and moving. We had rehearsed the sequences and we thought we were really well prepared. But due to a technical hatch on the day of filming, we had organised for the air con to be turned off but then it automatically turned on and we couldn't switch it off. So therefore it was really noisy and we couldn't film the curators actually talking about the portraits. So what we did was we filmed Theresa Cooper interpreting the stories into NZSL to the camera but she was reading directly off the script and the script had been intended to be read in English by the curators. So this was a little problematic. However we got the filming finished and produced and uploaded on to the website in time for NZSL Week. We knew that it wasn't perfect and we wanted to learn more so we asked for some feedback and we got it. First of all the moving camera was an ONO. It was too distracting so keep the camera still preferably on a tripod. Use a plain background with good contrast to the presenter so that the hands and the face are clearly visible. Facial expressions are really important so good light on the presenter's face is ideal. Plain coloured clothing creates less visual distraction as well. It's best to frame the video as a mid-shot from the waist up. Be really careful not to let the arms or the hands go out of the video shot otherwise it's like having a sentence cut off partway through. And ideally the presenter, the deaf presenter would be supplied with the script and the background information at least the week in advance so they had time to prepare. We didn't do that. The second project that we did was for Pacific sisters again in toy art. This was a video of the Pacific sisters talking about their work and their processes and we wanted to offer an NZSL interpretation of that video. This interpretation was going to be available on demand by the visitors by selecting the appropriate button. In this instance we used a hearing interpreter. We collaborated with an organisation in Australia called Connex U and they work a lot with the Glam sector in Australia to produce sign language videos for those organisations. They've also started working with a lot of New Zealand organisations so we wanted to try working with them and they were great. They were really helpful in helping us to connect with deaf people in New Zealand as well and that really was quite helpful later on when we were organising our workshop with deaf participants. We supplied the original video to Connex U as well as the audio script in a Word document. They filmed the interpreter signing an NZSL, sent the video back to us and we were able to put the composition together ourselves. That helped us keep control which we really liked. Again, we asked for some feedback and we got some different feedback this time. While having sign language interpretation available is really great, ideally the person signing would be a deaf person. This is because a deaf person has learnt NZSL as their first language so they have a unique way of telling the story from a deaf perspective. It also enables visibility of deaf people in the museum so representation is really important. In addition to that, it's really good to allow the option for captions to be turned on and off. Some people find them really helpful and other people find them distracting so it's good to give people the option. So we had all this feedback from these projects but we knew that there was more to learn. We ran an exploratory research workshop to understand the needs and experiences of deaf visitors to the museum. We organised the workshop with representatives from Deaf Aotearoa, Victoria University, Connex U and Arts Access Aotearoa. Most of the people in this workshop were deaf and we had two interpreters. We started with getting people to create their very own journey maps. It was an individual exercise. We wanted to understand everyone's experience of coming to Te Papa and then everyone came together and shared these journey maps as a group. Here's a couple of examples. So this man came to Te Papa to visit the Gallipoli exhibition. He had read a lot about it and he was very excited to come. However, once he got into the exhibition, he realised that a lot of the stories relied on audio and there wasn't the interpretation available. He says, oh, audio stories I tried to hear. I got bits but I missed too much. So while he enjoyed the visual experience of the exhibition, he missed a lot of the storytelling. He felt disappointed he wasn't able to have the full experience like everybody else. Another visitor came to Te Papa with her children. She was looking for a particular art exhibition and she had a little bit of trouble finding it. But once she got there, there was a host that approached her and started to tell her some information about this exhibition. She couldn't understand what the host was saying and the host didn't realise that she was deaf. So it was frustrating for both sides. She felt like she was missing out on some information that she could share with her children. She says here, what are they saying? Is it important? Am I missing some information? She just didn't know. After the journey maps, we had a second part of the workshop which was to create some designs. We posed the challenge to the participants. If you had a magic mobile phone that could do anything and it was going to help you in your journey through Te Papa and the experience of visiting the museum, what could it do? What could make things better? This activity was really good because it helps everyone be creative. But they don't need to understand any kind of design process or worry about technical constraints. We got everyone to share their designs afterwards and it's really valuable to have people explain their designs and thoughts in their own words. Here's a couple of examples. This mobile device is a transparent floating phone. It had a virtual NZSL guide interpreting things in the museum and touring you through the different experiences. The reason it floated was because sometimes holding a phone up all the time is really tiring on the arm. This gave us a really valuable insight about some considerations we should think about the ergonomics of design. It was also able to track where her children were in the museum. This next design was a comprehensive guide with information about everything in Te Papa in NZSL. It had things like being able to discover the facts in Te Papa, a virtual tour guide through the exhibitions, seeing what's on, some helpful information about finding the toilets in the parent's room. The rules of the museum, which is sometimes quite ambiguous, what you can and you can't touch, and really importantly, what to do in an emergency. From the journey maps, we were able to understand some of the core needs for the deaf people in the museum. This one, Access to Audio Information. I need to be able to access any audio content in the museum so I can get the full experience and not feel like I'm missing out. I need to navigate the museum independently because I can't always ask someone. I need to easily understand the rules of the space because so many stories are told using audio. Shared experience. I need to be able to access the same audio content as my family so I can be the educator to my children and have a shared experience together. So this is quite a unique thing to the museum experience at Te Papa where people come to share an experience and easily understand the rules of the space so my kids and I can avoid getting told off. Communicating with staff at the museum can be difficult. So there is now NZSL training available for hosts, which is fantastic, and that should help with future visits from deaf visitors to Te Papa. I prefer seeing other deaf people sign because it looks more natural and they can explain things from a deaf worldview. It also creates a sense of ownership and pride. This was one of the biggest things that we learnt is that it's important for deaf people to be able to tell their stories in their own way. Also representation of deaf people in the museum space is really important. We combined the insights from the journey maps and the magic mobile exercise to create the ideal journey map for a deaf visitor. Interesting enough, when you look at this, it's really nicely to other non-English-speaking visitors. This was presented to internal Te Papa teams and to some representatives from deaf Aotearoa. So we know that there's still a lot to learn, but the biggest thing that we learnt was the importance of engagement with the deaf community when developing outcomes for this audience. These core needs are also relevant to organisations outside the Glam sector, including government services. I personally hope to be able to continue this research and integration in my work at the Service Innovation Lab where I now work. The lab works across multiple government agencies to improve the experience of New Zealanders interacting with government services. Thanks very much.


Hello, this is Watson and in this video we'll tell you why the Watson 1610 LT is one of the most popular laser machine tools on the market. Its main advantages are a versatile working area and more than 50 modifications and improvements made by our engineers. The Watson 1610 LT is designed for mass production and cutting of non-metallic material. This equipment guarantees durability even in continuous use. It is suitable for both small batch production and large industrial halls. Let us talk in detail about the features of the Watson 1610 LT. The Watson 1610 LT is a medium format CO2 laser machine with autofocus. It is suitable for machining uneven non-metallic materials. The machine ensures high accuracy of operation, durability and ease of use. The machine cuts plywood and other wood based materials up to 13mm thick, acrylic and other plastics including double layer ones. In addition it handles fabric, fur, rubber, cardboard and paper. The Watson 1610 LT is equipped with a high quality work head that is securely attached to the machine's gantry. Even during continuous operation the mounts do not loosen. The lens Zinc Selenide D20 F50 is easy to access for cleaning. The 1600 x 1000mm working area allows processing medium sized sheets of material. The machine comes with a blades working table but you can also order an optional honeycomb table to cut fabric or layouts with many small details. The Watson 1610 LT is equipped with a lifting and lowering mechanism and the working area can be lowered to 160mm. This allows machining materials of various thickness and installing a rotary device to work with cylindrical items and also helps to adjust the focal distance. At the same time the working area can withstand a load up to 80kg which allows processing heavy materials such as marble, stone and granite. Due to the through table it is possible to process sheet and roll materials that are longer than the working area itself. The machine tool is used in woodworking and furniture production, packaging design, indoor and outdoor advertising for manufacturing souvenirs, toys, board games and educational games, cutting materials for the textile and footwear industries and in other areas. The Watson 1610 LT cuts wood, plywood, MDF, chipboard and other wood based materials up to 13mm as well as peronite, acrylic, solid polycarbonate and other plastics including double layer ones up to 20mm. It also works with fabric, fur, rubber, cardboard, paper, stone and other materials. The rigid frame construction increases durability and reliability of the machine. The bed metal walls are 2.9mm thick that virtually eliminates vibrations which is relevant for engraving when active inertia is created. At Watson all machine frames are heat treated to ensure that the accuracy of the machine will be maintained for several years. The reinforced gantry carries the main load during operation and significantly affects the durability, precision, lack of vibrations and travel speed. It is made of aircraft aluminum with a thickness of 5mm and up to 7mm in the corners. To ensure durability it has additional stiffening ribs. The workhead with autofocus allows keeping a set distance from the nozzle to the surface of the processed material regardless of its flexion. That ensures cutting and engraving curved material without wastes. The workhead is moved by three phase stepper motors that provide high speed and precision. The machine is equipped with one quarter belt gear boxes. This ratio is intended to split the pitch when the laser head is moving and to relieve the excessive load on the motor. Belt gear boxes contribute to smooth operation and improved accuracy and quality. At Watson 3M belts are only used. They have a larger tooth and are not prone to overheating or stretching thus having a longer service life. The 15mm PMI guide rails provide precise operation and are designed for continuous loads throughout the service life of the machine. The FOTEC end sensors with the actuation distance of 5mm are used to prevent any collision of gantry elements with each other. Unlike mechanical ones, inductive sensors are less likely to fail as they are not susceptible to contamination and are designed for a longer service life. As standard, a 100 to 120 watt laser tube is installed. The universal laser tube mounting makes it possible to easily set its position for adjustment. The mounts come with an adjustment screw and a scale which allows you to replace the tube very quickly regardless of its diameter and power. The reduced nozzle section area provides clean cutting without any soot on the edges of the workpiece. The machine is equipped with a water stroke sensor which ensures that in case of the cooling system failure, the Watson 1610 LT automatically switches off, protecting your laser tube from overheating. Water cooling system and air supply are separated from the electrics in different parts of the machine. We care about your safety. The RDC 6332M control system allows the machine to operate autonomously according to a preset program. Files can be imported via Wi-Fi, LAN, USB. The controller has built-in memory and is capable of saving files from a USB drive. The Watson 1610 LT is officially guaranteed for one year. You can always find all required universal accessories in any region of the world. The Watson's goal is to provide each customer with failure-free operation and guarantee the highest quality of final products at a lower price. For this reason, when updating our machine tools, we use reliable and most common components which ensures continuous operation. In order to know more about machines' features and prices, call us or visit our website. We hope that this video has helped you to understand the design and features of the Watson 1610 LT. If you have any questions about laser machines, feel free to post in the comments or visit our website or social networks. Our managers are always happy to help you.


Hello everyone. Welcome back to Investor Intel. My name is Peter Clausi. Today we're talking again with Chris Thompson about one of his research reports. Hi Chris. Hey Peter, how are you today? I'm well. You and I haven't chatted for a bit. Today we're talking about your report on Movely Media, which trades as MVY on the venture exchange. That's correct. You are paid to write research but you don't write anything you don't believe in. That's right. I try not to but yeah. I like to focus on names where there are some sort of catalysts happening and there's going to be a share price appreciation from these catalysts that could be perfect for the company. Well, Movely has already had a really nice capital appreciation. I met the CEO at PDAC 2020 where we stress tested the software. I think I did something like 35 interviews over three days and the software worked perfectly. So I became a shareholder a couple of years ago when it was around 6, 7, 8 cents currently trading around 60. Yeah. I also like the company so much. I bought some shares as well. I participated in the financing last December. So what drove it from 8 cents to the 60 where it is now? I think it's just public awareness of the product itself. It's grown to the size. You know it's gotten out 3.7 million users who are using the application. It also has got some great partnerships and I think that just the momentum of those announcements and those deals have helped investors become more aware of the company. It must be driving revenue upwards as well. Yeah. There is incremental revenue coming through. I mean they do have a fairly good e-commerce base or your consumer product that's out there that is growing steadily month on month. They had a bit of a boost you know with the COVID stay at home where people wanted to make videos. You know movely focuses on it's a feature rich platform for video creation and so it really sort of keyed in for people staying at home and wanting to create videos from home and that's where they got even more of a boost. But I think more and more it's the enterprise customers who are coming in who are using some of their features like their API to integrating to their own products or they also have an automation tool that allows you to customize videos very quickly and send it out and I think those types of features have really sort of struck a chord with the larger enterprise clients who are looking for a partner you know on the video creation platform. I was talking to the CEO Brendan Grunewald when they wrote their Google API so that it would enable like if you and I were talking within their platform it could give you subtitles in another language across the bottom in near real time as we're chatting. Yeah and that's one of the things that movely has done is it's really listened to its customers and tried to build a platform that really has a lot of features and work with their larger customers on that and that's what I think is really important because you know it's all said and good to have some you know some enterprise sort of some you know e-commerce clients come on one by one but really what you want to do is sign these larger deals and that's where I see the big catalyst coming where you get one of these larger deals and in my report I sort of give one example of like you know the the website creation software companies you're just one of these partnerships of signing up say you know 100,000 clients you know at a dollar per day as an incremental million dollars to movely's bottom line and these are the types of catalysts which will see the revenue go like you know from 1.5 million this year sort of the 2.5 million next year and even maybe up to a step jump of 8 million and that's what I have in my report and that's and that's where I'm seeing this sort of this catalyst being done by these larger enterprise customers coming in and and taking hit the platform and integrating it into their offering. Does movely have the capacity to scale up? Yeah it's a SaaS based platform so it's easily scalable itself and they've gone on and signed up to hardware contracts online with the distribution of the various web points to enable it to scale up into millions of users. And I see that this week or today well today they announced that they've integrated with Instagram allowing users to publish videos made in movely's platform directly to Instagram. Yeah and they've done that with both on the in and the outbound they've done lots of third-party integration so they've integrated with products like you know box and Dropbox and Google Drive and Microsoft Drive to be able to to get your your information on and off or in and out of the platform and then they when you've done the video they have integrations with with things like platforms like Facebook and Instagram YouTube so you can maybe publish your videos to those platforms. So seamless is the magic word right? Yeah seamless exactly so you can when you're talking about moving around you know data you want to be able to easily pull data in and out of your platform and be able to publish it seamlessly to your to your audience. 136 million shares out trading around 60 cents so roughly an 80 million dollar market cap today. Where do you see it going? Well in my I did a DCF as well as a revenue blend to create a target price. I have it in the next 12 months being at $1.40 based on those metrics and that's and that's from the revenue going from you know 2.5 million this year to about 8 million the year after. So I believe with those enterprise clients they can achieve those numbers. What kind of multiple are you using? Well it's a fairly healthy multiple it's a 40 times revenue multiple right now because of the growth in the product as well it is a SaaS product and because of its growth curve it does warrant a fairly high multiple. Who else has that kind of multiple? Shopify? Shopify does have a high multiple any of the your SaaS based growing companies that are scalable and of interest to you know probably a third party acquisition you know could be interested in it will warrant that high multiple. Neat. Well I'm due to talk to Brendan soon anyway so I can bring this up with him. Your website is e-research.com. That is correct. So you can find the report there if you have any questions Chris is easy to access by phone or by email his information will be all over the website. It is and it's all over the report the report's available for free from the website you can download it and my contact information is on the report. Chris it's always a pleasure talking to you. Thanks Peter have a great day. Peter Clausi signing out from Investor Intel. Have a safe day everyone.


Okay, this is the first part of lecture two on algebraic geometry in which we'll be discussing affine space and the Zariski topology on it. So first of all, what is affine space? Well, if you take any field, common choices will be the real numbers or the complex numbers or a finite field. So we take a field k and affine space is then just k to the n, a vector space of n dimensions over k, except it isn't quite, as we'll see in a moment, and it's often denoted by a to the m for affine space. So what's the difference between affine space and vector space? Well, the difference is quite subtle. They have slightly different automorphism groups. So let's first look at the automorphism group of a vector space k to the n. So we have automorphisms of a vector space. Well, these are just invertible linear transformations. The group of automorphisms is denoted by the general linear group over k, which is just n by n matrices of determinant, none zero. So we can picture this if n is 2 as little 2 by 2 matrices of non-zero determinant. On the other hand, if you look at affine space a to the n, then the automorphisms include all linear transformations gln of k, but they also include translations where you map any point x to x plus v for some fixed vector v's. So these are the translations. So the full group, so this group has dimension n squared and this group has dimension n. So the full group of symmetries of affine space is dimension n times n plus one, and it can be pictured as the group of matrices of the following shape where this bit here in the top left corner are just the automorphisms of the corresponding vector space, and this bit here corresponds to translations. So the difference is roughly speaking that a vector space has an origin and an affine space is kind of like a vector space except you've forgotten what the origin is. In other words, if you've got a vector space, then from any vector space we get an affine space and we get the affine space just by forgetting which point 0 is, roughly speaking, and to get from an affine space back to a vector space, all you have to do is choose any point of the affine space as your origin and that makes it into a vector space. For example, take the three-dimensional space we live in and pretend we're in the days before Einstein so it's not curved or anything like that. Then the three-dimensional space we live in is really an affine space, not a vector space because there's no really natural way to choose the origin. But if you choose the origin, for instance, you might choose the origin to be the centre of the Earth or if you're in the ancient astronomer you might choose it to be the centre of the Sun if you're trying to study the solar system or you might choose it to be the centre of the galaxy or whatever. You can choose any point you like as the centre of coordinates and then three-dimensional space becomes a perfectly good vector space but there's no canonical way to choose the identity. So we're actually living in a, well, I guess it's not really an affine space because it's got a metric but never mind. So affine geometry can be sort of as a study of the properties of affine space that are invariant under affine symmetry. So any property that is invariant under translations and linear transformations. So let's list some properties of affine geometry. Well, perfectly good concepts of things like points or lines or parallel lines because if two lines are parallel and you do any sort of linear transformation or translation they remain parallel so that's fine. Connex are also well-defined and even polynomials. So polynomial functions on affine space. Next we should list some things that are not affine geometry. So first of all, circles are not affine. This is because if you take a circle and apply some linear transformation to it there's no reason why the result should be a circle. It might end up as some sort of ellipse. However, if you take all connex including ellipses and circles then that is a perfectly well-defined concept in affine geometry. Similarly, angles make no sense. For example, if you take a rectangle and apply some linear transformation form 1101 to it, the skew transformation becomes some sort of parallelogram and this angle here doesn't get preserved. Similarly, lengths are not well-defined in affine geometry because they're changed by linear transformations. Now, algebraic geometry tends to use the coordinate ring of affine space. So the coordinate ring is just the space of all polynomial functions or all polynomials on A to the N. Notice that whether or not something is a polynomial doesn't depend on the choice of origin so that's okay. I should mention here we're taking our field K to have an infinite number of elements because if it's only got a finite number you've got to be a little bit more careful about how you define the polynomial ring. So we take the polynomial ring Kx1 up to xN or polynomials in the N coordinates. So a point here is going to be x1, x2 up to xN. So if we've got affine space we can reconstruct the ring of polynomials on it's just as polynomial functions. Conversely, if we've given the polynomial ring over K we can reconstruct affine space as the A to the N as the set of homomorphisms from this polynomial ring to the field K. This is homomorphisms as a K algebra. So a homomorphism taking Kx1 up to xN to K just takes x1 to A1 for some number, A1x2 to A2 and so on. So it's uniquely determined by these numbers A. So this corresponds to the point A1, A2 up to AN of A to the N. And you notice this map here is just the value of the polynomial at the point A1, A2 up to AN. So we can go from affine space to the coordinate ring by taking all polynomials and we can go from the polynomial ring to affine space just by taking various homomorphisms. So because of this, the study of affine space is more or less equivalent to the study of this polynomial ring. So anything you can do for a polynomial ring has an analog for affine space and anything you can do for affine space has an analog for polynomial rings. In particular, for example, the automorphism groups of these two things are the same. So we had the affine group acts on affine space and you can also easily check that it's the group of automorphisms of the polynomial ring over K. Next, we're going to discuss the Zariski topology on affine space. So if we do this, we define algebraic sets. So an algebraic set is a set of zeros of some set of polynomials KX1 up to XN. So this is going to be an algebraic set in the n-dimensional affine space.  The set of common zeros of X minus A and Y minus B is obviously just the point AB. So a single point AB is also just an algebraic set. And now algebraic sets are closed under the following two operations. So they're closed under, first of all, they're closed under intersections. This is because if we have an algebraic set C1, C2, C3, and so on, which zeros of sets P1, P2, and so on of polynomials, then C1 intersection C2 intersection C3 and so on is the set of zeros of P1 union P2 union P3 and so on. So taking intersections of algebraic sets just corresponds to the operation of taking unions of sets of polynomials. They're also closed under finite unions. And you've got to be a little bit careful here because if we take the union of two algebraic sets is not given by the set of zeros of the intersection of their polynomials. Instead, if C1 and C2 are zeros of sets F1, F2, and so on, and G1, G2, and so on of polynomials, then C1 intersection C2 is the set of zeros of the polynomials FI, GJ. So we have to take all products of pairs of these polynomials. And you notice this doesn't work for infinite unions because to do for that, we'd have to take the product of an infinite number of polynomials which doesn't really make sense. Now, we notice that if a collection of sets is closed under all intersections and under finite unions, then they form the closed sets for a topology. And this is called the Zariski topology. So the algebraic sets are the closed sets of the Zariski topology. Of course, to check something's the closed sets of a topology, all you have to do is to check it's closed under arbitrary intersections and finite unions. Arbitrary intersection means the intersection of any collection of subsets. I've sort of written as if it's a countable collection, but that's just because it's easier to write. So let's see some examples of Zariski topologies. So let's first do one-dimensional affine space A1. So this is just a line. And we can ask, what are the closed sets of it? Well, first of all, the whole line is the set of zeros of, you can either take the empty polynomial or just the polynomial zero. Any finite set is going to be the zeros of a polynomial x minus A1 times x minus A2 and so on. So any finite set of points is going to be the set of zeros of some polynomial. And in fact, these, the whole of A1 and finite sets, you can easily check, are the only possible closed sets. If you've got any collection of polynomials, their common zeros are either a finite set or they're the whole space. In particular, this topology is a bit weird. I noticed that it does not house dwarf. And this is a bit of a problem because if you've done a course in topology, probably most of the topological spaces you were seeing were house dwarf.  And this simply isn't true in algebraic geometry. For instance, if you take a line and take two points on it, if it were house dwarf, we would have to find open sets. We're going to be able to find open sets containing each of these points that are disjoint. But the trouble is the only open sets contain all but a finite number of points. So any two open sets have an infinite number of points in common unless they're empty. That's again assuming that we're working over a finite over an infinite field, over a finite field, but this happens to be house dwarf, but that's a bit misleading. Let's look at two-dimensional affine space A2. So let's write down some closed sets. Well, first of all, we've got points A, B, which as we saw earlier is the set of common zeros of X minus A and Y minus B. And we've also got any curve, any algebraic curve, which are the set of zeros of FXY equals zero. So any irreducible curve will do. And as we said there, closed sets are closed under finite unions. So a typical closed set will look like a few algebraic curves and a finite number of points. Here is a typical open, typical closed set in two-dimensional affine space. Notice by the way that the Zariski topology on A2 is definitely not the product topology on A1 times A1. So if we take the product topology on A1 times A1 and look at its closed sets, it's not very difficult to work out what these are. We get a finite number of vertical lines and a finite number of horizontal lines and a finite number of points. So the product topology on A1 times A1 has far fewer open sets than the Zariski topology on A2. So in higher dimensions, algebraic sets look like this only more so. So we get points and we get one-dimensional curves and we get two-dimensional varieties and we get hypersurfaces and so on. I just finished by giving you one slightly more exotic example of an algebraic set. So this is an example of an algebraic set. It's called a determinant variety for a reason that will be pretty obvious in a moment. And what we do is we take affine space of dimension m times n for m and n integers. And we think of this as being linear maps from k to the m goes to k to the n. And these obviously form a vector space of dimension mn because you can think of them as being m by n matrices. And now an algebraic set is going to be all linear maps of rank less than or equal to i for some constant i form an algebraic set. So this is going to be the determinant or variety. And we want to check that it is actually an algebraic set. So this is given by the vanishing of all i plus 1 minus of an m by n matrix because this is just the condition for a linear map to rank at most i. So this is some set of polynomials. You notice it's actually quite a large set of polynomials in general because we have to choose i plus 1 of the m rows and i plus 1 of the n columns and in general this would be a really quite large number of polynomials. So this determinant or variety is given by the set of common zeros of polynomials but it's a large set. In particular, for example, the subset of maps from k to the m to k to the n that are onto is open in the Zariski topology.


General Merrick Garland has a lot of reasonable friends who say he is a smart and moderate person But that was not a moderate statement. He was dishonest completely dishonest dishonest enough. You should be worried about it There's no evidence that white supremacists were responsible for what happened on January 6th. That's a lie Tucker Carlson needs to be you know tied up and put in the corner somewhere. So we'd never hear from him again Are you sure about that? Yes?  Well, this is important Okay, because the stuff that they're saying on the spew is the exact same thing That's getting pumped out into the country from the former free press. What's known as the mainstream media But before we get into that I'd like you to hit that like button and subscribe and as we all know you gotta hit that bell icon as well Because otherwise you won't be notified about new content Well, I'm not being completely fair here because eventually Bayard does back off her call to violence against a reporter Who says things that she disagrees with? Yes Can I just say what yeah, I don't mean to yes, I do it think bad should happen I do not mean to imply that anything harmful should happen to Tucker Carlson I just want him to stop saying stupid things.  I'm not Tucker Carlson needs to be Yeah tied up and put in the corner somewhere. So we never hear from him again I'd like to be perceived as someone who's violent in any way.  She wants everyone to know though that she's not violent I wonder what's to be done with all the stupid that's coming from Bayhar herself and this hour of propaganda and misinformation That they call a talk show believe it or not There is more bombastic BS from the view but first this quick message from this episode sponsor noble gold one of the first Commitments made by the new administration is the two trillion dollars spending on environmental concerns with renewables like solar panels Wind turbines and even batteries for electronic vehicles. The use of silver will soar but of course we don't have enough silver to cover the demand and that is good for investors and the price of silver if you're Thinking of an IRA or a 401k now is the time to look at silver and this month with every gold or silver IRA they're giving away one of these incredible 5 ounce solid silver Apollo 11 memento coins with every silver IRA that started click on the noble gold link in the Description or pin comment right now and learn more about future-proofing your investments All we hear now from Democrats and their propaganda machine known as CNN MSNBC CBS NBC ABC and the vast majority of the former free press is that all their political and business opposition Needs to be silenced from social media to cable news We just had several Democrats trying to strong arm AT&T to drop Fox News News Max and OAN Basically just leaving Democrat Party state media their reason those networks say things that they don't agree with and have tenuously connected to the minor riot at the Capitol yet We watch years of left-wing violence go largely unreported while the networks and the politicians that incited and stoked that violence are somehow Exempt from these same standards. So back to Bayhar. Why was she threatening Tucker Carlson in the first place you asked? I mean you had Tucker Carlson on television last night saying that there was no Evidence of white supremacists at the riot right? Wrong first off Houston's lying right off the back because Tucker Carlson didn't say anything about there being no evidence of white supremacists at the Capitol Carlson said that there was no evidence that white supremacists were responsible for what happened on the 6th There's no evidence that white supremacists were responsible for what happened on January 6th That's a lot and the phrase white supremacists itself is nebulous It has come to mean pretty much anything that is white and stands against the left and you don't even have to be white anymore This is a sleight of hand on hostess part But she still has no evidence just because someone was there waving a Confederate flag Doesn't mean that there are white supremacists and then you can't just judge thousands of people because of one person The evidence was clear at the riot at the at the insurrection I mean you had people carrying Confederate flags so hosting acts like there was Confederate flags everywhere and symbols of hatred Let's look at some pictures from the Capitol I mean there should be Confederate flags and racist symbols everywhere right? I mean look at this one I see nothing but American flags and how about this one? Okay? I see some Trump flags and American flags or this one American flag American flag looks like we got a Betsy Ross flag up there Oh, I know they really hate that one, but it's not a symbol of white supremacy any more than the American flag is which we all know is coming, but let's just look at a few more pictures here No, don't see any Confederate flags or racist flags there. Oh, here's one. Oh, look one guy One person standing there with a Confederate flag. Are you kidding me? That's your evidence Well, let's look at the aftermath of some BLM rallies. Oh, here we go George flight Communist symbol hammer and sickle another Communist symbol whoops that must mean that they're all communist, right? Here's another one a BLM rally. Oh, look at that hammer and sickle Communist flag. Oh, and look, there's another one But we all know that BLM nor antifa or Democrats at all will ever be held to that same standard It's literally just something they're making up on the fly so they can suppress all dissent How are we done a Capitol police officer a black Capitol police officer saying that he was called racial slurs at that Insurrection I was disgusted by what Tucker Carlson said how dare he say there was no evidence of white supremacy There there was evidence everywhere. Okay, and who was that person? Do you know their identity? Do we have any recordings any audio any evidence at all that his claim is true? But I want you to remember that they've tried this before with the Tea Party with black Democrats claiming that they were called the inward Again with no evidence despite there being cameras and mics everywhere and even a hundred thousand dollar reward from Breitbart At no time during hosting's rantings or this politifact propaganda Do they ever prove that white supremacists were responsible for what happened at the Capitol? As we do know there were left-wingers there who were instigating and inciting violence And then getting paid by CNN and MSNBC for the video. All right That's all I can take of these traitorous liars for one sitting if you enjoy this video Please hit that like button and I'll see you all next time


Hello, everyone. Thanks for joining. My name is Animesh Singh. And this is my colleague Tommy Lee. Together, we work for IBM Cloud and Containers Developer Technology Group. And today, we are here to talk about how you can build resilient and fault-tolerant microservices leveraging Istio. Now, before I go into some of the details, how many people are actually using service measure Istio here? Very few. I didn't see any hands raised, in fact. So I think it will make sense to actually go back and talk a bit about the motivation of the project, except for what led to it. But essentially, in 2014, there was a reactive manifesto which came out. More than 20,000 people have signed it. If you haven't read it, I would highly encourage you to go and read it. Very nice read. But the key theme there was that today's application demands can simply be not met by yesterday's application architectures. Essentially, today, what we want are systems which are responsive, resilient, elastic, and message-driven. Now, if we focus on the resiliency piece of this, what it says is they are significantly more tolerant of failure. And when failure does occur, they actually meet it with elegance rather than disaster. That's essentially one of the true characteristics for a cloud-native application. Typically, during the same time, microservices revolution was happening. It started somewhere around that same time frame. And essentially, as we are all aware, you take a monolithic application, break it down into single functions, which are typically around business capabilities. And you have small teams which are actually developing, maintaining, and deploying those microservices. Now, typically, microservices are encapsulated inside containers. There is a one-to-one relationship most of the times. Everyone's container journey starts with one container, and it's easy in the beginning. But soon, the growth becomes overwhelming. We need container and microservices management. Enter container orchestrator. Now, if you look at a survey which was done last year where we asked respondents, what are they expecting most from a container orchestrator scheduling, cluster management, and discovery where the top three functionalities are identified? Now, if you look at the container stack and all the layers, definitely popular container orchestrators like Kubernetes, Swarm, Mizo, they actually set a layer five of this. We are all aware of the Kubernetes architecture. Any interaction we do with Kubernetes through our UI, CLI, API goes to Kubernetes Master. And then we have slave nodes, which are essentially responsible for running your workloads. They actually run the QBlade, QProxy, Docker Demals. And they are then serving your workloads on top of those slave machines. Within IBM, we have our own IBM Cloud Container Service, which is based on Kubernetes. It's a managed service, so we manage the Kubernetes master. It's single tenant. The slave nodes are actually managed by the customer. We do provide triggers for OS updates, patches regarding Hypervisor, Docker Demon, et cetera. And customers can actually scale up and down based on their need. We actually use the logging and monitoring data from the slave nodes to provide the management. But we don't have any access to the persistent data which is residing on customers cluster. What we did was we actually also created a lot of developer patents to show how Kubernetes and microservices work great together. So they are essentially on-ramps to technology. And they actually help developers be productive with cloud, data, and AI. You can actually find a lot of our developer patents on developer.ibm.com, slash code, slash patents. And anything you need with this getting started with the technology, be it the architecture diagram, step-by-step instructions, the actual code in the GitHub repo, it's all there. So some of the microservices pattern we created for all the Java and Spring Boot fans out here. How can you actually run Spring Boot microservices on top of a Kubernetes cluster? In addition, in this particular pattern, we also show how can you use functions using the very popular open-source open-visc, which is part of the Apache Foundation. There is another Java EE framework, which is becoming quite popular, which is MicroProfile. It's being backed by Red Hat, IBM, Fujitsu, and others. And we'll talk in big detail about this particular MicroProfile microservices framework. So there is a developer patent to actually use that. And if you're in a polyglot land where you actually are having microservices written in multiple languages, there is a patent to get you started there as well. So what we see is Kubernetes is great for microservices. Do we need anything else? And that's a question a lot of people were asking. Kubernetes and microservices already handle a lot of your use cases. Now, what we saw on that slide was the top three functionalities which a container orchestrator gives you, scheduling cluster management and discovery. But is that enough? We need to build fully reactive and resilient microservices. And for that, we need mechanisms to actually avoid fault. So that means when you are doing candidate testing, A-B testing, rolling out new versions, you need to be able to selectively route traffic. You need fault isolation. So that you have ways to create circuit breakers. You are enforcing bulkheads, et cetera. Detect faults when they do happen. For that, you need great metrics capability. And then if failure does happen, you are able to recover from it in a graceful manner. In short, what we need is strong visibility, fault tolerance, traffic control, and a way to enforce security and policies. Enter service mesh. So what essentially is a service mesh? A way to think about it is think of it as a network of devices. So essentially you have a network in your data center which is connecting two machines. In this case, instead of connecting two machines, you're connecting a couple of microservices together. And all the tasks which typically the routers and the switches would handle, that's all offloaded to the service mesh. Now how do you actually build a service mesh? Enter sidecars. So sidecars actually are gatekeepers which actually sit within your pod along with your microservice. And they are responsible for intercepting every incoming and outgoing traffic. And because they are able to do that, they also provide you rich routing, load balancing, plus they're collecting a lot of data which they can pass to the metrics systems. Istio essentially is an implementation of the service mesh launched earlier in the year. IBM, Google, and Lyft came together. And if you look at the architecture of Istio, essentially three key components are there. Pilot, which is actually responsible for configuring Istio deployments and ensuring that all these configuration are propagated to all the components in the system. All the routing and resiliency rules which we create, they actually go in Istio Pilot. Mixer, which is responsible for policy decisions like ACLs, rate limiting, authorization, et cetera. Mixer is also actually responsible for giving you the dashboards which give you the great metrics capability. And then finally proxy, which is essentially the sidecar which is the heart of the service mesh architecture that is based on Envoy and it mediates all the inbound and outgoing traffic and it's responsible for enforcing all the policy decisions, all the routing decisions, load balancing decisions. When your application does get deployed, this is how it looks. You have Istio control plane with all these components and then finally your Istio data plane which is essentially hosting your application. Taking a bit more into the architecture, as I said, all the traffic entering and leaving is being intercepted by Envoy. Envoy essentially is a layer seven proxy which was developed by Lyft, very high-performance proxy, able to actually handle up to five million requests per second. That's essentially the heart of this. You then have ingress proxy which is the gateway to your application. You can actually use Envoy for that as well. A lot of people actually use their Kubernetes ingress controllers. And then NGNX also announced they have added support now so you can use NGNX instead of Envoy. And all these different protocols, GRPC, HTTP, HTTP2, HTTP1, they are all supported by Istio currently. So how do we make microservices resilient with Istio? So let's see the capabilities which Istio is providing. Traffic control and visibility, let's go into them a bit. So for example, when you are rolling out a new version of your microservice, you don't want to redirect all the traffic to that. You want to selectively control, in this case, a rule like, just send 1% of the traffic to this new version will actually ensure that if there is some fault in your new version, you can actually roll it back in a timely manner. You can steer the traffic based on the content based on whether the user is using an iPhone or an Android or a particular browser or the request is coming from a particular geographic location. You can steer it to a particular version of your microservice. Then I talked about visibility which is essentially the key. How do you actually look what's going into your service mesh? So Istio comes by default with Grafana, with Prometheus backend, as well as Zipkin, which actually gives you consistent metrics across the whole fleet of microservices which you have deployed. Essentially, since Envoy is intercepting every incoming and outgoing traffic, it's also able to store that data and be able to transfer that data to Mixer, which is based on a plugin-based architecture and Prometheus and Grafana. They're actually plugins for this and you can actually bring your own dashboard into this mix. And definitely Zipkin, which gives you the request tracing capabilities and which is very important. You are able to look at the source of the request. You are able to look into the request headers. You can see which services are lagging, which are slow. All that information you can get from the Zipkin dashboard. So around the same time Istio was launched, we launched a developer pattern. How can you actually manage micro-to-services traffic using Istio on Kubernetes? So we took the sample book-in for application, but we also, what we did was we added a relational database component to it. When the sample application came out, it was a static application. Everything was being written to the local file system. So what it allowed us to do was, A, make the application dynamic. B, we can also show that for egress traffic, where a certain protocol is not supported by Istio, for example, in this case, you are using JDBC to connect to a relational database. How does Istio handle it? This is essentially what's happening in that particular pattern. So essentially what we are showing is that how you can selectively route traffic to different versions of the microservice. Now, if you probably would have seen book-in for many times, but if you don't, book-in for actually gives you a product page, which gives you the details of the book. Then there are reviews microservice. There are three versions of it, which essentially are reviews of the book. And then finally you have ratings, which are like how many stars this is getting. So in this case, we are showing that, we are splitting the traffic 50-50 across the version two and three and nothing is going to be one. Similarly, if a particular user is coming, we can actually select where to redirect him. The other thing which we can do is that we can limit the access to a particular destination microservice. So in this case, when we see, we probably want to say that reviews version three doesn't and cannot talk to ratings microservice. So you can actually make decisions based on that. So now let's look into fault tolerance. And if you still are questioning why we need fault tolerance because things will go wrong, how many of you were on the rainy street yesterday night? I was like one of these and I was shivering there, right? So can't predict things, things will go wrong. And essentially before going into this, let me talk about some of the definitions, which we will use and I want to make sure, everybody's aware of some of these terms, which are being used in the resiliency features. So circuit breaker and I'm going to read it, we'll be at him because this is a great definition. So the basic idea behind a circuit breaker is very simple. You essentially wrap your function call inside a circuit breaker object. And what it does is once the failure reaches a certain threshold, the circuit breaker trips so that any other further call to the circuit breaker returns with the error without overloading your protected method. So that's the idea behind circuit breaker. Then we have bulkhead, right? So that's a pattern which is talked a lot about in the microservices use case. Now, essentially, if you see in the industrial world, bulkhead was used in ships or aircrafts actually to partition them into sections. So if a hole does happen in the hull of the ship, in this case, the water will only fill one component or one compartment and the ship wouldn't sink. So that's the idea which is also carried forward into the microservices patterns. Now let's test the resiliency of the sample application, right? So within IBM we actually have developed a tool, IBM Research essentially is developing it's in very early stage, but that actually gives you a great visualization whether your application is resilient or not. So it gives you a control panel to inject false. You can actually inject false in your sample application and then visualize the traffic flow using the view panel. In the first case, what we see is we actually abort the ratings microservice which was the last microservice. And in this case, the system is behaving as if the ratings microservice is not available. What we see is reviews microservice is written correctly to come back and just show the reviews if the ratings is not available. But if you actually add some delay, when your ratings microservice is delayed, there is timeout happening. In that case, the application crashes. It is not able to handle and know the reviews microservice just shows that it's not even able to process and show you the reviews, which is the wrong behavior. So this tool actually allows you to test fault tolerance and it's actually pulling the data from Prometheus and Zipkin and giving you those visualizations and you can actually click on the details and be able to see what are the response times where it is lagging, et cetera. With that, Tommy would give a very quick demo of the sample book info application and this tool. As I said, the tool is in very early stage. So if it doesn't work, we do have a recording. We have a fault tolerant. And then I'll come further and talk about how do we actually handle resiliency in application frameworks themselves and then how does this do handle it. With that, Tommy. Hi, I'm Tommy. I'm going to show you the book info samples and how to use that tools. So for the purpose of this demo, I already have Istio and book info deployed on my cluster. So as you can see, this is a book info page and you have the details microservice showing the details and review microservice showing the reviews. And also the rating microservice will help you help some of the review, some version of the review microservice to show the review stars. As you can see, this free version of the review. This is the version one of the reviews. This version three of the reviews. This version two of the reviews. And right now I'm going to apply Istio traffic routing rules to route all the traffic to version two of the reviews. So I will run a Istio control command. So right now all the traffic route to the version two of the reviews microservice. As you can see, no matter how many time I refresh, you'll always see the review with the black stars. So right now I'm going to show you the tools. This tool is called Istio analytics. It's developed IBM internally. What it does is it could apply false injection into the Istio pilots and also help you visualize some of the traffic using the login data from Permanenteus. So let me apply some traffic to our point for page. Or trying to apply some traffic to the sample look-in for page support. But it does take some time on the traffic walls and it picks up the rules to actually show you the visualization. Right. What it shows right now is all the login data for the past 30 seconds from Permanenteus. So you can see all the ingress traffic is going to the product page. And product page is calling the details and review microservice to get the details and reviews. While we will also call the rating to get the rating stars. This is the business as usual, right? Right. So right now I'm going to abort all the traffic to the rating microservice. So what Tommy is doing here is he is essentially aborting any request which is going to the ratings microservice. Hopefully if it is working fine if the request aren't able to go through. We're able to see that the application is written correctly to handle like a particular destination microservice is not a good idea. So the tool does take some time to apply the rules. So give it a second. So as you can see like for the past 30 seconds the traffic to the rating is decreasing because we abort all the connections. And we refresh it. As we can see the review microservice is good at handling 500 status code from the rating service. So it's still working fine. It's healthy. However, if you apply delays on the rating microservice. What if some of us essentially, you know we have ordered every request to ratings and still reviews is working fine. So the application is written correctly to handle that. Now let's see if we delay the ratings. What will happen to that? Now I'm going to apply a 20 second delay to 100% of the connection to ratings. So it does take some time. Adding a little 20 seconds of delay time so it takes about 20, 30 seconds to 40 seconds for the tool to actually start showing you the results. But in this case, hopefully what we will see is that the application is not written to handle that. So what you should have expected is the reviews are still being shown even if the user ratings the stars are not available. As you can see, the red bars are the error message from review to product page. And if you go on the product page, you can see that page is loading because we are having delays, putting delays on the rating microservice and review doesn't know how to handle that. That's why we turn the file for status code back to the product page. And that's the end of the demo. We give it back to Anmesh. Thanks. We just showed you how using this tool we can actually use Resiliency. We can actually test the Resiliency of our application and what's happening, as well as the traffic jam. So now some of you may ask, aren't Resiliency features already available in application libraries and frameworks itself? For example, if anybody who is using Micro Profile Java E framework, some of these capabilities should come out of the box. And you don't know about Micro Profile as I mentioned earlier that it's a Java E framework initially based on JAX, RS, TDI, JSON, P, IBM, Fugitive, Zivu, Red Hat, how we try to figure out the amount behind it. And there is a strong focus within Micro Profile around forward current. So let's see how do you handle it without this tool from just a micro service framework itself, right? So typically what you can do within Micro Profile is you can actually add all these annotations to your Java classes or Java beans and it actually helps you to add things like time off, you can try it all back, okay? For example, you can just add those annotations and to these and it will start giving you those categories. Now if you didn't have this, typically you would perform like this, right? There is an issue connecting to a service, try it five times. Now because of this annotation, you can actually add it directly in the code itself of an annotation to handle if something is not responding or you actually need to try it when you want to reach it. Similarly you can actually add annotations for time off. So you have here saying that there is a delay that time off of these many seconds. Well, okay, which is essentially you don't want to overload your service in this particular case. So what you're saying is that only five requests will be allowed and the rest of the requests can go in the rating issue. It will keep your request in the rating issue. From that perspective, a lot of these capabilities actually come from the framework itself, right? Essentially circuit breaker as well. You can actually essentially give an annotation for circuit breaker inclusive. There is also another annotation which is very useful in the micro profile case which is fallback. So yes, things go wrong, things will go wrong, but what do we do if something goes wrong? So instead of going X, you can go Y, so fallback is an annotation which you can add and that fallback you can define. Okay, this particular thing is not reachable or it's trying to solve its delay. Let's do this. So what happens if we slide this TO into this mix? The application libraries themselves are giving you these what are its features. What we will do, right? So micro profile gives you a way to actually disable all the annotation based approach. So even if you have an annotation within your code, you can actually set a variable and by that you will be able to disable everything else and this TO will take over in this particular case. Except for fallback, fallback is something which is more native to the application what you want to do if something goes wrong. Now, some of you might have question, right? What if both are enabled, right? So if your application is saying three tryouts and you still are saying five tryouts, how many tryouts will happen? That gives, right? So in this case, it will be 15, right? But then our policy is that tryouts after 10 seconds of the application these two are saying tryout over 20 seconds. What will happen? So the more restrictive will be taken first. So, okay, the reason here we still need these two in these cases is yes, frameworks which are mature which are sophisticated who come with these application libraries but what if we have a colleague-lawed application? Which you want to rewrite all these foreign features if you have micro services written in Python, O, PhD, that would be very cost intensive. This actually allows you to do it in a generic manner. So you can actually add forth on this to your application without any tools to force. So you can create simple things like timeouts, three tries with time on budget, you can create second labels, you can control the connection pool size and it plus flow, you can inject force. So for example, in this case, right? We can create a policy to show that there are X plus Y connections. What we are saying is that only X maximum connections are allowed to Y are connected and anything beyond that should be important. So you can create policies regarding this. Actually, there will be a balancing injection pool. So essentially, if a particular port is not responding, you can create a policy to inject it out of the load balancing pool so that any subsequent request are not being sent to that particular port. And then definitely you can add timeouts and retries within this particular application. So, quite important is to give you a lot of HTTP, GRBC, and of course, the laws you can inject force. In fact, the SDO analytics tool which we showed from my research, that's actually using the coordinated feature of SDO to inject force and show what's happening and the visualization what it's showing. And then we also created a pattern which actually goes into the details of it. How do you actually do that? So you can actually get that pattern there and Tommy is going to come and show you that pattern. So that essentially allows you to go step by step and show that how you can actually use the load balancing detection pool. All these features from this tool you can actually use it. This is a micro profile sample application. This is not the sample bokeh point application. So that, Tommy, we'll come and show you. So you go to our IBM pattern page to see these examples. It's using Java logo service. So what this examples is, it has five major Java micro services called speaker schedule web applications, sections and all these micro servers will communicate directly to the SDO ingress. And for the micro servers, they also use the cloud and database image to store it's building data and all of them are running on SDO. And here's the GitHub page of this pattern. And what we're going to show right now is the circus breaker feature on SDO.  And I also have this example running on another cluster. So once you deploy it, you're able to see like a page similar like this. This is a sample web conference app where you have speakers, you have your schedules, you can read their talks, et cetera. Right, so you can vote anything and you can go to the vote page and see all the voting data. This data is stored in a cloud and database image. So right now everything is broken properly. But however, if you want to roll out a new version of the cloud and image, if that's broken, what happens? So right now let me inject another version of the cloud and image. As you can see the cloud and dp second is our new version of the image. However, it's wrong open property. So it would keep having five hundred status code back to the work microservice as you can see. It's not working properly. So it's creating error to this microservice. So what I'm going to do is going to apply apply this circuit breaker rules. What it does is when it detects server error from any of the parts, it ejects from the load balancing pool. So it will keep all the traffic only passing through the healthy parts. So let me apply a E-steal control rule. So right now you try to keep booking. So the first time you see the vote is creating error. But after this error, the circuit breaker rule is designed to eject that broken image out of this load balancing pool. So from now on every vote you vote is going to be healthy returning 200 status code. And that's the end of this demo. I will give it back to Animesh. Thanks for everything. What it just showed was, you know, that using a simple E-steal policy would enable ejected servers, which is not performing out of the load balancing pool and all of a sudden all your errors. So a lot of these are patients that get a positive image was there, that particular case. So if you do want to try it out, a lot of our development patterns around E-steal from micro-services are actually at that particular link. The slides are at this particular link. So I do want to end it by saying that next film, Reactive Micro-Services, which are responsive, resilient, elastic, message-driven. Let's use this team. Thanks again. Thank you. Thank you.