previous lecture talked about some introductory issues on microfluidics. In particular, what is microfluidics and why is it important, what are its various applications and what are some distinguishing features from the classical micro, classical macro flows. So, this we discussed very briefly, of course we will be elaborating on these concepts throughout this particular course and slowly but steadily we will proceed into the theoretical description of microfluidics. But before that, we will be discussing about certain examples. Now, why we discuss about certain examples is because many times when we are learning a subject, we do not have a big picture, we do not have a motivation. Like for example, like from the first day, if I start deriving Navier-Stokes equation, you will try you will start believing that I mean we are forced to learn the derivation of Navier-Stokes equation or the derivation of some other equations related to microfluidics I am just giving Navier-Stokes equation as an example that we will be going through these things with a purpose. So, not just because we have to learn this and this kind of learning objective is very very important. So, we will try to look into the issue from a somewhat application perspective that what are interesting applications, what are the outstanding problems that remain to be solved in research, what are the outstanding industrial problems that need to be considered. So, by keeping all these in view, we can go for microfluidic studies for scientific level understanding for deep technological development and even for societal issues and we will talk about these as time progresses. So that is why I thought that before getting into the mathematical equations and the mathematical details, let us talk about some examples. So, I will talk about some examples may be possibly in the next couple of lectures where I will not get in get deep into the examples because I will try to get deep into the examples with their mathematical background and all those things for the remaining over the remaining part of the course. Since we have not yet developed the full theoretical basis of going through these examples, we will better sort of appreciate these examples from like from a common man's perception that right what are the interesting facets that these applications have and how can microfluidics solve these problems. So, most of these problems are of like interesting practical oriented nature, I mean these are not hypothetical abstract problems, these are practical problems. Many of these problems are addressed by my own research group but I will also talk about a couple of problems which are not touched upon by our own research group but are addressed by leading researchers worldwide. So we will start with that, so some illustrative examples, as I told you that in microfluidics we have broadly 2 types of applications bio and non bio, so when we say that it means that biological applications are quite significant and interesting. So I will talk about one biological example and I will try to demonstrate that we start with describing a biological problem but how fluid mechanics is coming into the picture, fluid mechanics over small scales to address this problem. So this problem is about DNA hybridization. So what is DNA hybridization, I will try to talk in a very simple terms and when we talk in simple terms there is always a danger that you oversimplify the problem. So please pardon me if I am oversimplifying the problem, this is just for the sake of your own understanding at this level without getting into too much of a depth. So let us say that, well before getting into the DNA hybridization let us get into the structure of a DNA. So DNA as you know has double strand, double stranded structure, so each single strand is associated with a phosphate group which you see here, phosphate group which is responsible for the negative charge of the DNA, a sugar and 4 bases, nitrogen containing bases, A, T, C and G. So if you look into the backbone of DNA strand then you have alternate sugar and phosphate group and with each base binded with the sugar that you see in this second panel. So what it means is that a single stranded DNA is structured like this. Now how a single strand mates with another single strand to form a double strand? That is possible because A wants to get combined with T and G wants to get combined with C and this tendency is there because of hydrogen bonding. So that means that you have a double strand like this where you see this kind of mating is like A mates with T and G mates with C. So this is the structure of a double stranded DNA. Now how can we use this for detection of a disease? How can we use this? So let us say that like some disease, let us say some arbitrary disease I do not want to mention any specific disease has some DNA sequence associated with it. Let us say A, G, T, C, G, G, T, A, C, C whatever some kind of sequence if that is there in the DNA then we will ascertain that yes this particular disease is there in the sample. So to do that to identify whether that sequence is there or not we can put a complement of that sequence on the wall of a channel because if that sequence is there it will mate with its complementary sequence and if this mating is successful then we say that that single stranded DNAs have hybridized to form a double stranded DNA. So this is what is DNA hybridization. Now how can microfluidics come into the picture here? See DNA hybridization typically so typically what you can do? See first see consider all these processes like first you have to break the cell and bring the DNA out of it. This process is called as cell lysis. So you break the cell and bring the DNA out of it this can be done even mechanically okay. So it can be a pure mechanical process that does it. Then when you break the cell and bring out the DNA then what you can do? You can heat the DNA because what you want? You want single stranded DNAs. So the DNA is double stranded so by heating the double stranded DNA can break into two single strands. This is known as DNA melting. This is a very typical name. So why this is called as DNA melting or DNA denaturation but melting is also a common term used. Why it is called as DNA melting is because it is like a phase transition process which resembles the melting process just like melting of ice thermodynamically. So you can see that there is a biological process which really has nothing to do with melting of ice or melting of a substance. But notionally the thermodynamics may be somewhat related. So biological processes are also interesting processes involving good amount of physics, chemistry or other fundamental aspects of science. Now but let us not get into that. So that single stranded DNA is passed through the channel and on the wall of the channel you have the sort of the capturing DNA probes. The capturing DNA probes are those which are complementary of what you really want to capture. What you want to capture is the target DNA. So you can see here that you have a test sample you have target DNA and these are capturing probes. Target DNA if that is the sequence that you want to interrogate then that target DNA will bind with the capturing probes and there will be successful hybridization. But how it will bind? It will slowly move and it will go to the reaction sites. The reaction sites are the walls. So it is a diffusion process and as we all know that diffusion alone if it takes part is a rather slow process. So diffusion is a rather slow process and like it typically like say the diffusion coefficient of the single stranded DNA of course it depends on how many base pairs are there and so on. So I will not quote any particular number but let us say it is typically of the order of 10 to the power-11 meter square per second. So it is very slow. So the DNA the single stranded DNA will take a long time to reach the reaction sites. So that means that essentially means that for disease detection a long time will be taken. So you want to make rapid DNA hybridization. So to make rapid DNA hybridization what you want to do? You want to accelerate the movement of the DNA. So even without applying fluid flow you can do it. How you can do it? Let us say that you apply an electric field. Why electric field is important here? This has something to do with the DNA structure. We have already discussed that DNA has a phosphate group. The phosphate group is responsible for the negative charge in the DNA. So because the phosphate group is responsible for the negative charge in the DNA if you apply an electric field the DNA will move because of the electric field. So like this is called as electrophoresis. So if you have a charged particle see the DNA is not a particle. So see we will study later on electrophoresis in this particular microfluidics course. So I am just giving you a motivation that why study electrophoresis out of so many things. See it will give you we will study electrophoresis of a sphere in a flow field. So when we study electrophoresis of a sphere see DNA is not a sphere but many times DNA is modeled with an equivalent radius of gyration. So you see that this is what is mathematical modeling all about. There is a physical reality you cannot you cannot represent the entire physical reality by a mathematical description because the physical reality is very complex. So what you try to do you try to simplify the problem and represent the essential physics in terms of some mathematical equations boundary conditions and so on that is what is mathematical modeling and simulation all about. So we are not in most of the cases representing the actual problem that is why we call modeling. See it is not the actual problem it is a idealized representation of the physical reality and when we do that we have to keep in mind that the I mean the actual geometry and all those things may not be well captured. So we can apply an electric field and the DNA will move but there are several issues associated with the use of electric field which may not be so advantageous. So it might accelerate the DNA movement but there may be several other features which are not which are not so favorable. I will not elaborate on those features now because we will discuss about these in more details as we progress in the course and as we discuss about biomicrofluidics we will talk about those things that what are the positive and negative consequences of applying electric field on a DNA sample we will talk about that. So but here we try to see that well electric field being not being always the most favorable solution let us consider some alternative mechanical means pure mechanical means of accelerating the DNA transport. So this is a research problem on which we worked in a collaborative project with Professor Mark Madhu's group in the University of California at Irvine and I mean it was funded by one in the US research program and what we proposed and was something like this. So I will just run a movie which will which is showing that there is a flap there is a flap which is oscillating on the wall of a microfluidic channel this is a flap not made of a rigid material but made of a flexible material called as polypural. So this flap is flexible and what it is doing is when it is oscillating it is oscillated by an actuator the actuator may be electrical actuator. So when it is oscillated by an actuator the fluid which contains the DNA sample is being you see that because of its oscillation it is being targeted towards the wall. So this oscillator is acting simultaneously like a mixture and a pump. So it is sort of directing the flow in a certain direction. Now when it is doing that is it satisfying the entire purpose you see that if you look at this this view graph you will see that there may be various DNA test sites not just one single DNA test site because you may be interrogating several diseases with one particular sample. So there may be several target sites so if all the DNA falls on one site then the next site will not get the DNA sample from the solution. So you want to make sure that all the sites get the requisite amount of DNA from the sample. So how do you do that? To do that what you do is instead of using a single flap you use multiple oscillatory flaps and the design problem see you see when you use multiple oscillatory flaps then all the DNA does not fall here I mean the DNA I mean here in this example just 2 flaps are shown but it could be n number of flaps and it is very important as a design problem and this is the pure CFD problem. It is important as a design problem that what is the amplitude of oscillation, what is the frequency of oscillation and see in terms of a CFD problem it is not a very straight forward CFD problem. These kinds of problems in CFD are called as fluid structure interaction problems. So there is a structure which is an oscillatory structure the fluid is interacting with it but the structure is a flexible structure the structure is not a rigid structure. So the flexibility of the structure plays its own role that alters the pressure in the surrounding fluid that pressure alters the flow field and that flow field in turn dictates the oscillation I mean in turn influences some of the oscillatory characteristics of the flap although it is in addition externally controlled. So there may be a 2 way coupling between the flow and the structural motion and this kind of problem has to be approached by considering the mechanics of solids and mechanics of fluids over small scales. So what I want to impress upon you is that to design this kind of setup see we started with when I first started narrating this problem many of you might have been frustrated because we started with phosphate groups, sugar, base all these things I do not think that many of you have come to engineering to study phosphate group or sugar or base or this kind of things. But when we went into the final solution of the problem you see we are talking about the fluid flow equation, the structural mechanics equations, the CFD and all those things and many of you I believe are interested in these areas. So you see this is what is the modern outlook of engineering that you can use engineering skills not just to solve traditional engineering problems but some problems of these kinds and this is one of the very important applications of micro fluid. Let us get into a second example. Let us again prepare a little bit of background of this example before we get into this example. In many scenarios even in classical fluid mechanics we are bothered about that how to drive a flow like as engineers we are very much bothered about how to drive a flow through a system. So when we say that how to drive a flow through a system we essentially mean that right what is the mechanism by which we drive the flow for example in the large scale system we require pumps to drive a flow and of course what is the penalty that we have to pay to get a particular output that means say what is the pressure drop that takes place for a particular flow rate something like these are very common facets which we tend to address when we are designing transport system that not just a classical system even in a micro fluid system these are important just that we may not use classical pumps we may use pumps I mean which are like typically say syringe pump peristaltic pump we will talk about these pumps and I will show you demonstration examples of these devices. So these are like I mean these are not pumps in the very classical sense but these are like pumping devices which can actuate fluid flow. But now many of these devices have their own shortcomings like for example these devices have mechanical components and mechanical interaction like say frictional interaction for example these are associated with losses and in a small scale system these losses are very significant like if you recall I mean we will again get into all these because I can understand that there may be some students here who may not have a comprehensive background in fluid mechanics but just to like reiterate that at least if you have if you if you recall the fully developed laminar flow through circular pipes for example. So the head loss is given by the Hagen Poiseuille's equation. So head loss is inversely proportional to the fourth power of the hydraulic diameter. So that means if you reduce the hydraulic diameter from 1 meter to 1 micron see you see how by how many times the head loss increases. So with that very significant head loss and with also like mechanically moving components working unfavorably over small scales you need to look for alternative strategies of driving the flow and that is where like a big whole lot of activities are going on in the area of alternative flow driving mechanisms in microfluidics like flow driving by electrical field for example and we will discuss in length in great details about how to drive a flow by electric field and entire science and technology behind that it is a big part of this particular course. But we have to understand that the electrical field also has its own limitations. So can we go for alternative techniques? So I will show you one example where we can move water by light by optics. So how it is possible? So let us let us consider an example. Let us look into this T shaped microfluidic channel. So T shaped micro channels are very commonly used for droplet generation because if you are passing some fluid then at the junction because of shear the continuous fluid may get broken into droplets. This is one of the mechanisms of droplet generation but here in this particular example we will not focus on droplet generation but something else. So let us say that we are injecting the fluid say deionized water from this bottom of the channel now it enters the junction. Now we have to decide that whether we want to transmit the fluid towards the right or towards the left.  So we have a logic. If the logic says we want to move towards the right it will be moved towards the right. If we say that if we want to move it towards the left we will do that. So how we do that is essentially something like this. We quote this top inner surface of the microfluidic channel with a metal oxide semiconductor. So the metal oxide semiconductor is like zinc oxide, titanium dioxide like that. These are typical examples. Now these semiconductors have energy gap roughly if I remember correctly around 3.2 electron volt. So and that falls within the regime of actuation of ultraviolet light. So if ultraviolet light shines on these semiconductors then electron hole reactions will automatically start. So when electron hole reactions will immediately start then these are competitive reactions. So the surface will eventually have either excess holes or excess electrons. So no matter whatever is there the surface charging state will change. And when the surface charging state will change the surface energy will change. And when the surface energy will change eventually that will be reflected in terms of an altered weightability of the substrate. We will get into the physics of this I will discuss about the details of this later on. So once that happens a surface which was originally hydrophobic may become hydrophilic. So that is what we intend to do. It is a very simple physics. So what we want to do is when the water comes here and we want to move it towards the right we shine ultraviolet light here. When we shine ultraviolet light here this part which was earlier hydrophobic will become hydrophilic and water will move towards that direction. If we want to stop that we will just switch off the light. If we want to move the water towards the left we will shine the ultraviolet light in this part of the channel. So what will essentially happen is that we can have a control over the flow by light. We can have a pattern of the flow. In microfluidics many times creating patterns of flows is very important because I mean as I told in the previous lecture that it is it may be very challenging to achieve a turbulent mixing in microfluidics because of low Reynolds number. So it is if you can create local vortices and patterns in the flow by some clever means even in a low Reynolds number flow that may be important for various applications. So that kind of pattern you can make by making a substrate making a surface which has patches of say this titanium dioxide or zinc oxide. So it will make a surface passed with alternative hydrophobic and hydrophilic zones. So that will create a pattern of flow on the substrate and this flow you can switch on and off by switching on and off the light. So you can have a combined spatial and temporal control on the flow that is a combined position independent and time dependent control just by switching on and off the light in a non-intrusive manner. So this kind of device that is shown here this we call as an optofluidic device. So this is just to show you as I told you in the previous lecture that microfluidics is an interdisciplinary subject because it is an interdisciplinary subject. It interfaces with many other aspects of say physics, chemistry, even biology and so on. So this is just an example to demonstrate that how microfluidics interfaces with say optics for example. Now the next example that I will talk about has a little bit of motivation. As I told you that droplets are important in microfluidics and we are interested to study droplets because I mean with droplets you can achieve certain things. For example with droplets I mean you can have two droplets say droplet A carrying a reactant A, you can have a droplet B carrying a reactant B and droplets A and B when they merge together the A and B rapidly react because of large surface area to volume ratio it is a highly active system the A and B rapidly react to form the product C. So droplets can be thought of as micro-reactors not only that you can bring a droplet to a hot spot and cool the hot spot because the droplet can take the heat from the hot spot and get evaporated. So droplets are very important entities and sometimes droplets can be thought of as carriers of information in information technology I will talk about that. So in a nutshell droplets are very important. Now how does a confinement affect the motion of a droplet or the dynamics of a droplet? Why is it important? See always when we want to solve a problem right if you are say think about a child when you start thinking about writing when you you do not immediately start writing an essay as a child you first learn alphabets then you learn how to make words then you learn how to make sentences and then you learn how to make collection of small sentences to give a meaningful idea. See that is how our education proceeds as we grow up. Similarly in research also we address problems in this way I will try to again like to give you a I will again like to give you a big picture. Let us say that we are interested to solve the problem of dynamics of a cell in a confined environment. I will discuss about why dynamics of a cell in a confined environment is very important and again this will happen to be one important aspect that we will cover in the later part of our course. Now when we are thinking of dynamics of a cell in a confined environment let us say a cell in a blood vessel. Now the cell is not a droplet right. See as a fluid dynamist if I am asked that please make a mathematical model of a cell and I know nothing about it. I will first try to relate that with whatever I know. This is how many times people start doing research and this is please do keep in mind that this is not a very bad way of doing research. That is sometimes you oversimplify a problem but you start with some basis which is comfortable to you. So as a fluid dynamist I am much more comfortable with a droplet than with a cell. So I start with a droplet. So when I start with a droplet I very much appreciate that there is no real comparison between a droplet and a cell. I mean cell is entirely a different entity as compared to a droplet. But a cell like a droplet deforms but there are certain aspects which are different from the deformation different as compared to the deformation of a droplet and deformation of a cell. We will talk about all this but to begin with we can study with the dynamics of droplet. So with of course the motivation of studying the droplet dynamics itself which has important applications in microfluidics as I told you micro-reactors or cooling applications. I mean droplets have their own applications or it is even for a big picture that yes at the end even if we want to study dynamics of cells we may have a basic building block by starting with droplets. So that gives a motivation of studying droplets in a confined system in a microfluidic system. So but how do droplets behave in a small scale system? So to make an understanding of that what we did is we try to make a map of the dynamics of droplet as a function of the contact angle and time. So remember I mean we will define the contact angle formally later on as we study surface tension and all these things. But just to give you a basic idea that a small contact angle means it is a hydrophilic substrate that means the surface likes water and the large contact angle means it is a hydrophobic surface. So the surface does not like water I mean it is the more scientific terminologies are lyophobic, lyophilic and all this because hydro when we say we commit to water but I am just again I am telling that I am not trying to be over technical when I discuss about these examples because these are just to create motivations in your mind that why do we go for studying microfluidic rather than getting into the in depth science. We will get into the in depth science immediately after we complete going through these examples. So like if you see that now if you have small if you have low value of the contact angle what happens the surface likes the drop. So this is a this is an example where we are thinking of a shear flow, quet flow that is you have flow between 2 parallel plates and one plate is moving relative to the other this creates a shear in the flow. So when you have this shear flow then because of shear the droplet will try to be deformed but on the other hand because the surface is liking the droplet because it is a hydrophilic surface the droplet will still try to stick to the surface. So what will happen is something which will happen is called as pinch off. So in the pinch off what is happening is that a part of the droplet will remain on the surface and the part of the droplet so first there will be a ligament formation like this. And this ligament formation because of high stresses in the ligament it will eventually break and it will sort of set apart from the original volume which is sticking to the surface. So this phenomenon is called as pinch off. On the other hand for large contact angles you do not see this pinch off what you see is that because the surface does not like the droplet or the droplet also does not have an affinity to the substrate what will happen is that it will simply detach from the surface. So you see that there is there are 2 important aspects of dynamics one is pinch off which is occurring at typical low contact angles and another is detachment which is occurring at higher contact angles. And there is a critical limit at which there is a transition from one type of dynamics to the other and it depends on so many factors. So I mean the essential objective of the study is to like assess that like how these are affected by various factors including the shear rate or even like the sort of the rheology of the fluid and so many other considerations. Now the previous in the previous case we studied the sandwich droplet. Now here we are studying an adhering droplet. Why we are studying an adhering droplet? Because again I told you that one of the big pictures is to study the dynamics of cells. So when you study the dynamics of cells you have to keep in mind that there are many cells which adhere to a microfluidic substrate or when the cells adhere to a substrate so this is the first point. The other distinguishing feature between the this study and the previous study is that we are considering instead of a linear shear also an oscillatory shear. Oscillatory shear why oscillatory shear?  It is oscillatory over time. So to mimic that mimic the shear in that flow we can make an engineering device where instead of giving a say motion of one of the plates in one direction instead of giving it is a velocity u equal to u1 towards a particular direction we give it a velocity u u equal to u0 sin omega t or cos omega t so that it is oscillating with a particular amplitude and frequency. So we can see that we can see the difference in the dynamics as we go from linear shear to oscillatory shear. I mean these movies are showing that what are the interesting dynamical features. Now as I told you that it is not just the droplet that we are interested to talk about. We are having a broader interest to model biological cells. So when we have a broader interest of modeling biological cells we have one step which is sort of in between because cells are very complex cells are very complex. So before modeling cells one can go for one step of advancement from a droplet that we can consider something which is called as a vesicle. Vesicles are not droplets but they are not cells. Vesicles are fluid enclosed by semi permeable elastic membranes.   So it is not just the water but it has a membrane. So if you consider the elastic membrane this membrane in addition to the properties of the fluid within the membrane it has bending rigidity, it has elasticity, it has membrane incompressibility. So these are some of the additional facets beyond the mechanics of fluids that you have to consider to model vesicles. So that is the second step. But is that all? Now if you consider a cell, a cell is also having some properties which is like the cell has a cell membrane which is having these kinds of properties that is the elasticity, bending rigidity, membrane incompressibility all this. But there is a very important aspect and this is I think the ultimate question that the CFD for biological systems is yet to answer. The cell has life but a balloon filled with water has no life. So if you have a living system, a living system responds to a stimulus in a particular way which depends on so many living activities within the system that cannot be mimicked by a dead system. So obviously when you are considering a CFD model of a living system you have to consider these kinds of aspects of a living system, the scientific features of a living system which include some of its activities and these activities may be best represented by coupling thermodynamics with fluid mechanics. So you can have the free energy of the system. See the cell and inanimate say like a balloon like body filled with water may have in an idealized condition similar mechanical attributes. But whatever has life will have certain additional free energies to sustain its living activities and these free energy considerations need to be properly coupled with the mechanics of fluids and that is where actually the future of CFD for biological systems should lead to. So that is I am many times you will see that during the course I will talk about several things which are still outstanding problems and I do not mind to do that because like I mean typically as a teacher many times I get upset with the education the way the manner in which we impart education to you that as if we know everything and we want to tell you what we know but there are many aspects there are many things which are yet to be solved or maybe there those have been solved by me some people recently but I am not very much aware of that. I think as a teacher it is my duty to let you know that what are the outstanding problems what are the very interesting yet to be solved problems what are the challenging problems. Now it is up to you whether you get interested in that and you take that up as one of your future activities but it is not my responsibility as a teacher just to read what is there in a reported book and tell that to you that that is the end of end of the scientific activity in these areas not like that. So what I am what I have just mentioned is an outstanding area of CFD not many CFD practitioners do that because if you just like start solving the Navier-Stokes equations as they are in their form in their routine form it is not possible to like take these aspects into consideration. So you have to have a nice coupling between thermodynamics and fluid mechanics that has also been addressed but the thermodynamic model still it is a it is an open question that how to make thermodynamic models which mimic all the living all the aspects of a living system which it is not as straightforward as this and one has to get deep into the biological applications of thermodynamics to get a get a clue towards answering these questions. So this is what is an interesting area as I told you that eventually our objective may be to study the dynamics of biological cells I mean we may study droplets independent of this interest for the interest for the sake of interest on droplets or even vesicles but when we are thinking of biological cells I mean I mean these are not just complex droplets. So we have understood that cells are not just like complex droplets cells are complicated by their own by their own merit not you cannot just think of a cell as a very complex droplet. So this is an example where we are thinking of the dynamics of a cell now why I mean again I am trying to give you a big picture that why is this important see like in this in this few introductory lectures my one of the objectives is to tell you that why are these problems important why should we study at all these problems. So if you think of I am giving you one example I mean there are many examples for which we should study dynamics of cells in a microfluidic confinement and again we have a chapter on this later on. So we will discuss about that much more details than what we are doing now but just think of a think of a problem all of us know that the progression of cancer becomes lethal the progression of cancer becomes lethal when the cancer cell from its origin moves to a location within the human body by the bloodstream and creates a new cancerous growth at a new location and how is it possible that the cancer cell moves by bloodstream and this process is known as metastasis. So this is one of the very critical stages of cancer progression. So I think a large number of deaths in cancer can be prevented if this metastasis stage may be arrested. So there are several like medical ways of looking into the problem but we try to see that what is the fluid dynamics way of looking into the problem. This remained an outstanding problem and what I will discuss I mean little bit now and elaborately later on is a work of one of my PhD students. So like when the cancer cell moves through the human body it moves through various blood vessels of various sizes and one of the typical blood vessels is the micro capillary. So in the human body as I told that you have large arteries, large veins, small arteries, small veins, arterios, venous and you have micro capillaries. Micro capillaries are like sort of I mean naturally made micro channels. So in these micro channels what happens when the cancer cell moves or even when a normal cell moves it is a highly stressful environment.  So what is the physical mechanism that is going on in the cancer cell that is allowing the cancer cell to survive so nicely in a stressful environment. What if we understand this mechanism maybe certain drug can be introduced to combat that mechanism and then progression of cancer can be prevented. This is a pure fluid dynamics outlook of cancer progression. This may not be related to the traditional medical outlook of looking into cancer. So like how we do that is basically so this is a cell which is adhering to microfluidic channel and when this cell is adhering to a microfluidic channel what is happening when the cell is adhering to the microfluidic channel you have various I mean these are the legs of the cell which we call as focal addition points. These are the legs of the cell.  When you feel destabilized on the feet that is what happens to the cell also. The cell feels destabilized here so these focal addition points are disturbed or disrupted. Now that is how the cell gets a message that yes I am subjected to a stressful environment. So when that message comes that message then propagates by a very intricate mechanism to the most distant part of the cell membrane which is called as apical cell membrane. So in a cell membrane there are two types of entities one is called as lipid which is like a fluid you understand lipid and then something which is little bit solid type which is called as lipid raft. So when this stressful environment is there one possibility is that how the lipid raft will adjust to the stress it is a mechanism which is very obvious. The lipid raft what it will try to do it will try to go from cell membrane to inside the cell. So many times I tell my students that the analogy is something like this. Say I am residing in an apartment now say suddenly decoys have attacked my apartment. So I am not a very brave person like many of you. So what I will do is I will try my best to save myself first and hide in the bathroom. So what will happen to the lipid raft is also something like this because of the highly stressful environment they try to escape from their original location and go to inside the cell from the cell membrane or otherwise if they still want to remain that maybe with a very high stress they may break. So whatever may be the possibility the eventuality is that the cell membrane becomes more fluid because lipid raft is more solid type and that has that the cell membrane is depleted of that now. So because it is more fluidic it is more malleable it the cell can then reconfigure its shape and by that it can sustain a large amount of stress. This mechanism is there both for cancer cells and normal cells but we have found from our research that this mechanism is more prolific in cancer cells than normal cells and that makes the cancer cells survive in a highly stressful environment as compared to a normal cell. Now we have studied this in a microfluidic system. Why we have studied this in a microfluidic system is because in a microfluidic system you can make micro channels which resemble this micro capillaries but when we make micro channels that resemble this micro capillaries and we talk about the dynamics of a cell we can isolate the dynamics of we can isolate a single cell the length scale of a typical cell in a human body is let us say of the order of 10 microns. So when you are thinking of a microfluidic channel you see the length scale is compatible with that of a biological cell in a in a human body. So that makes it possible that you can address individual cellular length scales. So you can focus or isolate on a single cell and study the dynamics of that and in that process if you can understand that how the dynamical features including some fluid properties like the membrane fluidity. We will discuss about that the fluidity of the cell membrane and how is it changing how is it different from different for a cancer cell as compared to a normal cell. If that can be well understood then it is possible that the mechanism by which the cell adapts to the stressful environment that mechanism can be disrupted and if that mechanism is disrupted that will sort of arrest cancer progression. So this is a pure fluid dynamics way of looking into cancer progression and that can be possible if we are making control studies in microfluidic environment. So these are some of the sort of very interesting and outstanding problems that we may consider like most of the problems that we have considered today are of biological applications. But as I told you that these the applications of microfluidics are not purely confined towards biological application but because biological applications are quite a lot. I thought that I will better give you some very interesting examples and I mean of course we are running out of time in today's lecture to continue with the remaining examples. So we will discuss about the remaining examples and those examples some of those will be biological and some of those will be non biological but I mean we will try to cover various aspects of microfluidics and just like we have covered some biological applications we will cover some more biological applications and some energy related applications because biology I mean the healthcare and energy are two very interesting areas of modern day science and engineering. So I will talk about energy related applications that is where microfluidics comes into the picture. Anyway we stop here today I mean for this particular lecture thank you for your attention and we will continue with these examples as we move as we meet next time thank you.


Hi, I'm Ricky. I'm a front-end developer at previous next and this session is about lazy loading and how to apply that to partially to couple projects Lazy loading isn't new, but let's do a quick recap. We're talking about the loading of render blocking resources being CSS and JavaScript non-critical being, you know, roughly below the fold and Basically being more targeted with what and when we load things And not lazy loading things that are above the fold which can have negative results It takes a bit of work to do so why bother, you know performance Good performance has so many added benefits How many of you have just given up and closed the web page because it took too long to load? Especially during your mobile phones or at times when you have poor internet connection In this industry, we tend to have good internet and good devices, but we're certainly not the norm, you know There's a link on my resources slide to a series Jake Archibald did on the formula one Comparing formula one websites. It's really good. There's like really good before and after page load Videos that Really explain how much of an impact this can have There's some basic principles that apply. I'm kind of gonna skim through these. There's tons of info on this online So style sheets are render blocking you want to determine critical or above-fold CSS and in line it and then once you've done that you can defer the rest with JavaScript attribute-stopping And use your library system to reduce the unused CSS on pages JavaScript is also render blocking again determine like really critical JavaScript is if there even is any Maybe in line it. This is a bit touchy in triple Definitely defer the rest to load asynchronously where applicable ES6 modules are great They're deferred by default and when you combine this with code splitting and again using Drupal's library system You can really reduce the unused JavaScript on page Media can slow down pages as well. The loading lazy loading attribute is gaining support in both Drupal and in browsers Image definitely has the widest support You definitely just use the native implementation for images. Don't use JavaScript and don't lazy load images that are above the fold like hero images or you know Always put a height and a width attribute to permit layout shift and use the responsive images module What else can be lazy load and how we're just going to talk about the intersection observer API Here's some nice techie language The purpose of this talk we just mean tell me when an element has scrolled into or out of view These aren't new. They're around five years old, but I didn't support them So usage was less than it should have been And yes, no code in this presentation is going to work.  So let's just use it as an example for how to do a basic Intersection observer lazy loading scenario For our HTML, we've just got a data source instead of a source attribute. So nothing at this point is going to load Quick caveat, I don't actually recommend this for iframes maybe if you have like a massive amount of Firefox users and The content in your fames is really important and you want that to load fast and then do the intersection observer approach otherwise just The native implementation is still going to be quicker for everyone else So this scope will just make a really quick reusable JavaScript function that takes an element We create an observer just with the default settings and we start observing the element, which is that last line We live through the results and grab the is intersecting property is Intersecting returns true just as the element hits the bottom of the viewport and you can increase or decrease this point with the settings We populate the source at which point the iframe loads and Then we unobserve the element, which is important. Otherwise, this keeps firing, you know as you scroll up and down the page The usage is simple. We just find all the iframes with data source, but not source And load call the lazy load function But let's get more interesting. Let's say we've got a normal Drupal side. We've got some JavaScript apps embedded here in there They could be written in react or view or whatever. They may fetch some JSON data from Drupal or elsewhere They may load their ncss and they may be multiple of these apps on page How this normally loads is you visit a page all the apps and their dependencies load This is JavaScript on possibly JSON and CSS And this repeats per app Even if it is deferred, it's not render blocking. Hopefully But users who don't scroll to it still downloaded and the initial load time is longer So how can we improve this we take our intersection observer and we combine it with dynamic imports to To only load resources once they scroll interview and this can significantly reduce the page load times And yet bonus points if you also use dynamic imports inside of Europe So we make another reusable function with an intersection observer and an asynchronous load function takes container element a component pastoring a props object and an optional callback function The load function dynamically imports the app component, you know and plus whatever we need to render it We use the dynamic import syntax to load our modules Dynamic imports return a promise. So we use promise.org to ensure that all of our dependencies are met And we can add error handling in here too is catch Then we step through the results of each import. We do structure render from the rack DOM import React just needs to be included at this point. So we just import it as well and We take the default export from our component path argument and call it something generic like component or app And then we render it passing in our props our container and our callback function The load function you can adapt to your needs. The basic premise remains the same if you free example and 18 example The observer down the bottom is the same as our frames one. It's just the default settings. Nothing fancy It just calls the load function instead of swapping attributes over Usage was looked something like this you find your unmounted container diff Call our lazy load function and set its arguments The HTML element to render to the path to the specific component are up to use The prop subject which can be simple values data attributes or durable settings and The callback function if needed. There are some accessibility considerations here. We take has findability rules for hidden content I like to add a heading and a button inside the container that triggers the load function And this just gets replaced by the rendered app anyway So you need to think about how important the content in your JavaScript app is Is it shown elsewhere or can it be and is the app itself successful as well? And also think about what should happen if JavaScript isn't enabled There's some UX improvements that can be made as well So the intersection observer as I said has a lot of fine-tuning options to change when Support things like a sticky header offsets and stuff like that There are also great candidate for a simple skeleton UI Just give the container a great background and a height and a width This prevents layout shift issues and makes the jump of the suddenly rendered app less jarring And don't forget to notify the user if something has failed to load The observer API is more performant than listening to window scroll events So really any JavaScript that does that now you can improve by converting over to an intersection observer Then when browser world is full of observers There's the mutation observer that listens to DOM changes like attributes or markup or content injection the resize observer listens to element dimension changes and It's also a more performant version of the window dot resize event And they all follow the same observe unobserved pattern. So once you get your head around one of them the rest is it pretty easy to master So quick recap performance really matters and observers are more performant than the older methods Dynamic imports are a great way to progressively load things So think about what else can be lazy loading lazy loaded inside and outside of your apps Um Lee's talk tomorrow is called improving core web vitals. He goes into more specifics about how to do this stuff in Drupal resources and Anyone any questions? Can I ask about the Google indexing? because I always found that when you Hide stuff and Google can't run a JavaScript, right? So yes, yeah failing to index our content and that can affect SEO negatively. Yes. Yeah So that's the thing if there's like really important content in those apps you want to sort of You can either make sure there's another way that it's on the page Maybe even just visually hidden sort of content. That's pretty simple and easy to understand It really depends on what the app does and what's inside it. Yeah


Oh, it's on now, hello, wow, oh my gosh, I really, I can't really see you, these are really bright lights, I can see the first two rows, you're very beautiful, thank you for sitting up front, appreciate that, I'm Lisa, I met a few of you, I always like to know who's in the room and who we are speaking to, come on in, there's some seats in the middle and in the front, and it sounds to me like we have a mix of people in the room, but I'm just gonna ask, because I didn't get to talk to everybody, show of hands, who here is a software developer? Okay, how about operator? Ooh, good, and architect, good, and what did I forget? Goat herder, no one? Oh one, excellent, okay, cat herder, no, no, that's my job, and I herded some awesome cats for this panel, look at me grabbing all the keynote people, oh my gosh, I mean a main stage isn't big enough for a small, our little main stage I guess, I don't know what I'm trying to say, it's really for me in some other time zone, okay, like I was saying I'm Lisa and I have been with OpenStack for many years and also Kubernetes from the beginning, I live in the San Francisco Bay Area and I run the OpenStack user group there and now the Cloud Native Compute Foundation's largest user group as well, and having done 19 meetups on Kubernetes in the last two years, I've gathered a lot of information from the community and from a lot of customers, I work at Portworx, we also have a lot of customers, we help people run stateful applications on Kubernetes, which is a really fun day two challenges, fun problems to solve, so I've been in the Kubernetes world for a while and I've been in the OpenStack world even longer and I have gathered some of my absolute favorite people on the planet, those of you who looked at the program and saw Tony Campbell, Tony sends his apologies, he could not make it to Berlin and so it's not a backup plan, it's probably an upgrade and Tony's going to watch this and he's going to agree with me, but Joseph wore a CoreOS shirt just in Tony's honor, I noticed. I had to recognize him. Yeah, I saw that, Joseph's actually with Adobe, not CoreOS, but we all love that shirt. That was what, three companies ago? Cross that out, put Red Hat, cross it out, put IBM. Okay, all right, I'm going to let these guys introduce themselves. Joseph, how do you start? Sure, I'm Joseph Sandoval and I am with the Adobe Advertising Cloud. Everything I'm telling you today is my own opinions and experience. This is actually my second go round with the company I'm currently at. Previously I was at a company called Lithium where we did OpenStack, but if you were at the Tokyo Summit, you probably saw us in our early nascent attempts to run Kubernetes on top of OpenStack and so I had a lot of lessons learned from that, as well as currently at the Advertising Cloud. We're also now deploying Kubernetes along with OpenStack. Hi everyone, I'm Mohamed. I'm a big part of the OpenStack community. I'm the vice chair for the OpenStack Technical Committee. That's kind of, and community-wise, I'm the project team lead for the OpenStack Ansible project. It's a project that allows you to deploy OpenStack. But on the commercial side, I'm the CEO of Exos Company that provides public private clouds and consulting services and we've had a lot of experience in helping our customers deliver Kubernetes on top of OpenStack. So really how to bridge the gap and make it easier to get Kubernetes deployed on OpenStack using things like Magnum, but also making Kubernetes better integrated with OpenStack such as with things like the OpenStack Cloud connector, which allows you to create things like sender volumes for your persistent volumes and things like using the load balancer resources and integrating them with Octavia. So a lot of my experience comes in how to move away from having two systems working independently and making them more working together so that it makes operators' lives a lot easier and making deploying Kubernetes a lot easier for them because on its own sometimes that's quite the task. Great. I'm Robert Starmer. I run Community Technologies. We're a technology consulting company that helps people figure out how to get the right cloud put in place. So whether that's something like OpenStack or Kubernetes or a combination of the two, we look at making sure that you're getting the right solution. And obviously the more important part even beyond that is figuring out how to make the best use of those resources. So getting the system in place, getting it operable as part one, but then actually being able to consume it from a development perspective is really the other aspect that we help people do. Okay. And there's still a couple of open chairs if you guys don't want to sit on the floor. Now would be the time to crawl over your fellow colleagues and grab one of those open chairs in the middle of some of these rows. Okay. So we have a nice mix of people in the room and we will have something for everybody here. The questions will go from here to here. So just hang with us. We also want you to ask questions yourself if you can crawl back over your colleagues and get to one of those microphones. And if you can't, you can let me know. I'll hop down and pass this one around. These are our Twitter handles. So you can tweet us questions now. Some of you have already started that. Thank you very much. That was very funny, by the way. I appreciate the jokes you guys are throwing at me as well. They come through on my watch. But anyway, we'll keep the conversation going. I actually opened my DMs. Very courageous move. And so I will keep them open, at least throughout the conference or at least until I get spammed by people and that starts driving me nuts. And that will probably be about 24 hours. But anyway, if you follow me, I'll follow you back and we can keep this conversation going. It doesn't have to end 40 minutes from now. Well, let's start by talking about Kubernetes. Let's talk about just getting started. You know, some of the installers. And I'm going to ask this one to Robert because he's out there in the real world putting this into customer sites all over the world. So probably, of everybody, the most experience, we live in the fake world. We work for companies and we just get to play with software all day long. But Robert's in the real world kicking the tires. So can you talk about getting started? Well, yeah, I think there are a couple of different approaches. I think the first question you have to ask yourself is, do you want to do this yourself? Do you want to operate the Kubernetes infrastructure directly or do you want to work with a cloud provider and have them provide you with a Kubernetes service that you can consume? You've made that decision and that is driven usually by the technical competence of your team and not that they're incompetent. But is this really something that you want your team focusing on is sort of the first question that you have to ask. Because the installation process, if you've already gone through the pain, for example, of working through and getting your team up to speed on OpenStack, adding Kubernetes is actually fairly straightforward compared to that. But it is still more operational load that you still have to manage, especially if those Kubernetes environments start to scale and start to grow. So I think there are times where it makes sense to sort of set back and say, is this something that I want to run? Or do I want to use a tool like Magnum to help me deploy the core resources? Or do I even want to go to a cloud provider and just say, look, provide me Kubernetes as a service, let me leverage it at that level and then let me focus on the applications and how the applications are going to integrate into that environment. So we see sort of all those different requirements coming forward as a part of that decision-making process. And I think, you know, I mean, Joe, in your environment, you have very specific requirements that are driving you to do something specific, right? Yeah. First of all, can you guys hear him or do you need them to lean into the mics? It's okay? You can hear? Good. Thank you. Yeah. I think, you know, for us, the OpenStack journey taught us a lot about just installers. And, you know, previous company, I kind of had some challenges definitely with it. I think we used to have the just, yes, you can get it installed and it gets up and running, but then you have to inject your own personality into these clouds. And then we all have these standards and requirements that we have to follow, existing systems. And so I think that first generation, I guess, is how we call them distributions, you know, that was always a challenge because then I started seeing patterns of where we're running automation on top of automation because the distro was using, maybe it had some puppet installer and then we were using Chef. And then now currently, you know, here we are using puppet and I've seen, you know, OSA, which is a great community. But, you know, we have to live in this role that all of a sudden we have this duality of like automation tooling. You know, I like to say that, you know, we have 99 problems and an installer's not one. Only because, you know, we have really learned how to build and run our software. And I just feel like for the type of teams that I have, and I think sometimes it's a downside of when you work for a software company, you just tend to be like, well, I don't want to pay for something. We could just build it. But there is a cost. And I think it's in two areas. Obviously, there's just the financial cost of like getting the right team and staff because we're getting into a really, really complex environment of challenges that is putting pressure on my teams to keep up.  So for us, that was like a no deal. We needed to know that the things that we're running in public cloud, we could run them back in our data center, feel reasonably confident that those workloads were going to be performing consistently or at least close to consistent. But then there's other things we have to consider. Like I'm running a platform that is, requires very low latency. And so we also want all the other things that come along with it, like the observability. We want to know like, you know, because we're getting billions of packets per second of requests per day, we want to make sure that things like Ingress are able to keep up. And so, you know, a lot of times we'll pick and choose the best and breed, you know, we'll evaluate things like linker D or other types of things to handle some of the load. But it definitely comes at a cost. It is complexity. It's like, you know, I'm always concerned about am I up leveling my team. And it brings a lot of tension and challenges. Yeah, I think that there's like, it's kind of two problems that you kind of have to look at them, which is like, how do I get it deployed? And then how do I operate it? And I think those are kind of two distinct things a lot of the times. A lot of times it's really easy to deploy Kubernetes. There's like 70 million tools to do it. But like you were saying, that's the easy part. The harder part is like day two, how do we operate it, how do we monitor it, how to make sure that if something breaks, we can get that fixed. You know, I'm sure many people here, maybe in the room have certain businesses that run on top of these clusters and that these clusters aren't operating, their businesses are not making any money. So, and really that's one of the important things to kind of keep in mind is like, how critical is this infrastructure to your business? And then like, do you really have the resources to put at it? And do you have the resources that will be able to resolve your issues in a timely manner? So I'm a huge kind of person that kind of encourages to increase the adoption of Magnum because it kind of provides a lot of aspects that integrate with all the different infrastructures that OpenStack provides as well. So it kind of sits in with that same open API. And then I would encourage people to, once they have that environment deployed using Magnum, then starting to bring all the other monitoring tools and infrastructure because once you have that Kubernetes cluster, it can be really treated just as like any other Kubernetes cluster. Now that it's conformant, it really is no different than any other ones deployed by any other tools. But I think it's nice that you kind of, if you have that OpenStack expertise in-house, you're working within an OpenStack project. If you want to make a fix, you're already familiar with the contribution process. And Magnum has really tested its scale. CERN is one of the biggest contributors and users of it, and they do all sorts of crazy stuff that is beyond my understanding in science, but they create thousands of clusters both on bare metal and VMs, which I think is also interesting because if you're going to deploy Kubernetes clusters, you need underlying infrastructure to do it on. And a lot of times getting that infrastructure and managing that infrastructure is a problem on its own. And the nice thing is working with something like Magnum. If you already have Ironic doing bare metal for you and you already have Nova doing VMs for you, it's literally a matter of just telling it deploy on that environment. So I think that Magnum has a little bit of advantage on that in terms of facilitating everything underneath that stack.  Okay, but since we're talking about infrastructure and Magnum and bare metal and Ironic, there's, by the way, no one way to do this. And we've had a lot of fun over the last couple of days talking about the many, many ways to do this. But let's talk about Kubernetes and bare metal because this is what a lot of our really large customers are doing, but they're not using OpenStack. They're not OpenStack shops. So, Robert, why don't you talk about Kubernetes and bare metal and what you've experienced? Yeah, I find it actually kind of interesting. In much the same way that you have to make a decision as to whether or not you want to operate the resource or just consume the resource, the same thing applies, I think, when you start thinking about whether you want bare metal, do you want and or need a virtual machine management solution as well? Is that a part of your current application stack? In which case, then I think it sort of drives you to definitely saying, yes, I'm going to put in an OpenStack. I'm going to run my own infrastructure. But there's basically that level of hierarchy. If your application environment, starting from scratch and you have enough money to sort of build your own environment out or need to, there isn't necessarily a requirement anymore to have a virtual machine layer underneath a Kubernetes environment. At the same time, it's, again, a question of operations. Now, having a VM layer really sort of simplifies the operations, the deployment, the redeployment, the recovery from failure type of operations that you might otherwise have, and potentially gives you the ability to migrate workloads instead of rebuilding things from scratch. If you haven't completely operationalized your Kubernetes environment and some of the VMs around that, you can leverage that VM infrastructure that we now have to move workloads around. And I think that's a large part of what you have to look at when you decide, are you going to go all bare metal and sort of recover those, some of the pain points that metal had in the past, depending really mostly on how your application is going to consume those resources. You know, I mean, we often forget, I think many of us were living in this layer of infrastructure and infrastructure operations only, the application is the thing that's really got to continue to run. That's what's going to drive our businesses forward. And if you're operating at the level of just looking at the application, if your entire development staff is only application developers and not really operators or SREs or whatever it is you want to call them these days, then there is potentially a benefit to saying, let me find the simplest solution to get access to Kubernetes and that goes back to the previous discussion. Do I have somebody else operate that infrastructure for me? I just focus on the application. If I need something more detailed, I need to have appropriate GPUs, I need, you know, I have latency concerns I have to deal with. I worked with one customer that actually does a lot of telco-related services. They have latency issues. They have their own data centers where they've already dealt with sort of incoming and outgoing packet latency. They're not going to a public cloud where they can't control that anymore. But they're still looking at a virtual machine layer and then a Kubernetes layer on top of that because they're looking at continuously changing the scale and size of those individual clusters. That's how they're dealing with their tendency or multi-user sort of aspect on the cluster. So again, it really comes down to how the operations are going to tie into your business and how close you can get to that metal level of performance I think for some applications as to whether you want to go into that bare metal model or whether you keep the virtualization layer. I think it really interestingly ties into what I was talking about yesterday, which is how we kind of think that OpenStack, everyone's kind of historically thought, oh, it's just VMs, it's just VMs. We're kind of going through this transformation where you don't have to use VMs at all. You can just use Ironic, which is just a bare metal management infrastructure. What we find is at some point you're going to have to manage all that infrastructure. Even if you're using bare metal machines, you will have some sort of tool that does imaging or does deployment and managing of all of these physical servers because I hope none of you are still going through the pain of running through installers and hitting Next and writing IPs down. We've all moved out from that. But to kind of run at scale, you don't want to be doing that. You want something that manages it all and Ironic provides some of that stuff which I feel is really useful and you can just run that without running any of the other OpenStack components. You can run it to get your bare metal and then install your Kubernetes on top of it. So that is kind of one of the views. And actually, there is a project even if you don't want to even touch the OpenStack, it's actually taken Ironic and extracted it into its own individual component. It's just like a bare metal provisioning tool, period. You don't have to have Keystone, you don't have to have Noble, you don't have to have Glass. It's just like an individual tool and so that is kind of an interesting thing to kind of look into. Or you could use Moss or... That's Bifrost that you're talking about, right? And there's actually another one that is there called Metalsmith, I think. I remember the governance change came in, I haven't followed too much since then. But yeah, Bifrost is one, but yeah, Metalsmith is one that is actually aiming to build an API as well. So Bifrost never had an API. Right, because it was intended to have one. Okay guys, we're getting in the weeds here. And I too love Project Ironic and Dave and Julia and all the wonderful people that have worked on that over the years. But yeah, I have a lot of questions for you. Let's talk about more buzzwords, multi-cloud, hybrid cloud. Joseph, we had a great discussion yesterday about public cloud, private cloud, what you're running where, why you're moving things, where you're moving them. So let's talk about hybrid cloud. Kubernetes is finally making this a real thing, right? You know, I mean that's probably been one of the things I was early on and previously at this company, I lived there. That was a lot of my driver behind, you know, we had public cloud, but we also had things in the data center and I wanted to normalize it with the infrastructure as a service and so OpenStack was really that answer. But there's like a cost. I mean, to me it's honestly, we had certain drivers that have moved us back into the data center. We looked at a lot of our ROI as well as the workload that we had. It required to have close proximity. So we had to really think about as we're evolving these things and to be more cloud native, we had to really tight requirements to be able to meet service levels that our customers are looking for. So that was also another reason why. But now we live in this world where we run an Amazon and we have stuff in the data center as well. Kubernetes is kind of like, to me, the closest to getting into that model of being able to run across clouds because OpenStack, we were trying to do that and we were trying to do that and OpenStack, we were trying to use tools, we used different ways to kind of give that functionality. But like I said, if you don't have to, I honestly wouldn't recommend it because you're absorbing a lot of overhead. I do like what we're seeing now because a lot of the tooling is getting a lot better to enable this and with Kubernetes. So if you have to, it can do it. I'm really excited about some of the things that are happening with public clouds. Where like control planes actually can, you know, you can burst across and I'm like, okay, this truly looks like what I thought five years ago I envisioned. So it's going to be interesting to see how things turn out in the next year or so. Yeah, and we'll talk about some of those tools in a bit. But tell me, we were, talk about private cloud a little bit because this seems to be a trend where everybody moved everything to the public cloud a while ago and now everybody's moving everything back to the private cloud and oh my gosh, I'm oversimplifying. Ridiculously. Some of the stuff we were talking about earlier about why you're moving back to private cloud at Adobe, yeah. And this is specifically for the advertising cloud because the majority of the company runs in public cloud and we have different requirements. Like I said, the first off, we did look at a lot of the analysis, a lot of costs and the types of instances that we had to choose that would meet our requirements were cost prohibitive. I mean, it's the one thing that in public cloud when you have network requirements, you're starting to get into really more edge case instances that definitely are pricey. So for us, that was one of the big drivers. I think as well as like, you know, for a lot of customers and you know, I know with the rise of privacy and things like, you know, data gravity is real. So oftentimes it's less about like all the stateless, all the microservices things. Those things are pretty easy to kind of move around and refactor if you need to. But wherever your data is at, that's where you're going to live. And so that became a challenge. And we're definitely a big data company. And so that was another big factor for us to move back into the data center. We still on the edge use public clouds for reach, but for like our core processing areas, we find that the data center better serves our use case. Okay. Robert, do you want to add to this? No, I think actually a couple of things that Joe touched on are really important, right? And it comes back again to the question in my mind, which is do you really want to run this yourself? Is there benefit in you running it yourself? Or do you want to have somebody else take on a portion of the operations and then scale it across a much larger set of customers? And the public cloud versus private cloud question always comes back to that. Most small companies do not start out buying their own servers these days because it's more cost effective and it's a lower overhead on the development side of the house to borrow them from somebody. At some point though, it might be that it does make sense to move back into a private environment because of some specific requirements. Again, application latency, infrastructure latency, the whole managing your data, the fact that once it's in the cloud it tends to stay in that cloud makes it much harder to move from one cloud to another. Those sorts of aspects are the ones that I think are, again, driving a decision making process to whether or not you want to go back and forth. But I think there's another part of it which is getting kind of interesting, and that is that people are starting to see that when they have a consistent workload or a consistent load on a system, to basically pull that back into a more centrally managed set of resources. Again, whether that's still being hosted by somebody or being run in your own data center really comes down to the scale of your organization. But owning those resources more consistently, this is why there are spot instances and there are also long-term purchased instances. How much of the data plant do you actually want to run? All these things have to be operated at some point and there's a level of scale that some customers get to, you know, folks like Adobe obviously need that scale very easily, but even small companies, once you start getting into hundreds of servers in consumption full-time, I think it does start to make sense to start looking at these multiple options. I think the other aspect though is the question about hybrid cloud. And I think a tool like Kubernetes has provided yet another application interaction layer that simplifies the consumption of hybrid resources, in other words, resources of the same nature in multiple different cloud locations. It might still be one provider, it might be your own data center and a public data center, but you have one interface that supports that. And as Joe was saying, as the ability to make that one cloud look like a single cloud rather than eight different clouds, that further simplifies the process of making that hybrid decision. So I can select lowest cost consumption for any one compute resource. And I think that's the other thing that's really changing the discussion about whether you want to run it yourself or whether you're going to continue to run it in the cloud or do I have the flexibility of moving from or across multiple clouds? All right, so now I can start thinking about do I put my data into a private location where I have tighter control over it and, you know, I'm actually paying less money in pulling data into a public cloud than I am trying to pull it back out, right? So there are some ways of thinking into that way as well. All right, and we'll talk about the data in a minute. One of my favorite topics. But just real quickly, a show of hands. Who here is running Kubernetes? All right, who's running Kubernetes in production? Who's running stateful applications on Kubernetes?  You guys are better than my meetup group. That's more hands than we usually see go up at these things. So before we get into tools and data and all of that, I want to ask a question about distros. This has come up a lot as well. Rolling your own, using someone's distro. Yeah, Robert, take that. So the question of distros is always an interesting one. And especially with things like, you know, now cloud foundry is basically a Kubernetes distro, except they're not, but they really are. You know, you have OpenShift, which is a Kubernetes distro, except that it's not, because many of these services want to also put their own platform layer on top. And I think that's the thing that you really have to look at, is the installation process really so hard that you then want all the additional set of services that are there? Or is it really what you're after is the additional set of services and you don't really care about the fact that it's running on top of Kubernetes, which is also possible. But for me, it's always been, you know, let me see if we can't get this done in the simplest fashion possible. And again, this is where tools like Magnum on top of OpenStack, I think make a lot of sense, because they are basically pulling from the standard upstream repositories rather than any one particular distribution of something like a Kubernetes deployment. Yeah, but Joseph, you have particular reasons for doing it the way you're doing it. Well, you know, I think for us, I mean, as I mentioned earlier, you know, oftentimes we kind of get in this thing that, you know, because we can, we can do it. And it has been like a great teaching tool.   Now, here all of a sudden now we're in a world where, like, we have all the things around that support the lifecycle management of it.  You know, you have operators that can ease things like, you know, getting permit these, all the things that need to exist outside of once you get Kubernetes up and running where, you know, it makes it easier. So I'm a, for our use case and stuff, I tend to be like, we tend to be very like very modular, very pragmatic, like only use what we really need to use.  We've had times where things are very tactical, where I could jump into Slack and, you know, we had some deep questions about like pod security policies and how we were trying to apply them right away. We could get in and get answers. So I think that really drove us to be like, you know, this actually works for us.  And a lot of operators had that as challenges. And with Kubernetes, you know, we've, with our own approach to taking it, we're able to stay current. We're probably like always a release behind. The challenge that comes in that is that I keep seeing down the line as our cluster is starting to get bigger is, can we still maintain that same cadence, you know, but up to this point, I feel like because we had such a rigidness about how we build our software that I felt like we were pretty comfortable with it. And it would fall in that line where we needed to stay very lean in regards to like how we are, you know, building our infrastructure underlay. This is one of the things I hear all the time. The people are getting so far behind in releases. Yesterday, somebody was on Main Stage during the keynotes talking about, you know, how quickly, you know, they're getting to the next release. And I was sitting next to one of the rather large telcos and she was like, slow down. No, these releases, I can't keep up with them. And like, she wanted everybody to go a lot slower, not release every six months. And we hear that a lot. But with Kubernetes, it's not as complicated. It's not as hard when the new releases come out. How do you handle this, Robert?  So Kubernetes for private cloud. Many of them actually focus on that upgrade process and simplifying it. But also adding all the other services, right, like Joe was saying, installing it is one thing.  I think that's where some of the distribution players really do come into their own. But when the distribution is turn on Kubernetes, that's not really where the value is, right? And so I think that's one of the key things that people need to be aware of. But I also think that's where, again, you know, there are tools out there that simplify this process. If you have an open stack environment, Magna makes it really easy, right? So why wouldn't you use that? Now, did that also install Prometheus? Last I checked it doesn't it? It turns on a Kubernetes cluster, right? And it's thinking about the fact that there is a day two set of operations that you also want to keep track of. You know, it's easier, again, another one of Joe's points was the fact that now there are package managers like Helm or there are application managers like Scaffold that are sort of out there to try to help with that application management aspect and they're using Kubernetes as an interface for that. So you're going to end up wanting to layer Kubernetes on top of however you've deployed your actual physical infrastructure. But do you need a distribution for that? It really depends on, again, how much you want to operate those resources, how much of that you want to own and how much of your engineering budget you want to apply to continue to manage and maintain that. I think it also depends on the type of organization that you are. Some of the organizations are more focused on being upstream first and wanting the ability to do a lot of customizations in what they do. So I guess using a distribution will be a bit limiting in terms of that because most distributions will have maybe a few use cases or a few ways of deploying it and they're probably not going to support you outside of these few very specific use cases. Whereas working with more upstream based environments really does have less features. We can kind of say that. But it gives you the ability to iterate and customize and go over the improvements that it's provided. So actually, interestingly, you mentioned it, but a few releases ago, I think it's a few weeks ago, the Magnum now deploys for Mithius if you would like to deploy, right? Excellent. The thing is, it's progressive, right? It didn't do it right from the start. It took some time. It took an operator that had to come in and step in and do it. And then things like dashboard, you took a while for it to come in. But at the same time, it also depends on, again, the type of company that is like, okay, we're open source first. We know that, you know, there's going to be there's going to be great support, but you're never going to get an SLA. But you have the advantage of going out, being able to read the code, fix it yourself, if need be, versus, you know, having a more Kubernetes in a box solution where it just works in one way. But you don't have that amount of ability to do a lot of customizations and how you want it to work.  Congratulations. Yeah, these are new projects, new tools that are coming out, and they're not always, you know, ready, but they have strong communities behind them. I'm going to make a plug for one of my favorite new projects, Istio. I threw the first ever Istio Meetup a couple of years ago. It has come a long way. If you open source contributors are looking for another side hustle, I'm going to throw my hat in the ring for Istio, and I'm going to run a really cool project with a great community, so join us and contribute. But what are some of the other really cool projects out there that you want to make people aware of, and not just to contribute to, but to add to part of their ecosystem? Well, I mean, when I look at the spectrum, you know, use Kubernetes as a base, obviously, Prometheus is an important aspect to that. I also look at Istio as a way of building your application connectivity and also potentially dealing with some of the potential customer VPN related issues that might otherwise exist. I think there's some interesting ways of bypassing that by using tools like that service mesh class of technology. But then there's also, as a part of the continuous integration domain, I think tools like Spinnaker are interesting ones, and they also have sort of a really nice connection back into the kinds of environments that Kubernetes tends to favor in terms of development process. Spinnaker, oh, that's a good idea. Maybe I should throw a Spinnaker meetup. Who would come to that? Ooh, not many. More open stack and influenced ones is Courier is an interesting one that's actually trying to work on bridging the kind of your Kubernetes networks and your physical infrastructure networks using Neutron and some other stuff that are a bit harder for me to understand, but I know that they've done a lot of good work and they're kind of increasing the adoption, so I think that's a really interesting one to kind of have a look at, but indirectly also Zoolz, so Zoolz recently added a lot of features to help with doing things like to help you build whatever images you need to do, or actually do deployments, and now with what was updated today by Monty talked about how you can use, you can kind of link your Kubernetes cluster to Zool and it could kind of give you a name space for you to run all your jobs and bring up a deployment and do some testing and then it will destroy that name space afterwards, so I think it would be it's a really interesting thing to hack around. Zoolz is an awesome project. I also threw the first ever Zool meetup. Monty says he's going to come back and we're going to do another one. That is a really cool project. If you guys don't know about Zoolz you should definitely take a look at that. I promised you guys could ask questions too and I've left you about two minutes to do so. Does anyone have questions? Yes, please take the microphone so that everyone can hear a question, including the recording. I was wondering if any of you guys have any experience with running sort of soft and hard multi-tenancy in Kubernetes and any of the pains that sort of come along with that? I've been hacking around a lot around Cata containers. So I think Cata containers is a really really interesting aspect and I think that that's probably the best way to go around it. I think Kubernetes has pretty reasonable amount of multi-tenancy separation at this point but the problem is it's all kind of soft separation and I think some project like Cata containers brings that hard cut which is like you cannot get out of this. Can we have someone that can talk to you a little bit more about Cata containers if you want? Eric? I think there's another approach which comes to depending on what tendency you're really looking for. If you have completely separate organizations that need that complete level of segregation it might be easier to deploy Kubernetes per customer and that's one way of approaching that and at least amongst the namespace that you're working within additional roles-based access and those sorts of credentials can be layered on top but at least you've provided that level of tenancy so from a cloud operator perspective breaking it up that way is one approach. That could be challenging though because as you get scaling the management is becoming that. That's where I think I would probably go along with the possibility it just took some time with all the container interface and the run times and how that got sorted out it took a little bit of time to get there but we've been talking about it ourselves of looking at that as for security. I think the roles-based access interfaces within Kubernetes have gotten a lot stronger as well so you do have decent segregation at that point. I still think that there's a lot of confusion at least even around exactly how to set those roles up appropriately so that you really are providing true segregation. But again, it depends on how you're integrating and I will say that I've deployed the Cata container solution underneath Kubernetes and it is the simplest container run time swap for something that now is an actual VM based image that I've ever gone through so another plug for Cata is a great solution. Another cool project through the first ever Cata meetup it's very popular and it's really coming into its own now so if you haven't checked out Cata containers another plug for that one.  Oh, I thought you were leaning in to say something. Okay, so we're wrapping up. Do you guys have anything? I've got some of your questions on Twitter they're too long to answer right now but we will answer them. I promise if you tweeted a question at us we'll get to it. We are around all day and this is how you can find us. Any last words? Thank you very much everyone. Have a great rest of the summit.


So, why is it more important to be consistent even than being intense in what you do? Intense meaning, for example, making a great amazing video or making, you know, kind of a video like I'm making now, not feeling well, not very charismatic and just have a really bad heart, a stomach ache, like, you know, just an eh video. Why is it so important to be consistent even though you can't deliver intensity? Well, most problems start from not from a lack of intensity, but from a lack of consistency. So think of somebody with health problems. You don't really need to be that crazy to not have health problems.  That's it.  You'll be fine. You'll be unhealthy. Or getting attention on YouTube. Is it better to make an amazing video that will get tons of attention and admiration? Yeah, of course, but, you know, what is better? Like to, let's say you're not in that mood or you don't have that ability because you're traveling or you don't have the equipment.  Make a video about it and get 20 views, 50 views. Is it better that people think about you a bit? You know, you're on people's minds. You popped up or is it better to not even be thought of at all? So the minimum requirements are very, very easy. Intensity is a diminishing investment.  He's going to be very, very healthy. He's going to eat well, he's going to be in great, great, great shape. A guy who works out an hour a day is going to be in amazing shape. But both of them are going to be healthy or fit at least. Both of them are going to have fitness. So yeah, maybe the guy that works out 10 minutes and now like instead of an hour maybe he's not like, you know, super fast or super strong but they're both fit. The guy that makes amazing, incredible videos every day versus the guy that makes, you know, okay videos every day. Both of them, you know, one of them puts in like a tenth of the intensity of the effort but because he's consistent he's going to have a following and the intense guy is going to have a following. It's really that simple. Are both going to have a following? Is the regular guy going to have a big following as the super amazing, intense, high quality guy? Probably not. But are they both going to have a following? Yes. So, intensity is always less important than consistency. Consistency is like God. It's the most important thing in your life. Anything that you want you can get by being consistent. If you don't have the intensity maybe you won't get too much of it but you'll get it.  So it doesn't matter anyway. So I hope this video kind of helps you get more understanding why consistency is a must. It should be a given. Whatever your goal is you can always sacrifice quality or intensity but you can never sacrifice quantity and consistency because consistency is the bedrock that's going to create the results. It's basically what the results lie on. So every time you're consistent it's like this. But if you're not consistent it's like shoo shoo it goes up, goes down, goes up, goes down. You can train for 3-4 hours once a week. You're probably not going to see any results maybe a bit or you can train every day for 30 minutes. You're going to see much more results. So always put consistency first and make your life a hell of a lot better.


What is the role of data privacy literacy in higher education? I think it is probably one of the most important things we can do. And you know, we have this awesome responsibility and opportunity to teach the future leaders of the country and the world in, you know, a myriad of things. But one of those things is data privacy.  And those are very good. But there's also this opportunity that we have to demonstrate to our data subjects, to our students and our community members how their data ought to be handled. And by doing that, we're showing them the care and respect that data should be handled with and teaching them that this is how it's supposed to be so that when they grow up to lead the future free world, they have this idea of, well, you know, my college was able to do this with my data. Why can't you? I'm giving you money. So by setting that expectation of how data ought to be handled and how preferences ought to be respected, we're able to make this, you know, gradual, but make this significant change in how, you know, the country and the world really see data privacy. Great. The phrase cybersecurity and privacy is what you hear. Could you talk a little bit about the relationship between cybersecurity and privacy? Privacy is about making sure that the right folks have access to the right data at the right time and making sure that we're doing the right thing with those data. So cybersecurity is, you know, the lock on the door to make sure that nobody busts in and steals the data, you know, that completely unauthorized disclosure, the breach prevention, that sort of thing. Whereas privacy is making sure that if we're doing all the things that we intend to do, we don't accidentally do the wrong thing. And so that's where I see the difference. You know, we're kind of two sides of the same coin with privacy and security. Cybersecurity helps prevent those unauthorized breaches and things like that. Whereas, you know, the things that are intentionally malicious. Whereas privacy is we're trying to do the right thing and we want to make sure that we actually do the right thing. And that's sort of the difference that I see between them. That makes a lot of sense. What do you say to someone that says privacy concerns are bureaucratic and stifle innovation? Folks are used to sharing their data. They share it with Facebook and Amazon and Google all day every day. So the issue isn't that people don't want to share their data. It's that they want to know how it's going to be used and they want to have some say in how it's going to be used. And so by creating that transparency and by respecting their preferences, their agency, we're able to build a level of trust that we've never had before and have folks more willing to share additional data that they normally wouldn't. And so if it's, you have to share this amount of data to be able to be a student. OK, but if I trust the institution, I'm willing to share this much data. And that really can give a lot of new opportunities for innovation that haven't existed before because FERPA says we can't use this data in that way and HIPAA says we can't use this data in this way. But if the data subject trusts the institution and provides consent to use their data in a way that benefits everyone, then everyone is better off and we're able to be more innovative.