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Taking Django Distributed

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the end up on the and I
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and but really um as and told you I'm his togram taking gender distributed and that 1st of all a little bit about myself and that means making the of the so I ask you to
mention an agenda co-developer I'm perhaps most famous for working on South migrations in the past I vary greatly hand migrations to markers of all back and these are the local channels which we'll talk about 2nd my day job is a senior software engineer at and writes the chicken company and I generally have a very bad tendency to run toward code on fire rather than away from it and it's a problem I know I'm talking through its form so I have some bad news because he they
really don't like you and the 2nd is the bad news is this mixture distributed meeting very difficult and for a long time I'm sure you will agree with me like in my in my past my reaction this is very simple I'm going to build a model
the beautiful have nice clean energy is all the code in 1 place we have 1 application The . 1 and we can be very happy and this doesn't work for a long time on lists Robinson the most successful sites in the world and before install so properly monkeys advice is don't necessarily move away from the model this obvious to you if you want to what the thing you have to and the daddy reasons you should not go into those but is not necessarily a bad thing up front so if you are thinking
about along with the thinking well it's time that things are a bit like what would you have all this code and usually what would happen is you'll come in having existing convex this talk is for those who are coming in generally with a basis in base you how the code in place you pouring got a few years or your eventbrite was a decade of code them lying around the world hasn't taken and wrestling but up and this is particularly easy resulting from scratch that little easier but I also was tempered starting from scratch in this way too because there's braving tendency to why call over offset to sort of take the best ideas and run with them that begin with an amazing Sean systems due to the communities it serves like people you you don't want that the so this 3 aspects to taking a site or a project distributed 1 we talk about most polities code them or you databases if you're in that realm but I'm also then talk about teams and 1 thing that learned to the last 4 years is that the way your team works on the way you engineer software scale is very important you can't get anywhere that you're of 100 people if they don't talk to each other and understand what working so cumbersome about as well so there is no 1 solution I can't give you a magical solution the who walk out of this room and go back to your project and implemented scale if I could I point would be here other what a luxury yacht in the Caribbean something myself with 100 dollars there's no magic solution you can't do this and kids trying give you both strategies that you could try apply Annals of advice things were like your to look at the patterns and recognize things happening before you see the 1 of things I tried doing talks these days is to give you the point is to work together I can't cover a lot 45 minutes but I can try and give you the hint of what's out there the things to go look for research if they catch your eye if you saw itself find yourself going down path yeah and the reason is that 1 solution is sites very different there's all different kinds of loads types and different kinds implementation types these are just some of the ideas of what you can have for example if he's going Wikipedia Wikipedia is incredibly read heavy site knows the traffic that site the buddhist going there looking out leaving again a strategy works well for Wikipedia cuts very heavily does not work well something like event right where we vary right had to come to us to buy tickets to send the money a lot of what we will do is very transaction have involves a lot of sort of rights and updates and so we really can't scale the same way it's true for the kind of land to you can have very predictable load which I'm sure when you how Wikipedia on google it so a gentle curve addressing later began spiky load as well you have people they call will will be right in the next 10 minutes for this blog post should on right it's a it's a very common thing happens or even in your thing the hosts events every year so it was going variety in the 10 minutes the forties go on sale to try and buy this also the chapter this is often more problem in game development this clean more a problem in the web previously the idea of having a website that was sort of repeatedly sense small messages back the forwards was unusual and they just came along and Ajax helps a bit but is still quite bulky and now with sockets and small Jackson frameworks we start to see this problem solved sites very chatty talk about this a lot and if you're in an area with high latency like say Australia where was lost in the last week that comes a real problem the last always what we do with our code and how can we help deal with some of the problems with distribution supposable use gender you have perhaps there an amazing abstraction to use for many years by put all my code 1 apple call when I was all models or the code all this and later 1 that I think we ignore the entire axis of gender this is fine for me as a single developer my blog is still this way has 1 apple blog with all the geo tracking inside it and the place visiting and the talk track it all in 1 but as you become part of a bigger team apps a really useful lying to draw boundaries across not just for to put models encode bolstered understand what the dependencies are who's working a lot more the ownership is like it and you want to really formalize those interfaces and what problems of apps and it's good in short term is that it's very easy just cool functions on models to ready from the that if I'm writing you know appalling for my blog I can just make the point that call find Random House in mind my blogspace model this is fine a small scale band actually scale up 1 of the biggest things of code is having a very clean interface is drawn between the different parts of this is you chose this splitting up as we'll see in a 2nd but is also useful just generally in terms of thinking and reasoning about the code where codebase gets a certain size no 1 person can understand all that code base and so you have to let yourself forget about pieces of the code and think about in the abstract and that's the only possible if you have an abstract pieces that have good rules about and so these interface is a very important for saying I can reason about this piece of code without remembering what society because otherwise my head explain if you do has interfaces and you do get the right scale you can then choose to spend long and this is kind of where I say you have to go this far in many ways staying that here with formalized interfaces is good enough for most big companies but if you want to you want go with separate machines having them they're gives you the perfect place to stick the cleverer split Apollo codebase at that point as a sort of small example if you imagine a site have things like inventory payments for detecting site of injury is name having tickets by the way and there's a very clear split there if you build a correctly of saying all we can take the whole payment system which deals with banks and settling and also a horrible stuff that goes on there and move that 1 part we can take the injured things like all you muscle exactly 30 circuits the signal not to move up to here and we can take the presentation layer the rest the logic and accept and even this sort of concept is very helpful again you can read about separately to say like I don't want to know about payments because it's really complicated takes whole team but I know that I can ask for payment and get a confirmation and 1 of the big problems we split is communication and this is kind of the reason channels exists channels often comes across as all this is made major WebSockets it and as I did it but others across not is true and the gap I 1st saw agenda was all what other thing to happen but their secret is the web so these are not backed hot there's plenty of good Python libraries to serve the problem is not sockets the problem is making a system that lets you have sockets is the idea of well what we can have people talk to a server this to serve as metric chapter each other how they talk so to so that is doesn't exist and idea is the problem in bigger scale for services imagine have
3 services and joint OK all do is will have the free services just be like Django apps on each 1 level of whiskey runner use call like Haitian the points that they give you Jason back very decent model note from within a small scale Stephanie giving careful you have 3 start with you can get 5 new
it at 1st of all it's been a pentagram is worrying that secondly you can see like it's gone from 3 to
10 interconnections and now what if you have 10 services of Dayton
get them and this problem gets bigger and I have heard for example uh that number have 2 and a half thousands of users who can imagine is models we work in case and so the thing channels goes for which is not the study with good fit but I think for most is is is a message passing
service but this is where rather having interconnection or your services and what individual pieces told to a common bus and that is how they collaborate and share information among each other Charles is a very good meeting for this eventbrite service in the structure is now starting to be moved on to running nor on channels into the sockets but only channel layers the underlying implantation of communications this is a really good way of starting have echoed separate it out now what is multi to the and how this works but for now we going to databases and this is kind the
hardest part branch this is not SKOS migrations exist but people often their Andrew what he migrations we can just use gave a code point is saying the data and the analogy is somewhat flawed it sounds lovely what our world of course the must be is a similar solution as there is proposed as gay came along with them and did for the database that it the character has not quite true public data is the data turned to quite valuable and Yukon is deleted recreate it linearly houses very big we could have a system like with pure virginal database they would make a hundred times or 10 times bigger when you have 60 or 70 gigabytes of data that is not a feasible prospect of kind of what we can go and say applies the scaling you could think about the same kind of thing to do with the code was show the 2nd they're very different strategies for different kinds of rights and the thing you might think about when you have code is standard we call those the partition is a fancy name for you give each tables on database the idea here is that say you have a couple of big tables I have a could be users table and maybe a bit images table of a common table at the end of the cheap Instagram for example and if they're all kind of the same size you can very cheaply use 1 3rd of the space on each machine but is putting 1 on each machine the problem with this is that you can't spit further than per table if you have 1 giant table especially this just starts falling down was a single look at it the so the next set a bit different and I'm sure you've most of you heard of it which is having replication particular having a single main database that you write to having lots of red because that you read from this is a very common pattern in gender there's lots of the body actually do this it does come with some caveats about Collins quickly the main caveat is that there's a replication lack which means that when you rights information to the main database it takes a little bit time usually under a 2nd hopefully under 100 milliseconds for that information to go into the main database to to 1 of the replicas and then the available to you to read to increase the replica now 100 ms is a long time but it is if you're rendering a page and particularly 1 of the main problems people have is they will write to the main database and that is replica straight away and not think about a lack and you'll read back stuff these but you may just say the new comment and you read about page again what would be the replica and you show the user page without surfing the dismiss it to this is a very common problem and the solution to it is called database pending what you do is you say OK with somebody writes to table inside 1 of our views for the rest of that you will pay in that you to read from the same name databases you right to expand consistent information that's great until you realize if your sights right heavy you can't actually do that all the pages because then you never all replicas you just always inviting reading from the main database and so this is kind of 1 is tricks and this is where my favorite triangle which is the SAP
triangle comes into play I'm sure many of you have heard of the idiom uh cheap fast and good pick any 2 but this is the same for databases you get partition tolerance availability inconsistency you get basically at most 2 if you're very lucky you get at least 1 made many advances give you maybe half of 1 of these if you look at it right uh my sequel is somewhere on the 1 scale I have 2 boys have a bias on it but this is from like inconsistencies everywhere
you can imagine the idea that like you might think say breast pose isn't very a partition tolerant inconsistent database in that it's not always available to read if 1 erectus files but usually if you can read you get consistent answer from what you just use gay but that's not quite true replication because there is still a little inconsistency that very
true in a single not a single sort of machine case analysis in the greedy creeps into all aspects of distribu computing in general and is rated reason for business reasons physics this is a nanosecond of
what uh the wonderful program Grace Hopper was famous giving uh in her lectures holding up nanoseconds of what and the idea is this is the maximum distance the is can travel in 1 nanosecond because the speed of light is a certain speed 300 thousand so 3 100 million it's the 2nd I believed and put me on ants in copper it travels 2000 that speed be even on fiber-optic directly final luminous think about computer computer does the school clocking got familiar process is basically they sort of what we look at how the machine way like you they do an operation and talk to the next 1 is due more operations and the clock is kind of what governs how everything synchronizing the conducive it's overcome many version of a big computer system and it turns out if you want to go more than 1 gigahertz which is it turns out 1 like using 1 nanosecond you can't have components further apart 1 nanosecond or they cannot physically thought fossil along the this is what we don't have the computers around the fastest physically impossible and this is kind of a microcosm of what should it is hard to think of this at a global scale if I have a server in Australia and a server in West Virginia they are at minimum 100 ms apart at the speed of light I cannot be its it's physically and as far as we know it in that cabinet physically impossible to do and so if my goal is to have more than 10 right the 2nd consistently I can't do it because I cannot synchronized more than once every 100 ms between these 2 sides and this is well the problems addition to compute coming give out the triangle
consistency is 1 of those things that's fitted heavily by being physically distributed and it really comes into play that places and if you think that this model
this works very well and it would dissuade you from it but there are more advanced things will come to you in the 4th part presentation of shot and so on that the kind of move towards a
microcosm of databases and co combined is load about a lot of people that think about this at 1st I said he didn't when I started out as a oxygen it was my so my 1st jobs and it quickly hit me like a ton of bricks or like a huge number of users taking refresher ones the problem is you think website is simple on that you just you know better than people think but such a simple people think all have a couple of servers scattered around there all equally balanced and then everyone have consistent low times Eliezer roughly the same ruler sort of very cookie-cutter generic people if you have this congratulations you have a general website please keep that no 1 else has this and what we have is loads of logic that run the different speeds and different machines that different pages have different amounts of processing loads for example a call you know this page is very easy to render such a shot him play this page out of thumbnail these 25 and show them and integrate the and and I am wildly varying users when I favor interview questions to give is um master's buildings from of candidate go OK I'm not gonna ask me sort of whiteboarding on technical questions like how viruses list I want you to discuss whatever level you feel comfortable how you would build Instagram ground and usually most engineers are junior or senior will go a decent way along house tables and it's getting ideas and then you drop the bomb figuratively which is that you say OK now 1 of the users has 10 million followers and nobody else to us you have what's almost all the just and being a problem right that this 1 individual user is so incredibly expensive you constant up their single atomic entity that really not with the way although works and not just that as the default um load balancing in theory like this um if you were 1 country especially your lovely curvature the daytime models awake and allow the reluctant however the sleep in the perfect esa scale for enjoy a nice line about 20 about this line there this is our maximum capacity on the list backpacks at all times for fitting sickly like 350 you can launch service in the morning and taking down evening if you a ticketing website which have some familiarity with looks like this where the goal is lovely relaxing and then an event and realize existed goes on sale and they're very popular and everyone in the world arrives at once trying get their free did mandatory have and and so suddenly everyone to slam the door service onto 1 single page um and often into an order flows very complicated and scaling for this and load balancing this is very difficult you commissary load-balanced equally across different servers that might hit a certain set of servers differently like this might your pain and points much more annual event view point so that little bit of extra work and this getting more complicated because of me because all I did but it 1 was a lovely things that beautiful migrate and they're very good for game programming in the browser in particular but they have some problems 1st leg most problems are not like ATP requests is 1 reason that they're into with like whiskey is you have requested service is in response to Don and responsibility so it's all other technically you buy a socket agave and hours or days is sit around you can't necessarily be rooted because TCP is what like that knowing that the set of tools that handle balancing sockets is very limited like you handle them almost as raw TCP connections but also their sort of Haiti to be but some told what do other properly and it comes vitamins and even worse different kinds of failure of which you realize the right so the serves the many realize 4 different kinds of very and they can not in the 1st place in close randomly always himself and the thing that what's is that great but there extra feature when you design assigned to them a bonus like you have done if you Clements browser supports them if you can open through a proxy they have great fantastic but you should treat them as optional and you close the in freely if you want to reload and sockets just close them and Lope that moment somewhere else so design into hope forever designed so that any new they might die if you on London Underground for example there's only Wi-Fi stations and not an internal between stations and so people regularly will appear for a minute go away for 2 minutes reappear for a minute you design the that case as well most sites I used to use in London didn't like the whole I haven't said how white nodes not here again the white nodes here again now the 3 latency and just started collapsing like some of the uh take sites of like and trying to order food did not plan for this case in the further from the big problems and figure from this become the team's further said teams a really important part of designing distributed software and big scales of a general engineering is a different discipline to programming it certainly encompasses programming the engineering is a more holistic engineering about taking a set of programmers designers and product people and making the best products that you can serve the needs best having part of this is how you use the people you have a disposal as it become more and more senior and go through the industry more more but I see this like I used to be in the body in 8 9 years ago at all all am the genius kid programmer I can do anything I understand everything and as you get out of the zone of your so incompetent you think you know everything gets his own worked out you as you know nothing and that's kind of where I ended up at this point teams a very important I don't know enough about managing people that's not like to use but the sum of the thing I've seen as a senior engineer who leads teams and projects I think it useful the 1st is you developers people to programming is an incredibly drain profession I'm sure many of you know this and mentally and also emotionally sometimes as well understanding requirements and also trying to adapt them and deal with people having different ideas from you can be very difficult you need to make sure this time and space to plan this in particular I see lots of plans like like all we can have these 3 features developed in parallel with the most instantaneously them this is often born out of being a smaller company list distributed we have all we have 1 or 2 services everyone knew whole codebase when everyone's in 1 room and there's a whole codebase you can happily do that you will into different pages and then emotions again this woman was crawling or but when you have a hundred 200 people you don't know everything going on elsewhere you have to allow time for both the spin up understand what the context is system so this already and then to spend on each so the variable thing to think about In part this is tackled that really can be poisonous again I'm preaching to the choir here I'm sure but it's very important the goal of some technical that when your but start at if you're doing like the spatial of genes that actually awarding websites your gender boom and as site you
can have some technical debt it's fine it's always healthy requirements change people change you basis change what you should do is very very cognizant very aware of where your daddy's and when you need to pay it off cause like normal that true interest as your codebase grows it drops down you more and more and more and so you need a little bit compete but you need to keep the the head aridity managing it is very easy to lose track of battle that as you go along and then at the year slightly more controversial question which was commissioned not even solved internally which is how many gear posture this is 1 of the things we're making a big system is really yeah think about together into a sitting down fusion going on OK we've managers stood out patients basin resident fantastic when we put it if you answer the same repository then congratulations that's great to have a single giant repository everyone's have knowledge of that's what time is going to be terrible if you chose Motorola trees congratulations you never have 300 posit trees and no 1 knows where the law and you will have 300 versions and responders to have a hell of a time is there again is no good answer um multiple repos often seems more attractive at 1st it is but it means that we're doing is pushing complexity from programming and doing the merge conflicts that problem you going away it's just happening to push down to the release phase as you're giving operations release engineers or your problem just kind of selfish if you us so just you're aware if they if they agree that's fine but don't think you might be making would go this then turns into well you have these repos a single repair how to walk home much stuff do you have your team's structure around individual services pieces but how do you instead of trying stretch strike people across different services like always teen what's different things and try encourage people to have diversity of knowledge and opinions of the codebase this again is really difficult because often you don't have enough engineers because no 1 diamonds and not about liking this also includes like designers and Eurex researchers and operations engineers to I can never have enough people and working out how to arrange everyone so that again no 1 knows everything is a very important thing I can't stress enough that the vital told to each other can get really difficult the and this gets really problematic with ownership gaps this is a problem i never saw coming from China to the company is that it's possible to have joint pieces of code that no 1 knows about because they got rid of for they still won't find their written right but nobody like even if the person who wrote it is still the company they've probably got like I forgot most the kind of a written not uncommon to do so and it's very easy to know what you're working on this for a cause they will not working like a some companies even working out what the feature set of the site is could take a team of senior engineers weeks to work out like there's some scientists collocated but it just no 1 may be made the support he knows that such like 1 good is going to to support people because they get all experience will not all the window features that basically nobody knows what's going on and until you run into these gaps it's hard to know their answer really think about like if your small or medium just give a rough spreadsheet even of like now these are the rough features that we have and he is who knows about the best and then the sum the leaves and their income by themselves to go up that person is left and nobody knows about this and so we should go fix this happens gender to like Django is a very big complex project we have specialists in log January's their areas of Django there and specialists in and for a long time we thought nobody knew about and all the women for was stuff then 1 that would that was admitted knowing about it with half the waterfall yes exactly how so that kind of thing and others noticed that income is bigger than supporters to varied so when only sort of rough points on isn't into some strategies like how can you take these ideas of inferring you and try and move what's my best advice as we like I continue single solutions but what what I suggest so 1st of all people laugh microservices and do this directly after that go micro-services like this just on the variable weather services buzzword they're very common and so they're very easy enough the problem it's so easy to ignore all the other code and start new service if the service version of all just delete or rewrite from scratch it's easy to start and you know that it's going to be this wonderful thing when you read most programmers a few exceptions I know a size do not let make sperm if you do regulations you should charge more but if you don't get the temptation is to go out and do new services and what disjoint altogether again you're not actually saving any work what doing is pushing all the work later on the process when you now have a thousand services services and no 1 knows what will do and can you imagine that you have a thousand services I doubt 1 person understand what they will do all of their ideas something is taken the same problem you have with a monolith and maybe it's not only being services announced on different machines as a consistency problem leads to the monolith it's along place and you can sort of trace to the current debugger easily yeah you tried tracing box through 4 different services of order machines it is not easy it like you can't put a PDT trace and I have to sort of financed logs and put locking in we from all Member for the looks a it's just a so that's 1 of the things to think about what I did encourage is a moderate size of services usually 5 to 10 is the start most companies trying real big business reasons and folks around those of often helps the team composition to if you have experts in certain areas noting already it's traces of a cluster around them and give them some junior engineers to mental ones well just don't have a thing where every engineer the service who that point there was writing there are different kind bases and you have a joint collaboration problem again I'm a big fan of service busses isomer wrote 1 in channels there really nice way of doing it's service into machine communication when the big things especially as 1 of doctrine of containers is that with a service bus when you have a piece of code you can say hey the busses that here there's no need to say also as 1 is here so as to his his of history is here only reason service to by the dresses changed to restart you the IP in existing methods from but not complex life so that a reading policy responses the make deployment scaling a lot easier than not listen any ports because talking out of synch launched 10 20 process very easily it's not for every design there totally case
we should have a passed we should try and keep some traffic off the bus In particular wondered lysine is having a service bus for some stuff in the terms that it is at most once which is a Mr. the boss might get there might not um and a separate thing about fire hose which is all the events happening in the site and they may happen once or twice or more to at least 1 and different code problems the modern things cache validation is best on providers because if you know the cash twice some problem and so you can relation things you listen to a firehose intimacy an idea all yet misuse changed invalid catch great we're doing that should be all of us and then on the consistency stuff you are gonna have inconsistent data it's always impossible to avoid this even if you think you're perfect monolith assume you have computers in more 1 thing to send to the physically separate you wouldn't have have do with something like this is like 10 20 ms and a really powerful way of doing this is to look at the product will you making way can you allow data sit down with your UX research is your product people ever designers and go OK we have to give somewhere but where can we give in a way that doesn't have the experience them a very common way of example is to give on continued also some if I have say a site images and comments all the things that I didn't I will comment on the happily serve you all data great good example of painting that was applied everywhere as many cases in different pieces of software you can go long gone it was just change but if we remove the pagination is very common by the way you can begin have recently they have does not 300 pages there are because that's what was that the slave it is and so but a show you next page most the functionality is there but that Spencer pagination queries go away and so that's what the compromise example you might you do it now sharding but surely is a very complex issue and 1 that it is entitled by itself to cover but for those who want to wear showing is the next step from base in the vertical partitioning put part of petitions yeah the idea is that you have 1 table on multiple servers say like my users tales of 100 differences and generally use a word Humpty from shelves and each user is essential it very very powerful it works sleep and friendly well for most and patterns the people understand but it is an incredible technology and person cost have ensured codebase makes everything so to write everything slow to run some people come along and designed for it up front they go OK we're gonna be amazingly gonna stop electron you start up it's in a shot of the beginning the fantastic is limited let me show you could do that but in the same way that you could not take content will then have a perfect codebase that passes every single test homes and coverage over time you'll be much slower like and was certainly when you're making the product the open-source or commercial you don't understand the full scope of your problems problem you should expect things to change so the same way you should have some technical that like I often won't write tests for some hot like the halls of my code I think change you probably shouldn't of shot in a natural way we should probably get through well we're gonna leave the touch points in here and 6 so I suggest is virtually all of your queries through single model in gender or function outside it so then you have showing you come along to that 1 single place and put it in a luxury often involves like the an ideally we're gonna hash of the ID find so do that stuff I see many that don't do this like direct query tables or do custom rule queries that instance of that is trying keep keep the split point that definite imagining what's happening again but what so this spells along poles things like any kind a connection is open and he send more than 1 thing down the expected to die designs of failure is designed a failure when things that fails a happy surprise about how the more fission you don't design failure your page will be go on other pages you might also be going off all the time July are not working week it turns out that that's not perfect and that all the time who could have guessed but I've seen so like I used to write a uh gains those interested in like a few years ago and have for my and that's another case like you expect that instead of revenue understanding and socket and no that's not true you can't that so design failure not this that many other things that others wholesome time-to-failure from them what teams this is very difficult find still thinking about this problem the best thing I've seen so far is independent full-stack teams what I mean by this is essentially when you company gets big enough treaty as lots of small startups each team has operations on it has designed as product on as research on it the and all together they have so small group feeling and they communicate between each of them 1 of the common examples this is quite popular these days is the matrix organization and I'm just like this is the idea that all you have to use the full stack but the people who especially each area sort of meetup across teams like all the opt people come at lunch together twice a week and discussed I like this because it encourages to think and use a small company on big small company persons why I think that's probably it does have some overhead where your to use that interact more formally that after requests of each other like the companies would and the city was like contract interface define between that gets you those system and data model designs free like it retains the defining how they talk to each other regulations even for data model so this is generally what I prefer all become thing and this is the velocity is that I see a lot of people not having solver architects model having just several text not suffer architecture is a very ill-defined term I'm probably 1 maybe I don't know and there's yet it's a person whose specialty is coordination and putting the pieces together the person you go and look at all those models in the abstract without interact it's very common to not have this time especially go coming from a small start-up where again everyone on code base because if everyone understand whole codebase you don't need this person is not important no 1 has to do the hard work of doing that information gathering but once you get big enough you need that person and then also often a big enterprises have a team of specialists software architects who's in the ivory tower at 1 end of campus and think about the thing and it is very simple because of and it's about practical i.e. value having Pratim larger stuff I think having people who specialize in architecture but still are involved in writing software is very importantly not using that particular focus all of you will the this can come back to the 1 thing which is the model with all that
aren't really and I've seen many big sites I run a few big sites that would just a joint model if and they have problems certainly the along the problems you think you have a monolith are just problems of your team in the way you code and going distributed but necessary make them back and you could in some cases you should if you have pages that are more expensive than others you have big funding thing have video rendering these good reasons to start up the gender that system is very good but it's not a bad idea to have 100 Django us because when you have a hundred Jan document that my machine is much easier to those animals 1 doing releases you have 1 repo you can just release the top version of that report is now what we need version . 3 6 of disappoint virgin point for the solution to this version 3 visibly goes to this provision for that's the problem you get with services so maybe just maybe he only but the
think about it and without all thank you very
much I think that so if my she
tha and so
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Zustandsmaschine
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Dienst <Informatik>
Kombinatorische Gruppentheorie
Term
Räumliche Anordnung
Code
Framework <Informatik>
Socket-Schnittstelle
Datenhaltung
Virtuelle Maschine
Informationsmodellierung
Benutzerbeteiligung
Weg <Topologie>
Software
Datentyp
Programmbibliothek
Softwareentwickler
Ganze Funktion
Schreib-Lese-Kopf
Gerichtete Menge
Telekommunikation
Physikalisches System
Quick-Sort
Vierzig
Flächeninhalt
Last
Mereologie
Basisvektor
Digitaltechnik
Beobachtungsstudie
Telekommunikation
Gerichtete Menge
Datenhaltung
Güte der Anpassung
Zahlenbereich
Telekommunikation
Dienst <Informatik>
Socket-Schnittstelle
Message-Passing
Multiplikation
Dienst <Informatik>
Informationsmodellierung
Verbandstheorie
Bus <Informatik>
Pentagramm
Information
Datenstruktur
Message-Passing
Fitnessfunktion
Partitionsfunktion
Bit
Subtraktion
Punkt
Fortsetzung <Mathematik>
Code
Raum-Zeit
Computeranimation
Datenhaltung
Homepage
Spezialrechner
Virtuelle Maschine
Migration <Informatik>
Datenreplikation
Mustersprache
Widerspruchsfreiheit
Analogieschluss
Bildgebendes Verfahren
Zentrische Streckung
Datenmissbrauch
Sichtenkonzept
Datenhaltung
Feasibility-Studie
Verzweigendes Programm
Datenreplikation
Physikalisches System
Partitionsfunktion
Dreieck
Einfache Genauigkeit
Menge
Geschlecht <Mathematik>
Rechter Winkel
Mereologie
Strategisches Spiel
Information
Lesen <Datenverarbeitung>
Tabelle <Informatik>
Datenhaltung
Physikalismus
Einfache Genauigkeit
Computerunterstütztes Verfahren
Elektronische Publikation
Partitionsfunktion
Quick-Sort
Widerspruchsfreiheit
Computeranimation
Virtuelle Maschine
Datenreplikation
Widerspruchsfreiheit
Analysis
Zentrische Streckung
Addition
Nichtlinearer Operator
Prozess <Physik>
Extrempunkt
Versionsverwaltung
Computer
Computerunterstütztes Verfahren
Dreieck
Computeranimation
Virtuelle Maschine
Informationsmodellierung
Datenverarbeitungssystem
Server
Zusammenhängender Graph
Abstand
Optimierung
Widerspruchsfreiheit
Programmiergerät
Bit
Punkt
Gewichtete Summe
Momentenproblem
Extrempunkt
Browser
Computeranimation
Eins
Homepage
Übergang
Last
Perfekte Gruppe
Vier
Prozess <Informatik>
Default
Figurierte Zahl
Parallele Schnittstelle
Gerade
Zentrische Streckung
Softwareentwickler
Sichtenkonzept
Krümmung
Datenhaltung
Gebäude <Mathematik>
Systemaufruf
Kontextbezogenes System
Biprodukt
Zeitzone
Widerspruchsfreiheit
Ereignishorizont
Dienst <Informatik>
Rohdaten
Menge
Rechter Winkel
Geschlecht <Mathematik>
Server
Projektive Ebene
Socket
Ordnung <Mathematik>
Tabelle <Informatik>
Proxy Server
Server
Subtraktion
Web Site
Mathematische Logik
Thumbnail
Baum <Mathematik>
Automatische Handlungsplanung
Zahlenbereich
Kombinatorische Gruppentheorie
Mathematische Logik
Physikalische Theorie
Whiteboard
Socket-Schnittstelle
Datenhaltung
Lastteilung
Virtuelle Maschine
Informationsmodellierung
Knotenmenge
Software
Spieltheorie
Arbeitsplatzcomputer
Endogene Variable
Softwareentwickler
Optimierung
Widerspruchsfreiheit
Minkowski-Metrik
Einfach zusammenhängender Raum
Kanalkapazität
Einfache Genauigkeit
Schlussregel
Mailing-Liste
Datenreplikation
Physikalisches System
Quick-Sort
Coprozessor
Einfache Genauigkeit
Last
Mereologie
Lastteilung
Einfügungsdämpfung
Gewichtete Summe
Gesetz <Physik>
Computeranimation
Richtung
Homepage
Netzwerktopologie
Dämpfung
Mustersprache
Phasenumwandlung
Regulator <Mathematik>
Schnittstelle
Softwaretest
Güte der Anpassung
Ausnahmebehandlung
Biprodukt
Ereignishorizont
Polstelle
Rhombus <Mathematik>
Dienst <Informatik>
Kollaboration <Informatik>
Menge
Benutzerschnittstellenverwaltungssystem
Heegaard-Zerlegung
Server
Socket
Ablaufverfolgung
Ordnung <Mathematik>
Repository <Informatik>
Instantiierung
Lesen <Datenverarbeitung>
Tabelle <Informatik>
Geschwindigkeit
Maschinenschreiben
Subtraktion
Selbst organisierendes System
Mathematisierung
Dienst <Informatik>
Repository <Informatik>
Virtuelle Maschine
Variable
Weg <Topologie>
Informationsmodellierung
Webforum
Fächer <Mathematik>
Reelle Zahl
Hash-Algorithmus
Endogene Variable
Turm <Mathematik>
Verband <Mathematik>
Inhalt <Mathematik>
Datenstruktur
Stochastische Abhängigkeit
Datenmodell
Schlussregel
Partitionsfunktion
Einfache Genauigkeit
Debugging
Wort <Informatik>
Programmiergerät
Prozess <Physik>
Punkt
Matrizenmultiplikation
Versionsverwaltung
Gruppenkeim
Computerunterstütztes Verfahren
Komplex <Algebra>
Synchronisierung
Eins
Datenmanagement
Bildschirmfenster
Stützpunkt <Mathematik>
Nichtlinearer Operator
Lineares Funktional
Dokumentenserver
Physikalischer Effekt
Abfrage
Tabellenkalkulation
Geschlecht <Mathematik>
Strategisches Spiel
Projektive Ebene
Information
Overhead <Kommunikationstechnik>
Normalspannung
Koordinaten
Telekommunikation
Web Site
Quader
Interaktives Fernsehen
Term
Code
Multiplikation
Software
Socket-Schnittstelle
Optimierung
Bildgebendes Verfahren
Widerspruchsfreiheit
Schreib-Lese-Kopf
Trennungsaxiom
Einfach zusammenhängender Raum
Expertensystem
Relativitätstheorie
Validität
Einfache Genauigkeit
Physikalisches System
Fokalpunkt
Quick-Sort
Design by Contract
Flächeninhalt
Basisvektor
Mereologie
Bus <Informatik>
Computerarchitektur
Normalvektor
Unternehmensarchitektur
Virtuelle Maschine
Dienst <Informatik>
Web Site
Punkt
Geschlecht <Mathematik>
Versionsverwaltung
Physikalisches System
Repository <Informatik>
Verkehrsinformation
Computeranimation
Homepage
Videokonferenz
COM
Computeranimation

Metadaten

Formale Metadaten

Titel Taking Django Distributed
Serientitel DjangoCon US 2017
Teil 34
Anzahl der Teile 48
Autor Godwin, Andrew
Mitwirkende Confreaks, LLC
Lizenz CC-Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben.
DOI 10.5446/33211
Herausgeber DjangoCon US
Erscheinungsjahr 2017
Sprache Englisch

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract While some code happily lives on a single server forever, most big projects will have to cross the boundary into running both their application and storing their data across multiple systems. The basic strategies are well-known, but we’ll take a look at what to do as you cross the painful threshold where you can’t run your app as a monolith or store everything on a single database server. Among other things, we’ll look at how to split up business logic and application code to run on different servers, how to scale to handle different kinds of web traffic (read-heavy, write-heavy, and long-connections/WebSockets), when and how to make parts of your code not run inline with HTTP processing, strategies for storing data across multiple machines, and how to structure your engineering team to best cope with all these changes. We’ll also look at a few apparently innocuous decisions and the spiral of bad performance they lead to, and how to recognise some of these common problems so you can avoid them yourself in future.

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