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Habitat 201: Habitat in the Ecosystem

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Habitat 201: Habitat in the Ecosystem
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Habitat is an open-source framework that gives modern application teams an application-centric automation platform. Build, deploy, and manage modern and legacy applications with Habitat. Habitat plays well with many container technologies such as Docker, rkt, Mesosphere, and Kubernetes. This talk will explore some of the ways Habitat fits into the broader ecosystem.
Context awareness Building Service (economics) Mapping Code Multiplication sign Software developer Moment (mathematics) Paradox Bit Distance System call Product (business) Product (business) Wave packet Data management Different (Kate Ryan album) Self-organization Right angle Spacetime
Dataflow Similarity (geometry) Pattern language Right angle Quicksort Rule of inference Condition number God
Pairwise comparison Standard deviation Observational study Divisor Direction (geometry) Set (mathematics) Bit Chaos (cosmogony) Mortality rate Computer programming Number Bit rate Causality Different (Kate Ryan album) Natural number Term (mathematics) Right angle Physical system
Autonomic computing Device driver Bit Frame problem Physical system Hypercube
Axiom of choice Time zone Context awareness Transportation theory (mathematics) Multiplication sign Similarity (geometry) Cartesian coordinate system Rule of inference Frame problem Product (business) Centralizer and normalizer Goodness of fit Angle Authorization Self-organization Right angle Iteration Hydraulic jump Physical system
Axiom of choice Complex (psychology) Run time (program lifecycle phase) User interface Code Multiplication sign Direction (geometry) Mereology Dimensional analysis Mathematics Strategy game Computer cluster Hypermedia Cuboid Endliche Modelltheorie Physical system Service (economics) Block (periodic table) Web page Computer simulation Sound effect Physicalism Bit Instance (computer science) Process (computing) Order (biology) Chain output Right angle Pattern language Quicksort Remote procedure call Physical system Writing Server (computing) Functional (mathematics) Service (economics) Patch (Unix) Virtual machine Maxima and minima Event horizon Twitter Product (business) Goodness of fit Internetworking Operator (mathematics) Program slicing Operating system Traffic reporting Computing platform Directed graph Pay television Server (computing) Weight Consistency Physical law Cartesian coordinate system Software maintenance Radius Visualization (computer graphics) Software Data center Point cloud Video game Object (grammar)
Point (geometry) Complex (psychology) System administrator Multiplication sign Set (mathematics) Event horizon Product (business) Different (Kate Ryan album) Operator (mathematics) Program slicing Cuboid Directed graph Inheritance (object-oriented programming) Server (computing) Interface (computing) Sound effect Cartesian coordinate system Entire function Software Order (biology) Video game Normal (geometry) Right angle Cycle (graph theory) Vacuum
Service (economics) Consistency Configuration space Right angle Endliche Modelltheorie Cartesian coordinate system Disk read-and-write head Event horizon Portable communications device
State observer Service (economics) Information Computer file Direction (geometry) Virtual machine Planning Perturbation theory Cartesian coordinate system Entire function Product (business) Word Process (computing) Video game Data conversion Cycle (graph theory) Figurate number Physical system
State observer Group action Service (economics) Information State of matter Consistency Range (statistics) Cartesian coordinate system Subset Process (computing) Ring (mathematics) Strategy game Software Network topology Self-organization Video game Right angle Cycle (graph theory)
Axiom of choice Complex (psychology) Scheduling (computing) Group action Scaling (geometry) File format Neuroinformatik Medical imaging Different (Kate Ryan album) Kernel (computing) Single-precision floating-point format Physical system Arm Software developer Electronic mailing list Shared memory Computer simulation Bit Instance (computer science) Twitter Virtual machine Hand fan Data management Process (computing) Workload Ring (mathematics) Order (biology) System programming Pattern language Computing platform Quicksort Figurate number Cycle (graph theory) Web page Point (geometry) Slide rule Open source Connectivity (graph theory) Cellular automaton Library catalog Branch (computer science) Mass Product (business) Number Template (C++) Goodness of fit Term (mathematics) Googol Computer hardware Authorization Data structure Computing platform Default (computer science) Distribution (mathematics) Scaling (geometry) Server (computing) Interface (computing) Code Computer network Line (geometry) Group action Cartesian coordinate system Frame problem Word Online service provider Software Video game State observer Building Run time (program lifecycle phase) State of matter Code INTEGRAL Multiplication sign Combinational logic Mereology Bookmark (World Wide Web) Formal language Data management Bit rate Semiconductor memory Befehlsprozessor Formal verification File system Cuboid Process (computing) Endliche Modelltheorie Extension (kinesiology) Service (economics) Common Language Infrastructure File format Moment (mathematics) Computer Entire function Microprocessor Degree (graph theory) Type theory Googol Internetworking Vector space Computer science Website Self-organization Right angle Physical system Functional (mathematics) Server (computing) Service (economics) Divisor Link (knot theory) Virtual machine Portable communications device Twitter Revision control Workload Population density Internetworking Software Gamma function MiniDisc Analytic continuation Multiplication Consistency Cellular automaton Projective plane Analytic set Library catalog Sphere Template (C++) Single-precision floating-point format Kernel (computing) Point cloud Object (grammar) Fiber bundle Communications protocol Local ring
Trail Set (mathematics) Numbering scheme Continuous integration Mereology Proper map Formal language Goodness of fit Software testing Endliche Modelltheorie Series (mathematics) Analytic continuation Hydraulic jump Physical system Focus (optics) Surface Moment (mathematics) Sound effect Bit Cartesian coordinate system Film editing Process (computing) Phase transition Right angle Automation Thomas Bayes
what so I am going to say I'm really glad that we get to do this talk again and I think there's been a really good call out to context in both of the keynote that we saw yesterday and today right we heard from Alaska Airlines right writing code actin context is meaningless and today Adams talk focused on understanding what we're doing understanding like what the context is from the things that we're building we can go forth and as we possibly can i'm SUCH organ look at a lot in this talk about habitat in the ecosystem but I should introduce myself so I George I'm product marketing manager at shaft and but I want a lot of different hats in my time there and before product marketing and business development work the partner ecosystem which I think is appropriate for the stock but before that I was doing training and services of writing on ship code and engineer and a background yeah but but so what that meant is that in my time which I I spent a lot of time on airplanes they do a lot of travel all those different roles require a boatload of travel the and just in my time at Shep alone I have covered the distance from the earth to the moon an entirely back in not quite entirely the map yesterday and once I get back from some trips in September I will be back on but for now it's a little bit of a space cadet the but but what that what that means is gone from really interesting places in my time at checked and I think by far the most interesting place that chips and me was India and I think I find it the most fascinating by far because I was struck by this massive paradox just moments after leaving the airport and the paradox is this the
Indian traffic is anybody there was in I the books and so if you haven't been if you don't know what I'm talking about but I think Southeast Asian countries like maybe Thailand Vietnam have very similar traffic patterns but Indian traffic by far is like the normally if that I've seen is this chaotic warm of cars and pedestrians and top tags and and just all sorts of things coming at you and it has no clear sense of lanes or rule that were discernible to me but on your personal space and and like and it's a very active thing right because when you're driving along you're diving through potholder kind of you manage road conditions and there
are not only pedestrian their towels on and there's this likes and warm of motorcycles and mopeds and talked out and like it everywhere and it all just like flows and so being in this situation I like my westernizer like 0 my god this cannot this cannot see With this not this is a word and so I did what any good Westenra would do in that situation and I pulled out my phone has like look steps
is really true so and so was by International Data planetary program like what can I find is this is this really reality or not I found this of study from the University of Michigan in 2014 under looked at per capita mortality rates uh for vehicular accidents 400 new population and what I found when I look at that study that should be that's
right like it is way more dangerous by to be in that system in India there's like at a higher rate of of particular fatalities and so I thought I get that man like if I if I stick around like I'm going to die and I was in India for a couple weeks I and I not dead yet and and I really wonder what's you know what's really going on cause when I looked it actually seemed to be a fairly safe systems despite all of the chaos so certainly a dealer bit deeper like a completely it out on traffic sets during this trip really get international data and I and I I'll give you kill the R & this is not a direct one-to-one comparison when you look at this way at the top 5 leading factors that expose you to a higher rate of fatalities in traffic and things like drunk driving rates uh you know safety standards of been mandated are you required to wear a seatbelt things of that nature right and so up with all of those factors India lag significantly behind the US which means the numbers you in a direction hard so it's not like a real direct 1 1 comparison in terms of the driving system which our so I sorry I decided to try to normalize those numbers make it more of account about a person and and when I did I took just the 1st factor alone drunk driving rates which are like huge in India it's like 70 % versus 31 % US I will be the 1 in road to the last couple of decades so you know we have an advantage there and just trying to normalize those numbers taking 1 step closer to have profound comparison this rate and like world that is not a small difference that is a stark difference it's almost like safer by a factor of 2 to drive knocking out it's 1 that is to drive in the US right what is going on right my initial
reaction was I don't understand how is that even possible like that this cannot be right like how could that right and
that's and things like that like I thought that all over the place like how can that possibly be favor the next frame what's going on they decided they in a little bit deeper and it
turns out that an Indian drivers have the hyper aware of their surroundings it's very active process and if you've ever seen in the in traffic go and it's very noisy there's lot of honking that's going on and it's not like rude honking it's almost like a like a system of radar brain like you see that something is approaching use like the solidarity move over person excuse over the entire for fleet adjusts real-time so you end up with there is this system of hyper where hyper vigilant autonomous actors and and and it requires those those actors to be more engaged ultimately to be safer and more aware of their surroundings and we you get is a much stronger resilience system
then you get with something that has rule the dictated by central authority like from transportation and maybe make things also state that were not as engaged as we could be 1 were driving so India really challenged my assumptions about things that I knew I thought I knew about the large-scale traffic systems and how they work and I think in a similar way habitat challenges the things that we think we know about how large-scale distributed applications should work the forget do in this talk we're
gonna look at 2 things look at 1st the question what is habitat if you're here for adoption remains 101 I think in a lot of good detail organ liquor from a slightly different angle I did to give you a little more context right like why this habitat meet the choices that does and and an understanding that scope of what is habitat and why does it operate this way then we can look at how habitat plays in the larger ecosystem and where where it fits into a larger whole so that let's jump into what is habitat I gotta tell you as a In this new role of product marketing at shaft on 1 of my biggest challenges has been trying to figure out how to succinctly talk about habitat when we start digging into habitat there are a lot of moving pieces in the time different concepts and I usually get you know the question of Haiti you know what is habitat you know can you me a short fiction it's like the idea of 20 minutes and I got a few iterations of this and I don't think that of my time frame is this really getting shorter but I think zeroing in on the right concepts of if we can make that all of that the excreted out this
picture of a few weeks ago and I call it box box on and if any of you've met block on the sales team and but he wanted to help visualize what's really happening in habitat and so we put something together we put on Twitter and it seemed to get a lot of uptake people really responded to it I think it's really good visual model what's happening by just by looking at the picture long and things always entirely clear what's up with there's were going to go through it we're gonna go through it from left to right so this is basically what happened right
and uh in the traditional computing model of the world right when were managing servers but the challenge here is that we we tend to think of our applications as just those bits of code that we wrote like the basic inputs and outputs they're giving our business value right and that is the only thing that we usually care about at the end of the day and we have this layer cake of dependencies around right we think that it's just that 1 box but in order to manage that 1 part traders bunch things when we need to do before and after we go there so I checked we call this infrastructure 1st of all we call it infrastructure 1st development because if you're really trying to manage their applications the we need to do is you need to start with a server right and that's a renewed and operating system in the days of physical data centers right mn yet like rack box or maybe in the cloud right get to go provision at the start some the and that starts with some sort of operating system choice the new thing about where that machine is placed right media like which rack was going to live in a in the cloud right which availabilities alone but once you have those 2 things right where kissing living has a going operate call them like I can now install runtime right where that platform on which those functions that I wrote it going to be executed and once I have all of those things great now I can get to my application i and that's a long time the value of the lot of things you have to do 1st before you can actually start writing any new the things that keep your business some some actual work and you are a chap cont so hopefully you're doing all of this which congratulations were also on an army during the day part with chef right the next part is for how do I manage this application once I have it ready to go right how to write a play and I make changes to it right patch my operating system dried but I do that ongoing maintenance I mean doing which right media doing of an external tool maybe have a different way the application artifacts are created radius dimension dependencies a bad thing brings with it and so you know you may have a tool 1st media doing with automation already right but then once we run application production and we make sure this process is doing the right thing right so we're going to get a monitoring report that on as an external I the we usually need to have some sort of remote execution strategy right like for various things various have events that occur in our infrastructure we will need a some sort of orchestration taller some weights text remote commands you know we have historically very complicated deployment patterns like in order to deploy this object I need to stop server a so I can stop server B and an update server b before I a and and update server be again and start the before I start a and like holy cow idea that was huge right so so will usually have a need for that there and service discovery maybe not so much of the thing and hard-coded legacy data centers right but even in the cloud when you have ephemeral instances coming and going e to figure out a wire them all together and so some really great tools for that began right another thing that we need to manage just bolt onto the culture and that is how it comes together right and it's usually in that order because that's just how we built a made start cobbling these things together as we know needed them and that's and that's how it evolves right it's messy it's destroying it it's it's a little bit slow I think containers but deftly took a step in the right direction and containers give us a way to the package upper applications and on the run time in this you know portable immutable artifacts and that a new law that works the same way everywhere with consistency right and it allows us really interesting things like get our effect put it up on the internet somewhere right download it run of 1 commander like whom we off to the races right like I can start writing things from application right away I'm and we short at that time the value right and I think this is why Dr. resonate so heavily with developers because at the end of the day just wanna write application and this is a nice short easy way to do that I think containers resonate a little bit less with the operations ground and because if you run these things in production right as we mentioned before you know you know that all we really done is move that complexity further up the chain right as we take steps forward running in production all those dependencies from the layer cake start creeping back in right now that I have this immutable objects how my going to make changes to it how my going to update software on how my going to deploy once I have it right of modern right how can I tell what's happening inside of this obscure immutable process but I put it monitoring inside my container to operate outside the container right what am I supposed to do but that's all real life a remote execution in orchestration right we never really solve for that so that's still a need the and then of course right with much micro-services coming in and out of service potentially the only define each other service discovery is a very real concern in that ecosystem aren't and so right we need the bullpen on and again right somehow like all those dependencies of layer cake still came back around to bite I think that that layer cake really it's just a remnant of how we have built machines in the past like this is just the way that we've always done and I think part of of problem is that when we think about our application we think it's just that 1 box right there right it's just like that 1 central piece in the larger layer cake but uh that's I think that's only the like those inputs and outputs the just the most obvious part of where we derive about anybody it's run these things in production knows that where we really have value right is when we put that in production into the hands of users right it's not just that 1 slice is that entire stack that brings you back you right is an entire stack they you're writing your business on right is an entire stack and its availability there is really key to running those applications and serving on the market right like that it's it's 1 it's 1 big cohesive the and then you know we we saw just look at our applications said is that 1 box in like this layer cake of complexities around it but it's it's really more cohesive the narrative the whole thing that matters but we don't treat it that way we never see it that way the so I
think de boxes taught us many things that In what like the summary years that about assuming point as a label I think 1 of more important lesson there has been that if we take a step back to holistically look at everything that we need to manage around our applications and the only way that we can really do do that effectively is if we not only look at everything that happens in development but if we look at what it takes to really run in production as well right and so having learned the lesson that we have from the DevOps movement I think maybe it's time to step back and re-examine what is the right way to run applications knowing that what really matters is that entire layer cake of complexity not just set 1 slice we think is where we get a value that's the that's the assumption that habitat challenges right so the question of what is habitat right habitat basically tries to take that layer cake and it posits that that's what your applications need in order to run or everything the applications need in order to run right it's like the entire life cycle of things that your application needs that is actually the application yeah so if the if the entire layer cake right it's not just that 1 tiny slice of the application box so our that is what we call application automation and that's when you when you hear say things like automation the travels with the application we see a lot for have that that's really what that means right that we're taking that external set of dependencies and looking at everything their applications need to run right from initial deployed to normal software operation like cycle events all the way through to decommission right and like all of that for the entire span everything that's necessary that is really a application and within super mind blowing to me like to my sysadmin this engineered like distribute systems mind but is that if you do that right if you manage your application that way what happens is when you deploy software you deploy everything that your application means along with it and this immutable self-contained like self-managing package and if you do that I had the
super super interesting side effect right and that side effect is that if we bundle everything the application needs into that 1 immutable artifact of what it means is that we can build that artifact once we expose an interface that alters the behavior of that artifact for different points of its life cycle and
when you deploy when you say I want to go to this particular infrastructure great right like set up a reconfigure event and whether I'm going to deploy on on-premise or whether I'm going to deploy in the interview us writer whether I'm going Topaz service great inuit configuration and I need to do for that already built
and and so you get like real that true portability and repeatability inconsistency benefits from treating applications that way so have the foot that the traditional model
of the developing from the infrastructure up on its head right it just looks at what the application really need right service with that imagine that then work our way down the infrastructure so what is habitat
yeah the habitat is the way holistically package self-contained applications and run them anyway habitat for over 2 i the well so this is a very deliberately chosen words right and and a they started saying that even yesterday when we force to the stock and the immediate follow-up question I think there's a lot of densely packed concepts into those very deliberately chosen words so very next question usually is wall how does that work and so I I think some of you were here production remains a 101 talk but here's the here's just a high-level enough of how habitat works to keep the conversation going through info about habitat works in 2 minutes or less very ready go has so whenever
you're developing you have access to habitat studio habitat studios usually on your local machine but conceivably that could be hosted elsewhere like I like a host to build service to me when there's going to talk about that 301 but in that studio what you do is you can model all of the observation that your application needs on inside of a planning that plan includes directions about how to build this operatic of figure it out a run it right all of those things you need for the entire life cycle include the build system and that build system processes those instructions and spit out the doctor hot file is top
hot for Habitat artifact it is not
hard because we let I have habitat the supervisor process perhaps soup and a supervisor knows how to manage those top artifact you just created so supervisors connect with other supervisors the former gossip brain and that ring gathers and shared information about the state of all the other supervisors in the software that they're running on the supervisors basically make observations about their neighbors right spread rumors about what's happening in the rest of the supervisors then go try to verify those rumours of when you end up with is this eventual consistency of the entire range to sentence of those supervisors can self organize into service groups right which is just a subset of supervisors that army to act together and what you can view in the service groups is you can use that to define topologies or update strategies were you know how these things managed secret securely our or just you know anything you need to do demand that the life cycle of an entire application that can how it all comes together that's not bad is better than a minute and a half and so so what is habitat
right habitat is a way to holistically package self-contained applications and run them and if you look at any of the the that we've done or the webinars when you press around it I'm habitat gives those same sorts of self manageability uh self-aware benefits and to all applications they don't just to be containers for microservices and and when you approach a applications this way right where you end up with is a network of hyper where self-managing autonomous actors the run in a distributed system that does not have any 1 central authority and and when you do that right that creates a large-scale highly distributed and fault-tolerant resilient systems so that get more resilient to become larger 1 of things that I didn't mention is in that in that gossip ring right we have a certain number of habitat supervisors if you add more superadditive we you get are more observations and more verifications so as you add more supervisors the ranking gets stronger right they you may get the stronger it gets and it's a fundamentally different approach of not only in managing distributed systems right but for managing applications we end up with is portability system the safer systems are more reliable and annotated challenges some version of our assumptions of what are applications really are in and what all you need to run so looking at what habitat is right how it operates white make those choices of let's look at habitat in the larger ecosystem what so we launched habitat almost exactly a month ago happy almost 1 month birthday habitat and and when we did our there was a there there's a lot of press I read a lot of what was happening kept tabs on that and I think 1 of my favorite pieces press came from Wired magazine and in this wired magazine article by that author looked at different advancements in computer science and biological computing models and what different markers were there along the way and it and it put this blob of Texoma read it I make sure I get it right so the the article says biological computing is also how Google Twitter and other Internet giants now think about building and running the mass online services this isn't software that runs on a single machine serving millions upon millions of people around the globe it software that runs on thousands of machines spread across multiple computer data centers the software runs this entire service like a biological system a vast collection of self-contained pieces that all work together in concert it can readily spread those cells of code across machines and when machines break as they inevitably do they can move that code to new machines and keep the whole lot to and that article goes on to compare habitat this organic model computing really care about managing this overall larger organism with communities strong a hyper where hyper enabled cells if you look closely at those cells right those cells should have everything we need in order to manage their entire life cycle which is how we start putting this all together and poignant so a container ecosystem aims to treat machines like vast biological systems right that act together in concert review call the challenges of managing containers right there's all this extra layer cake dependency on top is external to that self right and we don't treat it as 1 cohesive object so what habitat is trying to do right is take that layer cake of complexity and bundle it all into 1 small strong self contained truly portable package so I have a that focuses on making very strong computing cells if you're paying attention the boxes 1 of things that I didn't talk about when we talk about containers was workload placement and conveniently escaped the vectors that were going next but but when we look at managing the entire larger no biological organisms that is our suffer defined business and all of the different applications that we're are that through circling into into a larger whole but Google for a minute the I'm so Google has been running containers uh at scale for over a decade ran into this vast containerized Our approach to computing that the state of their entire business around right like this is what we will as and good been doing a long before we had things like Dr. or rocket right recent explosion of technology around the container ecosystem so you could use a been around for years right just used to be a horrible pain Demand anybody ever hear tried work with a lot them and thought about i'm so great I Dr. helped make containers more mainstream and more accessible and a lot easier to consume and set up right so however Google has been doing this for a long time frame and Google uh interesting they I found out that Google has 7 products with over 1 billion users billion with a b like let that sink in right 7 products of 1 billion users Google is managing the computing needs of the planet and just unprecedented scale and we do it in containers so Dr. came along right and then a Google Open Source communities right and communities is Google's on container management platform of n communities was open source as a way of showing the rest of the industry how Google does right how do they approach these large-scale problems of analytics compute and storage and tackle it well and so what happened over the last couple of years in a container ecosystem is now there's this escalating arms race of technology to help the Fortune 2000 figure out like how to do it The Google Way and if you look at the container ecosystem of pretty much all that happens and the way the way that you get there is is pretty much what this magic i factor right you have containers for that portability right you can ship these workloads around with consistency and and then you have a scheduler for workload placement I am a member so my my 1st experiences schedulers was the Apache measles from anybody were measles if you folks right and so but what Jesus this allows you to do is have these microprocessors they're running for you know x amount of time and as you need them right within milliseconds it will wake up this process it will allocate resources to it you can call on it you can get function that are there and as soon as it's done cool we can put it to sleep and let it go back into the pool and it does so with remarkable speed remarkable scale and I remember the 1st time I saw schedule like that but this is the future of computing and is 1 of those aha moments like the 1st time I use chef right like the 1st time I cobbled together but tools to make continuous delivery pipeline inside go right it's like that is the future and and value like if you haven't played in a container ecosystem to this degree of you would you will hopefully will have the same experience from but right you uh you have the schedulers that move your workloads around as needed on demand and you get I enormous benefits in terms of optimizing for hardware you get like massive compute density and it's it's really rather impressive on but when you do that right there's a lot of complexity that comes with that right so if I'm going to move a container across a grid of machines there are certain challenges the you have with that right like data persistency for example what containers do for data persistency the right to local file system or from the move their cost machines all crap that local file system needs to be shared across networks and how however I do that securely is my networking even set up to be able to do that for right and so there's usually some sort of cluster management layer on top of all that that helps so that's that you're actually do its thing across a wide swath of machines and so right that cluster management system the really search and a tying those bits into into that larger biological organisms that is habitat plugin the the just and talk a little bit about those profits packaging and post-processed packaging is a fancy way of saying that a habitat linked let you take the 2 things we care about the perhaps you and that heart artifact that we created and packaged those into and infrastructure appropriate image format so at launch that means that we have support for I Dr. BCI measles format containers I'm as the images that we have right but happy 1 month birthday habitat still very young i it's conceivable to think that we will have other runtime image formats like a like any my sites in the CC to like whatever the words format is and and you'll probably see things like that however AP launch we launched with support specifically for containers because the larger container ecosystem I think is very complementary to the types of problems habitat is trying to solve all so we work at the number of partners at launch I mean star with measles and so
again right me this distributed systems kernel I does the type of scheduling that we were just talking about to but me the sphere has an DCO as the data centre operating system which is uh that that cluster management platform is the number of tools to manage that type of great computational model of and within that Marathon is the container management platform so a words with habitat the or I guess rather wait American works on is that marathon supports 2 different types of container formats book me those native format and Dr. format containers on and in order to make this thing run you need a cradle abilities on that says I need this much compute right I need this much memory here's 1 gonna live right like basically describes the resources that are needed for this application and you take that definition along with the container image you feed them to marathon and marathon glycans and does thing scandals that like runs school so when you use habitat to create a me those image our measles format container with like have package exporters those on this will you get you see on standard out right now a big blob of Jesus on the described take like this is what you would need to give a marathon along with this container image a disgrace for you and your good I so a couple things to note here that the URI portion is active very important for measles like news no word I go pick up this image that I just created for you am and so in this example right it could be storage on cloud in google right could be a 3 could be any you right it can even be local file system and so that's you know that's kind of what we have today and that's what we have launch right it's it's we know that it works and it's a little bit clunky because they have to take that we have to manually feed it to me this fear right now but we know that it's there but if you look at the project page for habitat and in a lot of measles work you'll see that there's kind of wish list of next steps in places the we could go on so if you're going down this right here the things you need to know the the habitat supervisor and has a specific port needs for that gossip protocol but those have to be opened manually today by hand when you get things to marathon and marathon no has an artifact store in which if they have an artifact store right we should be able to take this tarball and give it to the artifacts for instance for recreating that adjacent some for you anyway right if we have those 2 components will then we should just be automatically able to load that to bear upon the API right and like just smooth that transition to right now it's it's like a manual kind of clunky process that seems like an easy contribution to make in an and take that forward but but of a marathon has a few different package format and but conceivably we could do little work there so the marathoners fans would adopt hot while it is and then you have to can jump through all those who you just give it the heart refund knows what to do from there and the other things uh going there were going on there and you can see those In the habitat docs our communities we did a lot of work with communities again communities is Google's container management platform and a communities is at the heart of Google container and that the heart of things like tectonic which by for while yeah I and community supports 2 different types of container format of the the ACI adopted both of which we have support for as well along with me those rated it's the have package export into this format thing you want export might PanImages goes so the pattern here rate is that habitat makes creating those image formats a lot easier and more manageable right it's a habitat worries about creating those containers and then communities worries about managing the cluster and running those containers across a distributed grid of machines but if you look to the future state works for communities and communities runs of what it called pods I. pods are interconnected groups of containers that all need to work together in some some way she performed on at launch we have single pod single container part support of for communities and we show you how to do them habitat box of a combination is very similar right has its own language for describing will want to this container need in order to run right tell me something about it and give me the image format and if you give me those 2 things great I can run with it and and it's so it's very similar to the work with the COS in part right the future state is also I think very similar I will 1 we wanna get multi container port support I'm still working on that is very actively being developed and there's a lot of very active development work going on communities right now and and when we export your container into either CI formats will why can't we just generate that gambling you need for the application and the way that we do for me that I should be able to do that that seems like a fairly easy contribution make up and the same thing right I mean it makes your gossip ports are open because they aren't by default inside that pod I'm so there are a couple of to do is there I think we see the same sort of pattern emerging and the same sort of integration pattern would probably be true with Dr. doctor has warmed right and which form you have you have dance distribute application bundles of many would be the same thing there and so the pattern is habitat and simple the management of creating containers and running them and you're cluster your banded of choice then you a scheduling and placement the of work it we launched with support for rancher and rancher is a container management and catalog system so it's it's actually like if you look at it uh it shows you collections of containers and let the presenting a different application but moles actual consumers on is it's a very nice portal interface for being able to do that and rancher works with me those and words with communities but which we support also works with swarm which conceivably pulsing patterns and and also manages habitat and catalog templates and natively uh that documents are really spot and so if you follow that link up which it will be shared in the slides and you can see a white world steps are you need in order to manage habitat with branches but before we dive into a general QNA I'm going to talk about some generals the question is that I seem to get when we talk about habitat and and the ecosystem so there are there are a couple of common questions that we hear from uh when we look at the larger ecosystem someone this habitat replace containers and hopefully from talk it's been made clear that the answer that is no right habitat is a different way to think about what your applications need in order to run and package those up and make it easy to run in the in the container ecosystem what that means is we make it easier to generate those containers and put in all things you need because it's just another habitat and point good so the answer that is it's not habitat were containers it habitat and containers a an extension that right we just covered this right this habitat negate the need for a container management system no 0 right habitat again managers creating those containers on still in order to get the benefits of what the container ecosystems trying achieve overall you still need that scheduling capability you still need cluster management in order to be able to pull that off so it's not habitat or a container management platform it is habitat and contain arrangement yeah I'm just covered this 1 but recovered again because of this we get this question all the time this habitat replace checked and I wanted to be a very clear unequivocal no it does not replace and so Schepers amazing for managing your infrastructure I model that kind of infrastructure complexity and anything it does a really good job at that and in fact most of us have probably had ship enough to work our way up through that layer cake of dependencies right and we can do it cool on habitat doesn't care about the infrastructure habitat can manager and structure you still need a manager infrastructures Stoneleigh provision servers you still have networking and storage of provisioning Nidrei all of that still needs to happen you still need to do that methodically something to do with compliance share is a very grateful for being able to do that habitat starts with the need the reapplication and works its way down the infrastructure oppose the chefs like infrastructure 1st approach so that you probably meet in the middle somewhere right where that line exactly know let's talk again in a few months for using it very heavily but right it's not habitat or shed its habitat and ship and I've done this question a couple of times and this habitat replace Jenkins and I got that question my 1st reaction was like what
like what is even happening there like that why is there such a but as as I thought about it right I think it's because we use language that says things like habitat helps you build application artifacts right and and Jenkins helps you build application artifacts on this on the surface I think were really the question is asking is you know not just that that actual build system but like to actually really need a CI system right and the and
so habitat doesn't replace the ISIS like all of it's it's a very simple packaging technology and you even see 1 of things you can do is you can run some tests as part of that that that that process however and it's not a refined system for but you know uh testing all of your upstream dependencies are having like a series of bayes gave the you would get with any good workflow solution and and if you use shall automated workflow feature shall horribly brings with it a built cookbook that actually helps you do all of that and go through the standard build phases that you would with you know proper governance models and tracking of everything that's happening and and that build cut but actually has a really neat effect in that that we go past continuous integration and we even go past continuous delivery which is the focus of automated and workflow feature but we go all the way to continuous deployment because habitat knows how to a look in its depot for updated artifacts and then just go ahead and deploy those so when you use the moment tandem you actually get to continuous deployment scheme very very quickly so it's not habitat wore a CI system it's habitat and jump on it or you know whatever the axis the so that set of think that is that is my tour of the a habitat put in an ecosystem anything we still have a little bit thank you