#kubernetes developer

so you've heard of kubernetes but you don't know what it is or you've been playing with docker in containers and you want to know how to take it to the next level today we're gonna take a look at what kubernetes is and see when and where we might want to use it so stay tuned so what is kubernetes before we get into exactly what kubernetes is let's talk about when you might want to use it you're in the situation where you've been using docker for a little while or you at least know what docker is and maybe you have it deployed on a few different servers and this is great and we've used docker compose in the past to actually go through and manage these kind of deployments and they're they're pretty simple for something that's really small but say your website or application makes it onto a big news source and drives a lot of traffic your way and you need to scale up really fast how are you going to go from the three servers that you have now to you know 40 servers 50 servers how are you going to go past the handful of servers that you can keep track of in your mind when you really need to scale out your business in this situation where would you have possibly put a specific container if you need to work with it or how are you deciding what containers go where this is where kubernetes comes in and kubernetes is a platform for working with containers not specifically docker actually just containers in general you can use alternatives to docker to manage the containers also but kubernetes gives you a few key things that we're going to talk about it gives you more that's kind of under the hood it's a platform you can build on it and extend it but at its core what kubernetes gives you is a means to do deployments an easy way to scale and it gives you monitoring let's take a look at how we actually do this with kubernetes so in kubernetes you have a master node so this is the kubernetes kubernetes master and this is part of a cluster so it knows of other servers that you create that you can then deploy containers to the actual process of deployment is pretty simple too so and this way you talk to kubernetes you tell what kind of image you would like to create a container from and you give it some other criteria and it creates what's called a deployment so that would be your applique in this case and your deployment can say a bunch of different things you can specify I need a certain amount of CPU I need a certain amount of RAM I maybe need a specified amount of file storage all of these things are held inside of your deployment and kubernetes will keep track of that for you and when I say keep track of it it's not like when we do docker compose to do a deployment where we just push a container out to run a deployment is something that kind of keeps on going it has a deployment controller that in essence if your application goes down kubernetes is gonna know about it and it's gonna try to everything it can to auto heal so it'll spin another container up and recover for itself because the deployment is not just about that initial launching of the container it's something much bigger in kubernetes next let's talk about scaling so I mentioned before that you're getting more traffic than you're expecting and you need to scale out your application so the naive way to scale would be all I'm gonna deploy one app container per server but that's not necessarily like useful and a lot of cases right like sometimes you're going to be in a situation where that's not the most efficient use of your resources so this is what I would call naive scaling and this is the way like this is a good way to do it when you have a few application servers but if you want to keep costs down you can't just spin up a server every time you need to play a single container unless by chance you're spinning up a server that is exactly the right size for that so the way that scaling works in kubernetes is it'll figure out where to put it for you so scaling a deployment is done by modifying the deployment so the deployment like I said before can hold on to how many CPUs it needs how much RAM it needs it also can hold on to the scale so you can say I need to deploy five different nginx nodes you put them in the best spot given that they have these hardware requirements that might bring us to another situation of how well how am I going to connect to my particular container and that's where another thing inside of kubernetes called services comes into play so say nginx is one of our services we have multiple nodes that are running and we need to connect to those but we want to connect to them in a smart fashion so services let us manage all of these and then they also put a load balancer in front and give us public accessibility to this particular service we can have multiple services just we can have multiple deployments so what you'll see is that you know service a or our nginx maybe maybe we need two containers for that but our database service we only need one container to actually run it so we have those on two separate things and they might be on the same machine or kubernetes might decide to put them on separate machines it really depends on what your scheduler thinks is the best usage of your resources at the time and you can tweak that within kubernetes you can tell it to prioritize and even distribution or you can tell it to prioritize you like fully utilizing the resources on a single node you can write your own schedulers there's there's a lot you can do with this but at its core kubernetes is a platform for allowing you to actually maintain deploying containers into production once you get beyond a certain scale but it definitely works if you're not at scale if you don't have 50 servers that you're working with which are called nodes in kubernetes but even if you're not web scale you can still benefit from kubernetes because it gives you the automated health checks it can give you rolling restarts and deployments so that you make sure that when you deploy a new application you're never cutting off anything that needed access to that service and I've seen extensions to kubernetes that allow you to do things like manage your let's encrypt free SSL certificates automatically so you don't have to do it yourself every three months when you know it's going to be up so for the foreseeable future we're going to be going through kubernetes in our weekly tutorials and actually building out some some mock deployments and figuring out how to use each of these components I hope that you enjoyed this video leave a comment down below and let me know what you're excited to use kubernetes for if you could also give it a thumbs up and share it with your friends that would be sweet don't forget to check out the patreon page if you're getting some value out of code or journey you could really help me out and kind of growing the channel but more so than anything just have a great week

so you've heard of kubernetes but you don't know what it is or you've been playing with docker in containers and you want to know how to take it to the next level today we're gonna take a look at what kubernetes is and see when and where we might want to use it so stay tuned so what is kubernetes before we get into exactly what kubernetes is let's talk about when you might want to use it you're in the situation where you've been using docker for a little while or you at least know what docker is and maybe you have it deployed on a few different servers and this is great and we've used docker compose in the past to actually go through and manage these kind of deployments and they're they're pretty simple for something that's really small but say your website or application makes it onto a big news source and drives a lot of traffic your way and you need to scale up really fast how are you going to go from the three servers that you have now to you know 40 servers 50 servers how are you going to go past the handful of servers that you can keep track of in your mind when you really need to scale out your business in this situation where would you have possibly put a specific container if you need to work with it or how are you deciding what containers go where this is where kubernetes comes in and kubernetes is a platform for working with containers not specifically docker actually just containers in general you can use alternatives to docker to manage the containers also but kubernetes gives you a few key things that we're going to talk about it gives you more that's kind of under the hood it's a platform you can build on it and extend it but at its core what kubernetes gives you is a means to do deployments an easy way to scale and it gives you monitoring let's take a look at how we actually do this with kubernetes so in kubernetes you have a master node so this is the kubernetes kubernetes master and this is part of a cluster so it knows of other servers that you create that you can then deploy containers to the actual process of deployment is pretty simple too so and this way you talk to kubernetes you tell what kind of image you would like to create a container from and you give it some other criteria and it creates what's called a deployment so that would be your applique in this case and your deployment can say a bunch of different things you can specify I need a certain amount of CPU I need a certain amount of RAM I maybe need a specified amount of file storage all of these things are held inside of your deployment and kubernetes will keep track of that for you and when I say keep track of it it's not like when we do docker compose to do a deployment where we just push a container out to run a deployment is something that kind of keeps on going it has a deployment controller that in essence if your application goes down kubernetes is gonna know about it and it's gonna try to everything it can to auto heal so it'll spin another container up and recover for itself because the deployment is not just about that initial launching of the container it's something much bigger in kubernetes next let's talk about scaling so I mentioned before that you're getting more traffic than you're expecting and you need to scale out your application so the naive way to scale would be all I'm gonna deploy one app container per server but that's not necessarily like useful and a lot of cases right like sometimes you're going to be in a situation where that's not the most efficient use of your resources so this is what I would call naive scaling and this is the way like this is a good way to do it when you have a few application servers but if you want to keep costs down you can't just spin up a server every time you need to play a single container unless by chance you're spinning up a server that is exactly the right size for that so the way that scaling works in kubernetes is it'll figure out where to put it for you so scaling a deployment is done by modifying the deployment so the deployment like I said before can hold on to how many CPUs it needs how much RAM it needs it also can hold on to the scale so you can say I need to deploy five different nginx nodes you put them in the best spot given that they have these hardware requirements that might bring us to another situation of how well how am I going to connect to my particular container and that's where another thing inside of kubernetes called services comes into play so say nginx is one of our services we have multiple nodes that are running and we need to connect to those but we want to connect to them in a smart fashion so services let us manage all of these and then they also put a load balancer in front and give us public accessibility to this particular service we can have multiple services just we can have multiple deployments so what you'll see is that you know service a or our nginx maybe maybe we need two containers for that but our database service we only need one container to actually run it so we have those on two separate things and they might be on the same machine or kubernetes might decide to put them on separate machines it really depends on what your scheduler thinks is the best usage of your resources at the time and you can tweak that within kubernetes you can tell it to prioritize and even distribution or you can tell it to prioritize you like fully utilizing the resources on a single node you can write your own schedulers there's there's a lot you can do with this but at its core kubernetes is a platform for allowing you to actually maintain deploying containers into production once you get beyond a certain scale but it definitely works if you're not at scale if you don't have 50 servers that you're working with which are called nodes in kubernetes but even if you're not web scale you can still benefit from kubernetes because it gives you the automated health checks it can give you rolling restarts and deployments so that you make sure that when you deploy a new application you're never cutting off anything that needed access to that service and I've seen extensions to kubernetes that allow you to do things like manage your let's encrypt free SSL certificates automatically so you don't have to do it yourself every three months when you know it's going to be up so for the foreseeable future we're going to be going through kubernetes in our weekly tutorials and actually building out some some mock deployments and figuring out how to use each of these components I hope that you enjoyed this video leave a comment down below and let me know what you're excited to use kubernetes for if you could also give it a thumbs up and share it with your friends that would be sweet don't forget to check out the patreon page if you're getting some value out of code or journey you could really help me out and kind of growing the channel but more so than anything just have a great week

Hey, I'm Nick from the container tools team at Google. And today, I want to talk to you about one of our newest and most exciting tools, Skaffold. Skaffold is a tool that's designed to make local Kubernetes development easy. It watches your local application directories for changes, and can automatically build, push, and deploy your application images to any local or remote Kubernetes cluster, letting you focus on developing your application. Let's take a look at how to get Skaffold running on your application. Skaffold runs as a binary on your local machine. So installing it is as easy as downloading the latest release from the Google Container Tools GitHub page. Alternatively, you can build Skaffold straight from source. Skaffold uses YAML configuration to describe how your application should be built and deployed. You can specify one or more images for Skaffold to build, which Skaffold will tag, and push to any valid document repository. These continuously-built images will be injected into your Kubernetes ideas manifest, and used to deploy new changes to your cluster on every code change. Let's walk through an example to demonstrate a typical Skaffold workflow. Here we have a simple go Hello World! application, which just prints "Hello World!" in a loop forever. We have a docker file that builds a binary from the source file, and puts it into a container, and a Kubernetes manifest that creates a pod from this container image. Skaffold has a built-in command, skaffold init, that will generate a Skaffold YAML for your code base containing default values to get Skaffold running. Let's run it on the code that we have here. You can see our generated Skaffold YAML has one build artifact pointing to our Docker file that builds the image and pushes it to our project's registry. This image is tagged with the git tagging strategy, which uses the latest commit hash as an image tag, though there are several other tagging strategies available. Skaffold also defaults to using the Kube control deployer that deploys from our Kubernetes manifest to our existing cluster, though there are several other deployment strategies available as well. As we run skaffold dev, you can see Skaffold immediately builds the artifact we specified, and pushes it to the target registry. It then creates a pod in our cluster using the image we just pushed. By default, Skaffold streams the logs from the pods it creates, so looking at these now, we can see Hello World! being logged like we expect. One of Skaffold's most exciting features is its file watcher, which watches for changes to one or more local directories on your file system in real time. When Skaffold sees any changes to your code, it will build a new image from source, and deploy it to your Kubernetes cluster. Let's change our print statement up, and watch how Skaffold reacts. As I change the string to Hello Skaffold! We can immediately see Skaffold recognizes that our source file has changed and re-triggers a build and deploy. Watching the logs, we can see them switch over in real time to our new print statement as the new pod is created. Let's take a look at a more complex example to see how Skaffold works with more realistic workflows. Here, we have an application with two services-- a web server and an application server. These services can be built and deployed independently of each other, and Skaffold is smart enough to understand that. Let's go through the same flow we did with the Hello World! Example here to see what it looks like. Running skaffold init again, this time we're prompted for which Docker file builds each image, since there's no way for Skaffold to know that beforehand. In our generated Skaffold YAML, we can see that a build artifact is specified for each services' source code directory, and Skaffold will put a separate file watcher on each of these directories. This means that when files change in one directory but not the other, only the container corresponding to the modified directory will be rebuilt. skaffold dev builds and deploys both parts of the application as we expect, and in the logs, we can see both services are ready in our Kubernetes cluster. Now if I go make a change in the web server, we can see Skaffold picks up the change, and only rebuilds that container. Skaffold's deployer then only updates the deployment associated with the newly-built artifact, and we can see this reflected in the deploy logs. This means your dev cycles are never bottlenecked by parts of your application that you're not working on. These services don't necessarily need to live in the same repository. As long as your Skaffold YAML points to valid workspaces on your local file system, you can use any number of different repositories in a Skaffold workflow, making it an awesome tool for development on microservice-based applications. Skaffold can help speed up any Kubernetes development workflow by getting ops out of your way, allowing you to focus solely on application development. You can find these examples and more in the Skaffold GitHub repository, linked in the description of this video. Contributions to Skaffold are always welcome. If you'd like to learn more about contributing, check out the contributing guidelines in our GitHub repository. Go try it out for yourself, and let us know what you think. Happy Skaffolding.

Hey, I'm Nick from the container tools team at Google. And today, I want to talk to you about one of our newest and most exciting tools, Skaffold. Skaffold is a tool that's designed to make local Kubernetes development easy. It watches your local application directories for changes, and can automatically build, push, and deploy your application images to any local or remote Kubernetes cluster, letting you focus on developing your application. Let's take a look at how to get Skaffold running on your application. Skaffold runs as a binary on your local machine. So installing it is as easy as downloading the latest release from the Google Container Tools GitHub page. Alternatively, you can build Skaffold straight from source. Skaffold uses YAML configuration to describe how your application should be built and deployed. You can specify one or more images for Skaffold to build, which Skaffold will tag, and push to any valid document repository. These continuously-built images will be injected into your Kubernetes ideas manifest, and used to deploy new changes to your cluster on every code change. Let's walk through an example to demonstrate a typical Skaffold workflow. Here we have a simple go Hello World! application, which just prints "Hello World!" in a loop forever. We have a docker file that builds a binary from the source file, and puts it into a container, and a Kubernetes manifest that creates a pod from this container image. Skaffold has a built-in command, skaffold init, that will generate a Skaffold YAML for your code base containing default values to get Skaffold running. Let's run it on the code that we have here. You can see our generated Skaffold YAML has one build artifact pointing to our Docker file that builds the image and pushes it to our project's registry. This image is tagged with the git tagging strategy, which uses the latest commit hash as an image tag, though there are several other tagging strategies available. Skaffold also defaults to using the Kube control deployer that deploys from our Kubernetes manifest to our existing cluster, though there are several other deployment strategies available as well. As we run skaffold dev, you can see Skaffold immediately builds the artifact we specified, and pushes it to the target registry. It then creates a pod in our cluster using the image we just pushed. By default, Skaffold streams the logs from the pods it creates, so looking at these now, we can see Hello World! being logged like we expect. One of Skaffold's most exciting features is its file watcher, which watches for changes to one or more local directories on your file system in real time. When Skaffold sees any changes to your code, it will build a new image from source, and deploy it to your Kubernetes cluster. Let's change our print statement up, and watch how Skaffold reacts. As I change the string to Hello Skaffold! We can immediately see Skaffold recognizes that our source file has changed and re-triggers a build and deploy. Watching the logs, we can see them switch over in real time to our new print statement as the new pod is created. Let's take a look at a more complex example to see how Skaffold works with more realistic workflows. Here, we have an application with two services-- a web server and an application server. These services can be built and deployed independently of each other, and Skaffold is smart enough to understand that. Let's go through the same flow we did with the Hello World! Example here to see what it looks like. Running skaffold init again, this time we're prompted for which Docker file builds each image, since there's no way for Skaffold to know that beforehand. In our generated Skaffold YAML, we can see that a build artifact is specified for each services' source code directory, and Skaffold will put a separate file watcher on each of these directories. This means that when files change in one directory but not the other, only the container corresponding to the modified directory will be rebuilt. skaffold dev builds and deploys both parts of the application as we expect, and in the logs, we can see both services are ready in our Kubernetes cluster. Now if I go make a change in the web server, we can see Skaffold picks up the change, and only rebuilds that container. Skaffold's deployer then only updates the deployment associated with the newly-built artifact, and we can see this reflected in the deploy logs. This means your dev cycles are never bottlenecked by parts of your application that you're not working on. These services don't necessarily need to live in the same repository. As long as your Skaffold YAML points to valid workspaces on your local file system, you can use any number of different repositories in a Skaffold workflow, making it an awesome tool for development on microservice-based applications. Skaffold can help speed up any Kubernetes development workflow by getting ops out of your way, allowing you to focus solely on application development. You can find these examples and more in the Skaffold GitHub repository, linked in the description of this video. Contributions to Skaffold are always welcome. If you'd like to learn more about contributing, check out the contributing guidelines in our GitHub repository. Go try it out for yourself, and let us know what you think. Happy Skaffolding.

hello and welcome to this course on the certified kubernetes applications developer my name is moonshot monomyth and i will be your instructor for this course so about me I'm a Solutions Architect I specialized on cloud automation and DevOps technologies I have authored several best-seller and top rated courses on docker kubernetes and OpenShift as well as automation technologies like a stable chef and puppet this course is the second installment in the series on kubernetes and focuses on a certification let's take a look at the structure of this course we start with a series of lectures on various topics in kubernetes where we simplify complex concepts using illustration and animation we have optional quizzes that test your knowledge after each lecture we have coding quizzes that help you practice what you learned on a real live environment right in your browser the kubernetes certification is a hands-on practical exam so the coding exercises will give you enough experience and practice on getting ready for it more on this topic in the upcoming lectures we will also discuss some tips and tricks to crack the certification exam and as always if you have any questions you may reach out directly to us through our Q&A; section now this is one of the course in the series on kubernetes and focuses on getting the kubernetes application developer certification so a basic understanding of kubernetes is required for example you must know how to set up a lab environment to practice on the certification curriculum does not include kubernetes set up or install so you could set up a learning environment in any way you like we discussed a lot of these in the beginners course you also need a good understanding of Yama language for creating configuration files in kubernetes and a basic understanding of what a master and worker nodes are and what pods replica sets and deployments are we do refresh some of these topics in this course but if you are absolute beginner I highly recommend taking my kubernetes for the absolute beginners course let us now look at the course objectives the objectives of this course are aligned to match the certified coordinators application developer exam curriculum we will discuss about details around the certification itself in one of the upcoming lectures before heading into any of these topics we start with the core concepts we have covered a lot of the core concepts in the beginners course we will recap some of these in this course to refresh our memory such as the kubernetes architecture what ports are and how to create and configure pods etc the next section is on configuration and covers topics like config maps security contacts resource requirements secrets service accounts etc we will then look deeper into multi container pods the different patterns of multi container pods such as ambassador adapter and sidecar we will look at some examples and use cases around these we then learn about readiness and lightness probes and what you need them we will also look at some of the monitoring logging and debugging options available with kubernetes specifically around pods containers and applications we then move on to labels and selectors and then rolling updates and rollbacks in deployment we will learn about why you need jobs and cron jobs and how to schedule them we will then learn about services and network policies and finally we look at persistent volumes and claims for all of these topics we have lectures that makes these complex topics easy to understand followed by coding challenges where you will be practicing what you learned on a real live environment let's take a look at that the kubernetes certification is a practical hands-on exam so it is very important to practice what you learn which is why we have built a custom solution that will give you access to a real kubernetes environment right in your browser along with a quiz portal that provides fun and challenging problems for you to solve you were required to gain a set of different skills working with kubernetes such as how to look for and find information how to troubleshoot issues etc that is why we have questions where you will be asked to find information within an environment we'll also be asked to perform configuration tasks where you will be required to configure and deploy applications and services on the cluster we will test your work and provide feedback instantly we will occasionally make changes to the environment or break stuff and ask you to fix them these are common issues that one would face while working with kubernetes and these exercises will help you troubleshoot and fix issues quickly when you see an error message you should be able to understand what that means and where to look for and how to fix it you need practice you need to get faster one of the major villains in a practical test like the one in the kubernetes certification is time even simple issues like a typo or an indentation error in a yellow file can take a beginner hours to fix this is why we have hundreds of such exercises in this course that will make you an expert and give you enough practice to help you clear the exam well that's all for now thank you for taking this course and I am excited to get started

hello and welcome to this course on the certified kubernetes applications developer my name is moonshot monomyth and i will be your instructor for this course so about me I'm a Solutions Architect I specialized on cloud automation and DevOps technologies I have authored several best-seller and top rated courses on docker kubernetes and OpenShift as well as automation technologies like a stable chef and puppet this course is the second installment in the series on kubernetes and focuses on a certification let's take a look at the structure of this course we start with a series of lectures on various topics in kubernetes where we simplify complex concepts using illustration and animation we have optional quizzes that test your knowledge after each lecture we have coding quizzes that help you practice what you learned on a real live environment right in your browser the kubernetes certification is a hands-on practical exam so the coding exercises will give you enough experience and practice on getting ready for it more on this topic in the upcoming lectures we will also discuss some tips and tricks to crack the certification exam and as always if you have any questions you may reach out directly to us through our Q&A; section now this is one of the course in the series on kubernetes and focuses on getting the kubernetes application developer certification so a basic understanding of kubernetes is required for example you must know how to set up a lab environment to practice on the certification curriculum does not include kubernetes set up or install so you could set up a learning environment in any way you like we discussed a lot of these in the beginners course you also need a good understanding of Yama language for creating configuration files in kubernetes and a basic understanding of what a master and worker nodes are and what pods replica sets and deployments are we do refresh some of these topics in this course but if you are absolute beginner I highly recommend taking my kubernetes for the absolute beginners course let us now look at the course objectives the objectives of this course are aligned to match the certified coordinators application developer exam curriculum we will discuss about details around the certification itself in one of the upcoming lectures before heading into any of these topics we start with the core concepts we have covered a lot of the core concepts in the beginners course we will recap some of these in this course to refresh our memory such as the kubernetes architecture what ports are and how to create and configure pods etc the next section is on configuration and covers topics like config maps security contacts resource requirements secrets service accounts etc we will then look deeper into multi container pods the different patterns of multi container pods such as ambassador adapter and sidecar we will look at some examples and use cases around these we then learn about readiness and lightness probes and what you need them we will also look at some of the monitoring logging and debugging options available with kubernetes specifically around pods containers and applications we then move on to labels and selectors and then rolling updates and rollbacks in deployment we will learn about why you need jobs and cron jobs and how to schedule them we will then learn about services and network policies and finally we look at persistent volumes and claims for all of these topics we have lectures that makes these complex topics easy to understand followed by coding challenges where you will be practicing what you learned on a real live environment let's take a look at that the kubernetes certification is a practical hands-on exam so it is very important to practice what you learn which is why we have built a custom solution that will give you access to a real kubernetes environment right in your browser along with a quiz portal that provides fun and challenging problems for you to solve you were required to gain a set of different skills working with kubernetes such as how to look for and find information how to troubleshoot issues etc that is why we have questions where you will be asked to find information within an environment we'll also be asked to perform configuration tasks where you will be required to configure and deploy applications and services on the cluster we will test your work and provide feedback instantly we will occasionally make changes to the environment or break stuff and ask you to fix them these are common issues that one would face while working with kubernetes and these exercises will help you troubleshoot and fix issues quickly when you see an error message you should be able to understand what that means and where to look for and how to fix it you need practice you need to get faster one of the major villains in a practical test like the one in the kubernetes certification is time even simple issues like a typo or an indentation error in a yellow file can take a beginner hours to fix this is why we have hundreds of such exercises in this course that will make you an expert and give you enough practice to help you clear the exam well that's all for now thank you for taking this course and I am excited to get started