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      Using the context Go package


      Updated by Linode Contributed by Mihalis Tsoukalos

      Go is a compiled, statically typed programming language developed by Google. Many modern applications, including Docker, Kubernetes, and Caddy, are written in Go.

      Running a go command is as simple as:

      go run [filename]
      

      The context package provides contextual information that a goroutine may need such as how long it should run and how and when it should end. It can also pass informational key-value pairs for use down the call chain.

      In this guide you will learn:

      Before You Begin

      You will need to install a recent version of Go on your computer in order to follow the presented commands. Any Go version newer than 1.8 will do but it is considered a good practice to have the latest version of Go installed. You can check your Go version by executing go version.

      If you still need to install Go, you can follow our guide for Ubuntu installation here.

      Note

      This guide is written for a non-root user. Depending on your configuration, some commands might require the help of sudo in order to get property executed. If you are not familiar with the sudo command, see the Users and Groups guide.

      About the context package

      The context package supports both the handling of multiple concurrent operations and the passing of (typically request-scoped) contextual data in key-value pairs.

      If you take a look at the source code of the context package, you will realize that its implementation is pretty simple. The context package defines the Context type, which is a Go interface with four methods, named Deadline(), Done(), Err(), and Value():

      context.go
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      type Context interface {
          Deadline() (deadline time.Time, ok bool)
          Done() <-chan struct{}
          Err() error
          Value(key interface{}) interface{}
      }
      • The developer will need to declare and modify a Context variable using functions such as context.WithCancel(), context.WithDeadline() and context.WithTimeout().

      • All three of these functions return a derived Context (the child) and a CancelFunc function. Calling the CancelFunc function removes the parent’s reference to the child and stops any associated timers. This means that the Go garbage collector is free to garbage collect the child goroutines that no longer have associated parent goroutines.

      • For garbage collection, the parent goroutine needs to keep a reference to each child goroutine. If a child goroutine ends without the parent knowing about it, then a memory leak occurs until the parent is canceled as well.

      A simple example

      This first code example is relatively simple and illustrates the use of the context.Context type with the help of simple.go.

      Explaining the Go code of the Example

      The code of simple.go is as follows:

      ./simple.go
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      package main
      
      import (
              "context"
              "fmt"
              "os"
              "strconv"
              "time"
      )
      
      // The f1 function creates and executes a goroutine
      // The time.Sleep() call simulates the time it would take a real goroutine
      // to do its job - in this case it is 4 seconds. If the c1 context calls
      // the Done() function in less than 4 seconds, the goroutine will not have
      // enough time to finish.
      func f1(t int) {
              c1 := context.Background()
              // WithCancel returns a copy of parent context with a new Done channel
              c1, cancel := context.WithCancel(c1)
              defer cancel()
      
              go func() {
                      time.Sleep(4 * time.Second)
                      cancel()
              }()
      
              select {
              case <-c1.Done():
                      fmt.Println("f1() Done:", c1.Err())
                      return
              case r := <-time.After(time.Duration(t) * time.Second):
                      fmt.Println("f1():", r)
              }
              return
      }
      
      func f2(t int) {
              c2 := context.Background()
              c2, cancel := context.WithTimeout(c2, time.Duration(t)*time.Second)
              defer cancel()
      
              go func() {
                      time.Sleep(4 * time.Second)
                      cancel()
              }()
      
              select {
              case <-c2.Done():
                      fmt.Println("f2() Done:", c2.Err())
                      return
              case r := <-time.After(time.Duration(t) * time.Second):
                      fmt.Println("f2():", r)
              }
              return
      }
      
      func f3(t int) {
              c3 := context.Background()
              deadline := time.Now().Add(time.Duration(2*t) * time.Second)
              c3, cancel := context.WithDeadline(c3, deadline)
              defer cancel()
      
              go func() {
                      time.Sleep(4 * time.Second)
                      cancel()
              }()
      
              select {
              case <-c3.Done():
                      fmt.Println("f3() Done:", c3.Err())
                      return
              case r := <-time.After(time.Duration(t) * time.Second):
                      fmt.Println("f3():", r)
              }
              return
      }
      
      func main() {
              if len(os.Args) != 2 {
                      fmt.Println("Need a delay!")
                      return
              }
      
              delay, err := strconv.Atoi(os.Args[1])
              if err != nil {
                      fmt.Println(err)
                      return
              }
              fmt.Println("Delay:", delay)
      
              f1(delay)
              f2(delay)
              f3(delay)
      }
      • The program contains four functions including the main() function. Functions f1(), f2(), and f3() each require just one parameter, which is a time delay, because everything else they need is defined inside their functions.

      • In this example we call the context.Background() function to initialize an empty Context. The other function that can create an empty Context is context.TODO() which will be presented later in this guide.

      • Notice that the cancel variable, a function, in f1() is one of the return values of context.CancelFunc(). The context.WithCancel() function uses an existing Context and creates a child with cancellation. The context.WithCancel() function also returns a Done channel that can be closed, either when the cancel() function is called, as shown in the preceding code, or when the Done channel of the parent context is closed.

        Note

        One of the return values of Context.Done() is a Go channel, which means that you will have to use a select statement to work with. Although select looks like switch, select allows a goroutine to wait on multiple communications operations.

      • The cancel variable in f2() comes from context.WithTimeout(). context.WithTimeout() requires two parameters: a Context parameter and a time.Duration parameter. When the timeout period expires, the cancel() function is called automatically.

      • The cancel variable in f3() comes from context.WithDeadline(). context.WithDeadline() requires two parameters: a Context variable and a time in the future that signifies the deadline of the operation. When the deadline passes, the cancel() function is called automatically.

        Note

        Notice that contexts should not be stored in structures – they should be passed as separate parameters to functions. It is considered a good practice to pass them as the first parameter of a function.

      Using simple.go

      Execute simple.go with a delay period of 3 seconds:

      go run simple.go 3
      

      It will generate the following kind of output:

        
      go run simple.go 3
      Delay: 3
      f1(): 2019-05-31 19:29:38.664568 +0300 EEST m=+3.004314767
      f2(): 2019-05-31 19:29:41.664942 +0300 EEST m=+6.004810929
      f3(): 2019-05-31 19:29:44.668795 +0300 EEST m=+9.008786881
      
      

      The long lines of the output are the return values from the time.After() function. They denote normal operation of the program. The point here is that the operation of the program is canceled when there are delays in its execution.

      If you use a bigger delay (10 seconds), which is executed as a call to time.Sleep():

      go run simple.go 10
      

      You will get the following kind of output:

        
      Delay: 10
      f1() Done: context canceled
      f2() Done: context canceled
      f3() Done: context canceled
      
      

      The calls to time.Sleep() simulate a program that is slow or an operation that takes too much time to finish. Production code does not usually have such time.Sleep() function calls.

      Using Context for HTTP

      In this section of the guide you will learn how to timeout HTTP connections on the client side.

      Note

      This example makes a request to a local web server. A suitable, simple web server is available via Python and can be started with the following commands:

      Python 3.X

      python3 -m http.server
      

      Python 2.X

      python -m SimpleHTTPServer
      

      The presented utility, which is called http.go, requires two command line arguments, which are the URL to connect to and the allowed delay value in seconds.

      Explaining the Go Code of the Example

      The Go code of the http.go utility is the following:

      ./http.go
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      package main
      
      import (
              "context"
              "fmt"
              "io/ioutil"
              "net/http"
              "os"
              "strconv"
              "sync"
              "time"
      )
      
      var (
              myUrl string
              delay int = 5
              w     sync.WaitGroup
      )
      
      type myData struct {
              r   *http.Response
              err error
      }
      
      // In packages that use contexts, convention is to pass them as
      // the first argument to a function.
      func connect(c context.Context) error {
              defer w.Done()
              data := make(chan myData, 1)
              tr := &http.Transport{}
              httpClient := &http.Client{Transport: tr}
              req, _ := http.NewRequest("GET", myUrl, nil)
      
              go func() {
                      response, err := httpClient.Do(req)
                      if err != nil {
                              fmt.Println(err)
                              data <- myData{nil, err}
                              return
                      } else {
                              pack := myData{response, err}
                              data <- pack
                      }
              }()
      
              select {
              case <-c.Done():
                      tr.CancelRequest(req)
                      <-data
                      fmt.Println("The request was canceled!")
                      return c.Err()
              case ok := <-data:
                      err := ok.err
                      resp := ok.r
                      if err != nil {
                              fmt.Println("Error select:", err)
                              return err
                      }
                      defer resp.Body.Close()
      
                      realHTTPData, err := ioutil.ReadAll(resp.Body)
                      if err != nil {
                              fmt.Println("Error select:", err)
                              return err
                      }
                      // Although fmt.Printf() is used here, server processes
                      // use the log.Printf() function instead.
                      fmt.Printf("Server Response: %sn", realHTTPData)
              }
              return nil
      }
      
      func main() {
              if len(os.Args) == 1 {
                      fmt.Println("Need a URL and a delay!")
                      return
              }
      
              myUrl = os.Args[1]
              if len(os.Args) == 3 {
                      t, err := strconv.Atoi(os.Args[2])
                      if err != nil {
                              fmt.Println(err)
                              return
                      }
                      delay = t
              }
      
              fmt.Println("Delay:", delay)
              c := context.Background()
              c, cancel := context.WithTimeout(c, time.Duration(delay)*time.Second)
              defer cancel()
      
              fmt.Printf("Connecting to %s n", myUrl)
              w.Add(1)
              go connect(c)
              w.Wait()
              fmt.Println("Exiting...")
      }
      • The timeout period is defined by the context.WithTimeout() method in main().

      • The connect() function that is executed as a goroutine will either terminate normally or when the cancel() function is executed.

        Note

        It is considered a good practice to use context.Background() in the main() function, the init() function of a package or at tests.

      • The connect() function is used for connecting to the desired URL. The connect() function also starts a goroutine before the select block takes control in order to either wait for web data as returned by the goroutine or for a timeout with the help of the Context variable.

      Using http.go

      If the desired delay is too small, then http.go will timeout. One such example is when you declare that you want a delay of 0 seconds, as in the following example:

      go run http.go https://www.linode.com/ 0
      

      The output is as follows:

        
      Delay: 0
      Connecting to https://www.linode.com/
      The request was canceled!
      Exiting...
      
      

      If the timeout period is sufficient, say 10 seconds.

      go run http.go http://localhost:8000 10
      

      Then the output from http.go will be similar to the following:

      Delay: 1
      Connecting to http://localhost:8000
      Server Response: Serving: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd">
      <html>
      <head>
      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
      <title>Directory listing for /</title>
      </head>
      <body>
      <h1>Directory listing for /</h1>
      <hr>
      <ul>
      <li><a href="http.go">http.go</a></li>
      <li><a href="more.go">more.go</a></li>
      <li><a href="simple.go">simple.go</a></li>
      </ul>
      <hr>
      </body>
      </html>
      

      Notice that http://localhost:8000 uses a custom made HTTP server that returns a small amount of data. However, nothing prohibits you from trying commands such as:

      go run http.go https://www.linode.com/ 10
      

      Using Contexts as key-value stores

      In this section of the guide you will pass values in a Context and use it as a key-value store. This is a case where we do not pass values into contexts in order to provide further information about why they where canceled.

      The more.go program illustrates the use of the context.TODO() function as well as the use of the context.WithValue() function.

      Explaining the Go Code

      The Go code of more.go is the following:

      ./more.go
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      package main
      
      import (
              "context"
              "fmt"
      )
      
      type aKey string
      
      func searchKey(ctx context.Context, k aKey) {
              v := ctx.Value(k)
              if v != nil {
                      fmt.Println("found value:", v)
                      return
              } else {
                      fmt.Println("key not found:", k)
              }
      }
      
      func main() {
              myKey := aKey("mySecretValue")
              ctx := context.WithValue(context.Background(), myKey, "mySecretValue")
              searchKey(ctx, myKey)
      
              searchKey(ctx, aKey("notThere"))
              emptyCtx := context.TODO()
              searchKey(emptyCtx, aKey("notThere"))
      }
      • This time we create a context using context.TODO() instead of context.Background(). Although both functions return a non-nil, empty Context, their purposes differ. You should never pass a nil context –– use the context.TODO() function to create a suitable context. Use the context.TODO() function when you are not sure about the Context that you want to use.

      • The context.TODO() function signifies that we intend to use an operation context, without being sure about it yet. The good thing is that TODO() is recognized by static analysis tools, which allows them to determine whether a context.Context variable is propagated correctly in a program or not.

      • The context.WithValue() function that is used in main() offers a way to associate a value with a Context`.

      • The searchKey() function retrieves a value from a Context variable and checks whether that value exists or not.

      Using more.go

      Execute more.go with the following command:

      go run more.go
      

      It will generate the following output:

        
      found value: mySecretValue
      key not found: notThere
      key not found: notThere
      
      

      Propagation over HTTP

      In order to share a common context among multiple processes, you will need to propagate that context on your own.

      The logic of this technique is based on the Go code of more.go. First use the context.WithValue() function to add your data into a context, serialize and send over HTTP, decode the data, get the context, and finally use context.Value() to check whether the desired key and desired values are in place or not.

      Note

      The http.Request type has the Context() method that returns the context of the request and the WithContext() method that according to the Go documentation returns a shallow copy of r with its context changed to ctx. You can learn more about both methods at https://golang.org/pkg/net/http/.

      More Information

      You may wish to consult the following resources for additional information on this topic. While these are provided in the hope that they will be useful, please note that we cannot vouch for the accuracy or timeliness of externally hosted materials.

      Find answers, ask questions, and help others.

      This guide is published under a CC BY-ND 4.0 license.



      Source link

      An Introduction to the Strings Package in Go


      Introduction

      Go’s string package has several functions available to work with the string data type. These functions let us easily modify and manipulate strings. We can think of functions as being actions that we perform on elements of our code. Built-in functions are those that are defined in the Go programming language and are readily available for us to use.

      In this tutorial, we’ll review several different functions that we can use to work with strings in Go.

      Making Strings Uppercase and Lowercase

      The functions strings.ToUpper and strings.ToLower will return a string with all the letters of an original string converted to uppercase or lowercase letters. Because strings are immutable data types, the returned string will be a new string. Any characters in the string that are not letters will not be changed.

      Let’s convert the string "Sammy Shark" to be all uppercase:

      ss := "Sammy Shark"
      fmt.Println(strings.ToUpper(ss))
      

      Output

      SAMMY SHARK

      Now, let’s convert the string to be all lowercase:

      fmt.Println(strings.ToLower(ss))
      

      Output

      sammy shark

      Since you are using the strings package, you first need to import it into your program. To convert the string to uppercase and lowercase the entire program would be as follows:

      package main
      
      import (
          "fmt"
          "strings"
      )
      
      func main() {
          ss := "Sammy Shark"
          fmt.Println(strings.ToUpper(ss))
          fmt.Println(strings.ToLower(ss))
      }
      

      The strings.ToUpper and strings.ToLower functions make it easier to evaluate and compare strings by making case consistent throughout. For example, if a user writes their name all lowercase, we can still determine whether their name is in our database by checking it against an all uppercase version.

      String Search Functions

      The strings package has a number of functions that help determine if a string contains a specific sequence of characters.

      FunctionUse
      strings.HasPrefixSearches the string from the beginning
      strings.HasSuffixSearches the string from the end
      strings.ContainsSearches anywhere in the string
      strings.CountCounts how many times the string appears

      The strings.HasPrefix and strings.HasSuffix allow you to check to see if a string starts or ends with a specific set of characters.

      Let’s check to see if the string Sammy Shark starts with Sammy and ends with Shark.

      ss := "Sammy Shark"
      fmt.Println(strings.HasPrefix(ss, "Sammy"))
      fmt.Println(strings.HasSuffix(ss, "Shark"))
      

      Output

      true true

      Let’s check to see if the string Sammy Shark contains the sequence Sh:

      fmt.Println(strings.Contains(ss, "Sh"))
      

      Output

      true

      Finally, let’s see how many times the letter S appears in the phrase Sammy Shark:

      fmt.Println(strings.Count(ss, "S"))
      

      Output

      2

      Note: All strings in Go are case sensitive. This means that Sammy is not the same as sammy.

      Using a lowercase s to get a count from Sammy Shark is not the same as using uppercase S:

      fmt.Println(strings.Count(ss, "s"))
      

      Output

      0

      Because S is different than s, the count returned will be 0.

      String functions are useful when you want to compare or search strings in your program.

      Determining String Length

      The built-in function len() returns the number of characters in a string. This function is useful for when you need to enforce minimum or maximum password lengths, or to truncate larger strings to be within certain limits for use as abbreviations.

      To demonstrate this function, we’ll find the length of a sentence-long string:

      openSource := "Sammy contributes to open source."
      fmt.Println(len(openSource))
      

      Output

      33

      We set the variable openSource equal to the string "Sammy contributes to open source." and then passed that variable to the len() function with len(openSource). Finally we passed the function into the fmt.Println() function so that we could see the program’s output on the screen..

      Keep in mind that the len() function will count any character bound by double quotation marks—including letters, numbers, whitespace characters, and symbols.

      Functions for String Manipulation

      The strings.Join, strings.Split, and strings.ReplaceAll functions are a few additional ways to manipulate strings in Go.

      The strings.Join function is useful for combining a slice of strings into a new single string.

      Let’s create a comma-separated string from a slice of strings:

      fmt.Println(strings.Join([]string{"sharks", "crustaceans", "plankton"}, ","))
      

      Output

      sharks,crustaceans,plankton

      If we want to add a comma and a space between string values in our new string, we can simply rewrite our expression with a whitespace after the comma: strings.Join([]string{"sharks", "crustaceans", "plankton"}, ", ").

      Just as we can join strings together, we can also split strings up. To do this, we use the strings.Split function and split on the spaces:

      balloon := "Sammy has a balloon."
      s := strings.Split(balloon, " ")
      fmt.Println(s)
      

      Output

      [Sammy has a balloon]

      The output is a slice of strings. Since strings.Println was used, it is hard to tell what the output is by looking at it. To see that it is indeed a slice of strings, use the fmt.Printf function with the %q verb to quote the strings:

      fmt.Printf("%q", s)
      

      Output

      ["Sammy" "has" "a" "balloon."]

      Another useful function in addition to strings.Split is strings.Fields. The difference is that strings.Fields will ignore all whitespace, and will only split out the actual fields in a string:

      data := "  username password     email  date"
      fields := strings.Fields(data)
      fmt.Printf("%q", fields)
      

      Output

      ["username" "password" "email" "date"]

      The strings.ReplaceAll function can take an original string and return an updated string with some replacement.

      Let’s say that the balloon that Sammy had is lost. Since Sammy no longer has this balloon, we will change the substring "has" from the original string balloon to "had" in a new string:

      fmt.Println(strings.ReplaceAll(balloon, "has", "had"))
      

      Within the parentheses, first is balloon the variable that stores the original string; the second substring "has" is what we want to be replaced, and the third substring "had" is what we are replacing that second substring with. Our output will look like this:

      Output

      Sammy had a balloon.

      Using the string function strings.Join, strings.Split, and strings.ReplaceAll will provide you with greater control to manipulate strings in Go.

      Conclusion

      This tutorial went through some of the common string package functions for the string data type that you can use to work with and manipulate strings in your Go programs.

      You can learn more about other data types in Understanding Data Types and read more about strings in An Introduction to Working with Strings.



      Source link

      Webinar Series: Kubernetes Package Management with Helm and CI/CD with Jenkins X


      Webinar Series

      This article supplements a webinar series on doing CI/CD with Kubernetes. The series discusses how to take a cloud native approach to building, testing, and deploying applications, covering release management, cloud native tools, service meshes, and CI/CD tools that can be used with Kubernetes. It is designed to help developers and businesses that are interested in integrating CI/CD best practices with Kubernetes into their workflows.

      This tutorial includes the concepts and commands from the second session of the series, Kubernetes Package Management with Helm and CI/CD with Jenkins X.

      Warning: The procedures in this tutorial are meant for demonstration purposes only. As a result, they don’t follow the best practices and security measures necessary for a production-ready deployment.

      Introduction

      In order to reduce error and organize complexity when deploying an application, CI/CD systems must include robust tooling for package management/deployment and pipelines with automated testing. But in modern production environments, the increased complexity of cloud-based infrastructure can present problems for putting together a reliable CI/CD environment. Two Kubernetes-specific tools developed to solve this problem are the Helm package manager and the Jenkins X pipeline automation tool.

      Helm is a package manager specifically designed for Kubernetes, maintained by the Cloud Native Computing Foundation (CNCF) in collaboration with Microsoft, Google, Bitnami, and the Helm contributor community. At a high level, it accomplishes the same goals as Linux system package managers like APT or YUM: managing the installation of applications and dependencies behind the scenes and hiding the complexity from the user. But with Kubernetes, the need for this kind of management is even more pronounced: Installing applications requires the complex and tedious orchestration of YAML files, and upgrading or rolling back releases can be anywhere from difficult to impossible. In order to solve this problem, Helm runs on top of Kubernetes and packages applications into pre-configured resources called charts, which the user can manage with simple commands, making the process of sharing and managing applications more user-friendly.

      Jenkins X is a CI/CD tool used to automate production pipelines and environments for Kubernetes. Using Docker images, Helm charts, and the Jenkins pipeline engine, Jenkins X can automatically manage releases and versions and promote applications between environments on GitHub.

      In this second article of the CI/CD with Kubernetes series, you will preview these two tools by:

      • Managing, creating, and deploying Kubernetes packages with Helm.

      • Building a CI/CD pipeline with Jenkins X.

      Though a variety of Kubernetes platforms can use Helm and Jenkins X, in this tutorial you will run a simulated Kubernetes cluster, set up in your local environment. To do this, you will use Minikube, a program that allows you to try out Kubernetes tools on your own machine without having to set up a true Kubernetes cluster.

      By the end of this tutorial, you will have a basic understanding of how these Kubernetes-native tools can help you implement a CI/CD system for your cloud application.

      Prerequisites

      To follow this tutorial, you will need:

      • An Ubuntu 16.04 server with 16 GB of RAM or above. Since this tutorial is meant for demonstration purposes only, commands are run from the root account. Note that the unrestrained privileges of this account do not adhere to production-ready best practices and could affect your system. For this reason, it is suggested to follow these steps in a test environment such as a virtual machine or a DigitalOcean Droplet.

      • A GitHub account and GitHub API token. Be sure to record this API token so that you can enter it during the Jenkins X portion of this tutorial.

      • Familiarity with Kubernetes concepts. Please refer to the article An Introduction to Kubernetes for more details.

      Step 1 — Creating a Local Kubernetes Cluster with Minikube

      Before setting up Minikube, you will have to install its dependencies, including the Kubernetes command line tool kubectl, the bidirectional data transfer relay socat, and the container program Docker.

      First, make sure that your system’s package manager can access packages over HTTPS with apt-transport-https:

      • apt-get update
      • apt-get install apt-transport-https

      Next, in order to ensure the kubectl download is valid, add the GPG key for the official Google repository to your system:

      • curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -

      Once you have added the GPG key, create the file /etc/apt/sources.list.d/kubernetes.list by opening it in your text editor:

      • nano /etc/apt/sources.list.d/kubernetes.list

      Once this file is open, add the following line:

      /etc/apt/sources.list.d/kubernetes.list

      deb http://apt.kubernetes.io/ kubernetes-xenial main
      

      This will show your system the source for downloading kubectl. Once you have added the line, save and exit the file. With the nano text editor, you can do this by pressing CTRL+X, typing y, and pressing ENTER.

      Finally, update the source list for APT and install kubectl, socat, and docker.io:

      • apt-get update
      • apt-get install -y kubectl socat docker.io

      Note: For Minikube to simulate a Kubernetes cluster, you must download the docker.io package rather than the newer docker-ce release. For production-ready environments, docker-ce would be the more appropriate choice, since it is better maintained in the official Docker repository.

      Now that you have installed kubectl, you can proceed with installing Minikube. First, use curl to download the program’s binary:

      • curl -Lo minikube https://storage.googleapis.com/minikube/releases/v0.28.0/minikube-linux-amd64

      Next, change the access permissions of the file you just downloaded so that your system can execute it:

      Finally, copy the minikube file to the executable path at /usr/local/bin/ and remove the original file from your home directory:

      • cp minikube /usr/local/bin/
      • rm minikube

      With Minikube installed on your machine, you can now start the program. To create a Minikube Kubernetes cluster, use the following command:

      • minikube start --vm-driver none

      The flag --vm-driver none instructs Minikube to run Kubernetes on the local host using containers rather than a virtual machine. Running Minikube this way means that you do not need to download a VM driver, but also means that the Kubernetes API server will run insecurely as root.

      Warning: Because the API server with root privileges will have unlimited access to the local host, it is not recommended to run Minikube using the none driver on personal workstations.

      Now that you have started Minikube, check to make sure that your cluster is running with the following command:

      You will receive the following output, with your IP address in place of your_IP_address:

      minikube: Running
      cluster: Running
      kubectl: Correctly Configured: pointing to minikube-vm at your_IP_address
      

      Now that you have set up your simulated Kubernetes cluster using Minikube, you can gain experience with Kubernetes package management by installing and configuring the Helm package manager on top of your cluster.

      Step 2 — Setting Up the Helm Package Manager on your Cluster

      In order to coordinate the installation of applications on your Kubernetes cluster, you will now install the Helm package manager. Helm consists of a helm client that runs outside the cluster and a tiller server that manages application releases from within the cluster. You will have to install and configure both to successfully run Helm on your cluster.

      To install the Helm binaries, first use curl to download the following installation script from the official Helm GitHub repository into a new file named get_helm.sh:

      • curl https://raw.githubusercontent.com/kubernetes/helm/master/scripts/get > get_helm.sh

      Since this script requires root access, change the permission of get_helm.sh so that the owner of the file (in this case, root) can read, write, and execute it:

      Now, execute the script:

      When the script finishes, you will have helm installed to /usr/local/bin/helm and tiller installed to /usr/local/bin/tiller.

      Though tiller is now installed, it does not yet have the correct roles and permissions to access the necessary resources in your Kubernetes cluster. To assign these roles and permissions to tiller, you will have to create a service account named tiller. In Kubernetes, a service account represents an identity for processes that run in a pod. After a process is authenticated through a service account, it can then contact the API server and access cluster resources. If a pod is not assigned a specific service account, it gets the default service account. You will also have to create a Role-Based access control (RBAC) rule that authorizes the tiller service account.

      In Kubernetes RBAC API, a role contains rules that determine a set of permissions. A role can be defined with a scope of namespace or cluster, and can only grant access to resources within a single namespace. ClusterRole can create the same permissions on the level of a cluster, granting access to cluster-scoped resources like nodes and namespaced resources like pods. To assign the tiller service account the right role, create a YAML file called rbac_helm.yaml and open it in your text editor:

      Add the following lines to the file to configure the tiller service account:

      rbac_helm.yaml

      apiVersion: v1
      kind: ServiceAccount
      metadata:
        name: tiller
        namespace: kube-system
      ---
      apiVersion: rbac.authorization.k8s.io/v1beta1
      kind: ClusterRoleBinding
      metadata:
        name: tiller
      roleRef:
        apiGroup: rbac.authorization.k8s.io
        kind: ClusterRole
        name: cluster-admin
      subjects:
        - kind: ServiceAccount
          name: tiller
          namespace: kube-system
      
        - kind: User
          name: "admin"
          apiGroup: rbac.authorization.k8s.io
      
        - kind: User
          name: "kubelet"
          apiGroup: rbac.authorization.k8s.io
      
        - kind: Group
          name: system:serviceaccounts
          apiGroup: rbac.authorization.k8s.io
      

      In the preceding file, ServiceAccount allows the tiller processes to access the apiserver as an authenticated service account. ClusterRole grants certain permissions to a role, and ClusterRoleBinding assigns that role to a list of subjects, including the tiller service account, the admin and kubelet users, and the system:serviceaccounts group.

      Next, deploy the configuration in rbac_helm.yaml with the following command:

      • kubectl apply -f rbac_helm.yaml

      With the tiller configuration deployed, you can now initialize Helm with the --service-acount flag to use the service account you just set up:

      • helm init --service-account tiller

      You will receive the following output, representing a successful initialization:

      Output

      Creating /root/.helm Creating /root/.helm/repository Creating /root/.helm/repository/cache Creating /root/.helm/repository/local Creating /root/.helm/plugins Creating /root/.helm/starters Creating /root/.helm/cache/archive Creating /root/.helm/repository/repositories.yaml Adding stable repo with URL: https://kubernetes-charts.storage.googleapis.com Adding local repo with URL: http://127.0.0.1:8879/charts $HELM_HOME has been configured at /root/.helm. Tiller (the Helm server-side component) has been installed into your Kubernetes Cluster. Please note: by default, Tiller is deployed with an insecure 'allow unauthenticated users' policy. To prevent this, run `helm init` with the --tiller-tls-verify flag. For more information on securing your installation see: https://docs.helm.sh/using_helm/#securing-your-helm-installation Happy Helming!

      This creates a tiller pod in the kube-system namespace. It also creates the .helm default repository in your $HOME directory and configures the default Helm stable chart repository at https://kubernetes-charts.storage.googleapis.com and the local Helm repository at http://127.0.0.1:8879/charts.

      To make sure that the tiller pod is running in the kube-system namespace, enter the following command:

      • kubectl --namespace kube-system get pods

      In your list of pods, tiller-deploy will appear, as is shown in the following output:

      Output

      NAME READY STATUS RESTARTS AGE etcd-minikube 1/1 Running 0 2h kube-addon-manager-minikube 1/1 Running 0 2h kube-apiserver-minikube 1/1 Running 0 2h kube-controller-manager-minikube 1/1 Running 0 2h kube-dns-86f4d74b45-rjql8 3/3 Running 0 2h kube-proxy-dv268 1/1 Running 0 2h kube-scheduler-minikube 1/1 Running 0 2h kubernetes-dashboard-5498ccf677-wktkl 1/1 Running 0 2h storage-provisioner 1/1 Running 0 2h tiller-deploy-689d79895f-bggbk 1/1 Running 0 5m

      If the tiller pod's status is Running, it can now manage Kubernetes applications from inside your cluster on behalf of Helm.

      To make sure that the entire Helm application is working, search the Helm package repositiories for an application like MongoDB:

      In the output, you will see a list of possible applications that fit your search term:

      Output

      NAME CHART VERSION APP VERSION DESCRIPTION stable/mongodb 5.4.0 4.0.6 NoSQL document-oriented database that stores JSON-like do... stable/mongodb-replicaset 3.9.0 3.6 NoSQL document-oriented database that stores JSON-like do... stable/prometheus-mongodb-exporter 1.0.0 v0.6.1 A Prometheus exporter for MongoDB metrics stable/unifi 0.3.1 5.9.29 Ubiquiti Network's Unifi Controller

      Now that you have installed Helm on your Kubernetes cluster, you can learn more about the package manager by creating a sample Helm chart and deploying an application from it.

      Step 3 — Creating a Chart and Deploying an Application with Helm

      In the Helm package manager, individual packages are called charts. Within a chart, a set of files defines an application, which can vary in complexity from a pod to a structured, full-stack app. You can download charts from the Helm repositories, or you can use the helm create command to create your own.

      To test out the capabilities of Helm, create a new Helm chart named demo with the following command:

      In your home directory, you will find a new directory called demo, within which you can create and edit your own chart templates.

      Move into the demo directory and use ls to list its contents:

      You will find the following files and directories in demo:

      demo

      charts  Chart.yaml  templates  values.yaml
      

      Using your text editor, open up the Chart.yaml file:

      Inside, you will find the following contents:

      demo/Chart.yaml

      apiVersion: v1
      appVersion: "1.0"
      description: A Helm chart for Kubernetes
      name: demo
      version: 0.1.0
      

      In this Chart.yaml file, you will find fields like apiVersion, which must be always v1, a description that gives additional information about what demo is, the name of the chart, and the version number, which Helm uses as a release marker. When you are done examining the file, close out of your text editor.

      Next, open up the values.yaml file:

      In this file, you will find the following contents:

      demo/values.yaml

      # Default values for demo.
      # This is a YAML-formatted file.
      # Declare variables to be passed into your templates.
      
      replicaCount: 1
      
      image:
        repository: nginx
        tag: stable
        pullPolicy: IfNotPresent
      
      nameOverride: ""
      fullnameOverride: ""
      
      service:
        type: ClusterIP
        port: 80
      
      ingress:
        enabled: false
        annotations: {}
          # kubernetes.io/ingress.class: nginx
          # kubernetes.io/tls-acme: "true"
        paths: []
        hosts:
          - chart-example.local
        tls: []
        #  - secretName: chart-example-tls
        #    hosts:
        #      - chart-example.local
      
      resources: {}
        # We usually recommend not to specify default resources and to leave this as a conscious
        # choice for the user. This also increases chances charts run on environments with little
        # resources, such as Minikube. If you do want to specify resources, uncomment the following
        # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
        # limits:
        #  cpu: 100m
        #  memory: 128Mi
        # requests:
        #  cpu: 100m
        #  memory: 128Mi
      
      nodeSelector: {}
      
      tolerations: []
      
      affinity: {}
      

      By changing the contents of values.yaml, chart developers can supply default values for the application defined in the chart, controlling replica count, image base, ingress access, secret management, and more. Chart users can supply their own values for these parameters with a custom YAML file using helm install. When a user provides custom values, these values will override the values in the chart’s values.yaml file.

      Close out the values.yaml file and list the contents of the templates directory with the following command:

      Here you will find templates for various files that can control different aspects of your chart:

      templates

      deployment.yaml  _helpers.tpl  ingress.yaml  NOTES.txt  service.yaml  tests
      

      Now that you have explored the demo chart, you can experiment with Helm chart installation by installing demo. Return to your home directory with the following command:

      Install the demo Helm chart under the name web with helm install:

      • helm install --name web ./demo

      You will get the following output:

      Output

      NAME: web LAST DEPLOYED: Wed Feb 20 20:59:48 2019 NAMESPACE: default STATUS: DEPLOYED RESOURCES: ==> v1/Service NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE web-demo ClusterIP 10.100.76.231 <none> 80/TCP 0s ==> v1/Deployment NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE web-demo 1 0 0 0 0s ==> v1/Pod(related) NAME READY STATUS RESTARTS AGE web-demo-5758d98fdd-x4mjs 0/1 ContainerCreating 0 0s NOTES: 1. Get the application URL by running these commands: export POD_NAME=$(kubectl get pods --namespace default -l "app.kubernetes.io/name=demo,app.kubernetes.io/instance=web" -o jsonpath="{.items[0].metadata.name}") echo "Visit http://127.0.0.1:8080 to use your application" kubectl port-forward $POD_NAME 8080:80

      In this output, you will find the STATUS of your application, plus a list of relevant resources in your cluster.

      Next, list the deployments created by the demo Helm chart with the following command:

      This will yield output that will list your active deployments:

      Output

      NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE web-demo 1 1 1 1 4m

      Listing your pods with the command kubectl get pods would show the pods that are running your web application, which would look like the following:

      Output

      NAME READY STATUS RESTARTS AGE web-demo-5758d98fdd-nbkqd 1/1 Running 0 4m

      To demonstrate how changes in the Helm chart can release different versions of your application, open up demo/values.yaml in your text editor and change replicaCount: to 3 and image:tag: from stable to latest. In the following code block, you will find what the YAML file should look like after you have finished modifying it, with the changes highlighted:

      demo/values.yaml

      # Default values for demo.
      # This is a YAML-formatted file.
      # Declare variables to be passed into your templates.
      
      replicaCount: 3
      
      image:
        repository: nginx
        tag: latest
        pullPolicy: IfNotPresent
      
      nameOverride: ""
      fullnameOverride: ""
      
      service:
        type: ClusterIP
        port: 80
      . . .
      

      Save and exit the file.

      Before you deploy this new version of your web application, list your Helm releases as they are now with the following command:

      You will receive the following output, with the one deployment you created earlier:

      Output

      NAME REVISION UPDATED STATUS CHART APP VERSION NAMESPACE web 1 Wed Feb 20 20:59:48 2019 DEPLOYED demo-0.1.0 1.0 default

      Notice that REVISION is listed as 1, indicating that this is the first revision of the web application.

      To deploy the web application with the latest changes made to demo/values.yaml, upgrade the application with the following command:

      Now, list the Helm releases again:

      You will receive the following output:

      Output

      NAME REVISION UPDATED STATUS CHART APP VERSION NAMESPACE web 2 Wed Feb 20 21:18:12 2019 DEPLOYED demo-0.1.0 1.0 default

      Notice that REVISION has changed to 2, indicating that this is the second revision.

      To find the history of the Helm releases for web, use the following:

      This will show both of the revisions of the web application:

      Output

      REVISION        UPDATED                         STATUS          CHART           DESCRIPTION
      1               Wed Feb 20 20:59:48 2019        SUPERSEDED      demo-0.1.0      Install complete
      2               Wed Feb 20 21:18:12 2019        DEPLOYED        demo-0.1.0      Upgrade complete
      

      To roll back your application to revision 1, enter the following command:

      This will yield the following output:

      Output

      Rollback was a success! Happy Helming!

      Now, bring up the Helm release history:

      You will receive the following list:

      Output

      REVISION UPDATED STATUS CHART DESCRIPTION 1 Wed Feb 20 20:59:48 2019 SUPERSEDED demo-0.1.0 Install complete 2 Wed Feb 20 21:18:12 2019 SUPERSEDED demo-0.1.0 Upgrade complete 3 Wed Feb 20 21:28:48 2019 DEPLOYED demo-0.1.0 Rollback to 1

      By rolling back the web application, you have created a third revision that has the same settings as revision 1. Remember, you can always tell which revision is active by finding the DEPLOYED item under STATUS.

      To prepare for the next section, clean up your testing area by deleting your web release with the helm delete command:

      Examine the Helm release history again:

      You will receive the following output:

      Output

      REVISION UPDATED STATUS CHART DESCRIPTION 1 Wed Feb 20 20:59:48 2019 SUPERSEDED demo-0.1.0 Install complete 2 Wed Feb 20 21:18:12 2019 SUPERSEDED demo-0.1.0 Upgrade complete 3 Wed Feb 20 21:28:48 2019 DELETED demo-0.1.0 Deletion complete

      The STATUS for REVISION 3 has changed to DELETED, indicating that your deployed instance of web has been deleted. However, although this does delete the release, it does not delete it from store. In order to delete the release completely, run the helm delete command with the --purge flag.

      In this step, you have managed application releases on Kubernetes with the Helm. If you would like to study Helm further, check out our An Introduction to Helm, the Package Manager for Kubernetes tutorial, or review the official Helm documentation.

      Next, you will set up and test the pipeline automation tool Jenkins X by using the jx CLI to create a CI/CD-ready Kubernetes cluster.

      Step 4 — Setting Up the Jenkins X Environment

      With Jenkins X, you can create your Kubernetes cluster from the ground up with pipeline automation and CI/CD solutions built in. By installing the jx CLI tool, you will be able to efficiently manage application releases, Docker images, and Helm charts, in addition to automatically promoting your applications across environments in GitHub.

      Since you will be using jx to create your cluster, you must first delete the Minikube cluster that you already have. To do this, use the following command:

      This will delete the local simulated Kubernete cluster, but will not delete the default directories created when you first installed Minikube. To clean these off your machine, use the following commands:

      • rm -rf ~/.kube
      • rm -rf ~/.minikube
      • rm -rf /etc/kubernetes/*
      • rm -rf /var/lib/minikube/*

      Once you have completely cleared Minikube from your machine, you can move on to installing the Jenkins X binary.

      First, download the compressed jx file from the official Jenkins X GitHub repository with the curl command and uncompress it with the tar command:

      • curl -L https://github.com/jenkins-x/jx/releases/download/v1.3.781/jx-linux-amd64.tar.gz | tar xzv

      Next, move the downloaded jx file to the executable path at /usr/local/bin:

      Jenkins X comes with a Docker Registry that runs inside your Kubernetes cluster. Since this is an internal element, security measures such as self-signed certificates can cause trouble for the program. To fix this, set Docker to use insecure registries for the local IP range. To do this, create the file /etc/docker/daemon.json and open it in your text editor:

      • nano /etc/docker/daemon.json

      Add the following contents to the file:

      /etc/docker/daemon.json

      {
        "insecure-registries" : ["0.0.0.0/0"]
      }
      

      Save and exit the file. For these changes to take effect, restart the Docker service with the following command:

      To verify that you have configured Docker with insecure registries, use the following command:

      At the end of the output, you should see the following highlighted line:

      Output

      Containers: 0 Running: 0 Paused: 0 Stopped: 0 Images: 15 Server Version: 18.06.1-ce Storage Driver: overlay2 Backing Filesystem: extfs Supports d_type: true Native Overlay Diff: true . . . Registry: https://index.docker.io/v1/ Labels: Experimental: false Insecure Registries: 0.0.0.0/0 127.0.0.0/8 Live Restore Enabled: false

      Now that you have downloaded Jenkins X and configured the Docker registry, use the jx CLI tool to create a Minikube Kubernetes cluster with CI/CD capabilities:

      • jx create cluster minikube --cpu=5 --default-admin-password=admin --vm-driver=none --memory=13314

      Here you are creating a Kubernetes cluster using Minikube, with the flag --cpu=5 to set 5 CPUs and --memory=13314 to give your cluster 13314 MBs of memory. Since Jenkins X is a robust but large program, these specifications will ensure that Jenkins X works without problems in this demonstration. Also, you are using --default-admin-password=admin to set the Jenkins X password as admin and --vm-driver=none to set up the cluster locally, as you did in Step 1.

      As Jenkins X spins up your cluster, you will receive various prompts at different times throughout the process that set the parameters for your cluster and determine how it will communicate with GitHub to manage your production environments.

      First, you will receive the following prompt:

      Output

      ? disk-size (MB) 150GB

      Press ENTER to continue. Next, you will be prompted for the name you wish to use with git, the email address you wish to use with git, and your GitHub username. Enter each of these when prompted, then press ENTER.

      Next, Jenkins X will prompt you to enter your GitHub API token:

      Output

      To be able to create a repository on GitHub we need an API Token Please click this URL https://github.com/settings/tokens/new?scopes=repo,read:user,read:org,user:email,write:repo_hook,delete_repo Then COPY the token and enter in into the form below: ? API Token:

      Enter your token here, or create a new token with the appropriate permissions using the highlighted URL in the preceding code block.

      Next, Jenkins X will ask:

      Output

      ? Do you wish to use GitHub as the pipelines Git server: (Y/n) ? Do you wish to use your_GitHub_username as the pipelines Git user for GitHub server: (Y/n)

      Enter Y for both questions.

      After this, Jenkins X will prompt you to answer the following:

      Output

      ? Select Jenkins installation type: [Use arrows to move, type to filter] >Static Master Jenkins Serverless Jenkins ? Pick workload build pack: [Use arrows to move, type to filter] > Kubernetes Workloads: Automated CI+CD with GitOps Promotion Library Workloads: CI+Release but no CD

      For the prior, select Static Master Jenkins, and select Kubernetes Workloads: Automated CI+CD with GitOps Promotion for the latter. When prompted to select an organization for your environment repository, select your GitHub username.

      Finally, you will receive the following output, which verifies successful installation and provides your Jenkins X admin password.

      Output

      Creating GitHub webhook for your_GitHub_username/environment-horsehelix-production for url http://jenkins.jx.your_IP_address.nip.io/github-webhook/ Jenkins X installation completed successfully ******************************************************** NOTE: Your admin password is: admin ******************************************************** Your Kubernetes context is now set to the namespace: jx To switch back to your original namespace use: jx namespace default For help on switching contexts see: https://jenkins-x.io/developing/kube-context/ To import existing projects into Jenkins: jx import To create a new Spring Boot microservice: jx create spring -d web -d actuator To create a new microservice from a quickstart: jx create quickstart

      Next, use the jx get command to receive a list of URLs that show information about your application:

      This command will yield a list similar to the following:

      Name                      URL
      jenkins                   http://jenkins.jx.your_IP_address.nip.io
      jenkins-x-chartmuseum     http://chartmuseum.jx.your_IP_address.nip.io
      jenkins-x-docker-registry http://docker-registry.jx.your_IP_address.nip.io
      jenkins-x-monocular-api   http://monocular.jx.your_IP_address.nip.io
      jenkins-x-monocular-ui    http://monocular.jx.your_IP_address.nip.io
      nexus                     http://nexus.jx.your_IP_address.nip.io
      

      You can use the URLs to view Jenkins X data about your CI/CD environment via a UI by entering the address into your browser and entering your username and password. In this case, this will be "admin" for both.

      Next, in order to ensure that the service accounts in the namespaces jx, jx-staging, and jx-production have admin privileges, modify your RBAC policies with the following commands:

      • kubectl create clusterrolebinding jx-staging1 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx-staging:expose --namespace=jx-staging
      • kubectl create clusterrolebinding jx-staging2 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx-staging:default --namespace=jx-staging
      • kubectl create clusterrolebinding jx-production1 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx-production:expose --namespace=jx-productions
      • kubectl create clusterrolebinding jx-production2 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx-production:default --namespace=jx-productions
      • kubectl create clusterrolebinding jx-binding1 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx:expose --namespace=jx
      • kubectl create clusterrolebinding jx-binding2 --clusterrole=cluster-admin --user=admin --user=expose --group=system:serviceaccounts --serviceaccount=jx:default --namespace=jx

      Now that you have created your local Kubernetes cluster with Jenkins X functionality built in, you can move on to creating an application on the platform to test its CI/CD capabilities and experience a Jenkins X pipeline.

      Step 5 — Creating a Test Application in Your Jenkins X Environment

      With your Jenkins X environment set up in your Kubernetes cluster, you now have CI/CD infrastructure in place that can help you automate a testing pipeline. In this step, you will try this out by setting up a test application in a working Jenkins X pipeline.

      For demonstration purposes, this tutorial will use a sample RSVP application created by the CloudYuga team. You can find this application, along with other webinar materials, at the DO-Community GitHub repository.

      First, clone the sample application from the repository with the following command:

      • git clone https://github.com/do-community/rsvpapp.git

      Once you've cloned the repository, move into the rsvpapp directory and remove the git files:

      To initialize a git repository and a Jenkins X project for a new application, you can use jx create to start from scratch or a template, or jx import to import an existing application from a local project or git repository. For this tutorial, import the sample RSVP application by running the following command from within the application's home directory:

      Jenkins X will prompt you for your GitHub username, whether you'd like to initialize git, a commit message, your organization, and the name you would like for your repository. Answer yes to initialize git, then provide the rest of the prompts with your individual GitHub information and preferences. As Jenkins X imports the application, it will create Helm charts and a Jenkinsfile in your application's home directory. You can modify these charts and the Jenkinsfile as per your requirements.

      Since the sample RSVP application runs on port 5000 of its container, modify your charts/rsvpapp/values.yaml file to match this. Open the charts/rsvpapp/values.yaml in your text editor:

      • nano charts/rsvpapp/values.yaml

      In this values.yaml file, set service:internalPort: to 5000. Once you have made this change, your file should look like the following:

      charts/rsvpapp/values.yaml

      # Default values for python.
      # This is a YAML-formatted file.
      # Declare variables to be passed into your templates.
      replicaCount: 1
      image:
        repository: draft
        tag: dev
        pullPolicy: IfNotPresent
      service:
        name: rsvpapp
        type: ClusterIP
        externalPort: 80
        internalPort: 5000
        annotations:
          fabric8.io/expose: "true"
          fabric8.io/ingress.annotations: "kubernetes.io/ingress.class: nginx"
      resources:
        limits:
          cpu: 100m
          memory: 128Mi
        requests:
          cpu: 100m
          memory: 128Mi
      ingress:
        enabled: false
      

      Save and exit your file.

      Next, change the charts/preview/requirements.yaml to fit with your application. requirements.yaml is a YAML file in which developers can declare chart dependencies, along with the location of the chart and the desired version. Since our sample application uses MongoDB for database purposes, you'll need to modify the charts/preview/requirements.yaml file to list MongoDB as a dependency. Open the file in your text editor with the following command:

      • nano charts/preview/requirements.yaml

      Edit the file by adding the mongodb-replicaset entry after the alias: cleanup entry, as is highlighted in the following code block:

      charts/preview/requirements.yaml

      # !! File must end with empty line !!
      dependencies:
      - alias: expose
        name: exposecontroller
        repository: http://chartmuseum.jenkins-x.io
        version: 2.3.92
      - alias: cleanup
        name: exposecontroller
        repository: http://chartmuseum.jenkins-x.io
        version: 2.3.92
      - name: mongodb-replicaset
        repository: https://kubernetes-charts.storage.googleapis.com/
        version: 3.5.5
      
        # !! "alias: preview" must be last entry in dependencies array !!
        # !! Place custom dependencies above !!
      - alias: preview
        name: rsvpapp
        repository: file://../rsvpapp
      

      Here you have specified the mongodb-replicaset chart as a dependency for the preview chart.

      Next, repeat this process for your rsvpapp chart. Create the charts/rsvpapp/requirements.yaml file and open it in your text editor:

      • nano charts/rsvpapp/requirements.yaml

      Once the file is open, add the following, making sure that there is a single line of empty space before and after the populated lines:

      charts/rsvpapp/requirements.yaml

      
      dependencies:
      - name: mongodb-replicaset
        repository: https://kubernetes-charts.storage.googleapis.com/
        version: 3.5.5
      
      

      Now you have specified the mongodb-replicaset chart as a dependency for your rsvpapp chart.

      Next, in order to connect the frontend of the sample RSVP application to the MongoDB backend, add a MONGODB_HOST environment variable to your deployment.yaml file in charts/rsvpapp/templates/. Open this file in your text editor:

      • nano charts/rsvpapp/templates/deployment.yaml

      Add the following highlighted lines to the file, in addition to one blank line at the top of the file and two blank lines at the bottom of the file. Note that these blank lines are required for the YAML file to work:

      charts/rsvpapp/templates/deployment.yaml

      
      apiVersion: extensions/v1beta1
      kind: Deployment
      metadata:
        name: {{ template "fullname" . }}
        labels:
          draft: {{ default "draft-app" .Values.draft }}
          chart: "{{ .Chart.Name }}-{{ .Chart.Version | replace "+" "_" }}"
      spec:
        replicas: {{ .Values.replicaCount }}
        template:
          metadata:
            labels:
              draft: {{ default "draft-app" .Values.draft }}
              app: {{ template "fullname" . }}
      {{- if .Values.podAnnotations }}
            annotations:
      {{ toYaml .Values.podAnnotations | indent 8 }}
      {{- end }}
          spec:
            containers:
            - name: {{ .Chart.Name }}
              image: "{{ .Values.image.repository }}:{{ .Values.image.tag }}"
              env:
              - name: MONGODB_HOST
                value: "mongodb://{{.Release.Name}}-mongodb-replicaset-0.{{.Release.Name}}-mongodb-replicaset,{{.Release.Name}}-mongodb-replicaset-1.{{.Release.Name}}-mongodb-replicaset,{{.Release.Name}}-mongodb-replicaset-2.{{.Release.Name}}-mongodb-replicaset:27017"
              imagePullPolicy: {{ .Values.image.pullPolicy }}
              ports:
              - containerPort: {{ .Values.service.internalPort }}
              resources:
      {{ toYaml .Values.resources | indent 12 }}
      
      
      

      With these changes, Helm will be able to deploy your application with MongoDB as its database.

      Next, examine the Jenkinsfile generated by Jenkins X by opening the file from your application's home directory:

      This Jenkinsfile defines the pipeline that is triggered every time you commit a version of your application to your GitHub repository. If you wanted to automate your code testing so that the tests are triggered every time the pipeline is triggered, you would add the test to this document.

      To demonstrate this, add a customized test case by replacing sh "python -m unittest" under stage('CI Build and push snapshot') and stage('Build Release') in the Jenkinsfile with the following highlighted lines:

      /rsvpapp/Jenkinsfile

      . . .
        stages {
          stage('CI Build and push snapshot') {
            when {
              branch 'PR-*'
            }
            environment {
              PREVIEW_VERSION = "0.0.0-SNAPSHOT-$BRANCH_NAME-$BUILD_NUMBER"
              PREVIEW_NAMESPACE = "$APP_NAME-$BRANCH_NAME".toLowerCase()
              HELM_RELEASE = "$PREVIEW_NAMESPACE".toLowerCase()
            }
            steps {
              container('python') {
                sh "pip install -r requirements.txt"
                sh "python -m pytest tests/test_rsvpapp.py"
                sh "export VERSION=$PREVIEW_VERSION && skaffold build -f skaffold.yaml"
                sh "jx step post build --image $DOCKER_REGISTRY/$ORG/$APP_NAME:$PREVIEW_VERSION"
                dir('./charts/preview') {
                  sh "make preview"
                  sh "jx preview --app $APP_NAME --dir ../.."
                }
              }
            }
          }
          stage('Build Release') {
            when {
              branch 'master'
            }
            steps {
              container('python') {
      
                // ensure we're not on a detached head
                sh "git checkout master"
                sh "git config --global credential.helper store"
                sh "jx step git credentials"
      
                // so we can retrieve the version in later steps
                sh "echo $(jx-release-version) > VERSION"
                sh "jx step tag --version $(cat VERSION)"
                sh "pip install -r requirements.txt"
                sh "python -m pytest tests/test_rsvpapp.py"
                sh "export VERSION=`cat VERSION` && skaffold build -f skaffold.yaml"
                sh "jx step post build --image $DOCKER_REGISTRY/$ORG/$APP_NAME:$(cat VERSION)"
              }
            }
          }
      . . .
      

      With the added lines, the Jenkins X pipeline will install dependencies and carry out a Python test whenever you commit a change to your application.

      Now that you have changed the sample RSVP application, commit and push these changes to GitHub with the following commands:

      • git add *
      • git commit -m update
      • git push

      When you push these changes to GitHub, you will trigger a new build of your application. If you open the Jenkins UI by navigating to http://jenkins.jx.your_IP_address.nip.io and entering "admin" for your username and password, you will find information about your new build. If you click "Build History" from the menu on the left side of the page, you should see a history of your committed builds. If you click on the blue icon next to a build then select "Console Ouput" from the lefthand menu, you will find the console output for the automated steps in your pipeline. Scrolling to the end of this output, you will find the following message:

      Output

      . . . Finished: SUCCESS

      This means that your application has passed your customized tests and is now successfully deployed.

      Once Jenkins X builds the application release, it will promote the application to the staging environment. To verify that your application is running, list the applications running on your Kubernetes cluster by using the following command:

      You will receive output similar to the following:

      Output

      APPLICATION STAGING PODS URL rsvpapp 0.0.2 1/1 http://rsvpapp.jx-staging.your_IP_address.nip.io

      From this, you can see that Jenkins X has deployed your application in your jx-staging environment as version 0.0.2. The output also shows the URL that you can use to access your application. Visiting this URL will show you the sample RSVP application:

      Sample RSVP Application in the Staging Environment

      Next, check out the activity of your application with the following command:

      • jx get activity -f rsvpapp

      You will receive output similar to the following:

      Output

      STEP STARTED AGO DURATION STATUS your_GitHub_username/rsvpappv/master #1 3h42m23s 4m51s Succeeded Version: 0.0.1 Checkout Source 3h41m52s 6s Succeeded CI Build and push snapshot 3h41m46s NotExecuted Build Release 3h41m46s 56s Succeeded Promote to Environments 3h40m50s 3m17s Succeeded Promote: staging 3h40m29s 2m36s Succeeded PullRequest 3h40m29s 1m16s Succeeded PullRequest: https://github.com/your_GitHub_username/environment-horsehelix-staging/pull/1 Merge SHA: dc33d3747abdacd2524e8c22f0b5fbb2ac3f6fc7 Update 3h39m13s 1m20s Succeeded Status: Success at: http://jenkins.jx.your_IP_address.nip.io/job/your_GitHub_username/job/environment-horsehelix-staging/job/master/2/display/redirect Promoted 3h39m13s 1m20s Succeeded Application is at: http://rsvpapp.jx-staging.your_IP_address.nip.io Clean up 3h37m33s 1s Succeeded your_GitHub_username/rsvpappv/master #2 28m37s 5m57s Succeeded Version: 0.0.2 Checkout Source 28m18s 4s Succeeded CI Build and push snapshot 28m14s NotExecuted Build Release 28m14s 56s Succeeded Promote to Environments 27m18s 4m38s Succeeded Promote: staging 26m53s 4m0s Succeeded PullRequest 26m53s 1m4s Succeeded PullRequest: https://github.com/your_GitHub_username/environment-horsehelix-staging/pull/2 Merge SHA: 976bd5ad4172cf9fd79f0c6515f5006553ac6611 Update 25m49s 2m56s Succeeded Status: Success at: http://jenkins.jx.your_IP_address.nip.io/job/your_GitHub_username/job/environment-horsehelix-staging/job/master/3/display/redirect Promoted 25m49s 2m56s Succeeded Application is at: http://rsvpapp.jx-staging.your_IP_address.nip.io Clean up 22m40s 0s Succeeded

      Here you are getting the Jenkins X activity for the RSVP application by applying a filter with -f rsvpapp.

      Next, list the pods running in the jx-staging namespace with the following command:

      • kubectl get pod -n jx-staging

      You will receive output similar to the following:

      NAME                                 READY     STATUS    RESTARTS   AGE
      jx-staging-mongodb-replicaset-0      1/1       Running   0          6m
      jx-staging-mongodb-replicaset-1      1/1       Running   0          6m
      jx-staging-mongodb-replicaset-2      1/1       Running   0          5m
      jx-staging-rsvpapp-c864c4844-4fw5z   1/1       Running   0          6m
      

      This output shows that your application is running in the jx-staging namespace, along with three pods of the backend MongoDB database, adhering to the changes you made to the YAML files earlier.

      Now that you have run a test application through the Jenkins X pipeline, you can try out promoting this application to the production environment.

      To finish up this demonstration, you will complete the CI/CD process by promoting the sample RSVP application to your jx-production namespace.

      First, use jx promote in the following command:

      • jx promote rsvpapp --version=0.0.2 --env=production

      This will promote the rsvpapp application running with version=0.0.2 to the production environment. Throughout the build process, Jenkins X will prompt you to enter your GitHub account information. Answer these prompts with your individual responses as they appear.

      After successful promotion, check the list of applications:

      You will receive output similar to the following:

      Output

      APPLICATION STAGING PODS URL PRODUCTION PODS URL rsvpapp 0.0.2 1/1 http://rsvpapp.jx-staging.your_IP_address.nip.io 0.0.2 1/1 http://rsvpapp.jx-production.your_IP_address.nip.io

      With this PRODUCTION information, you can confirm that Jenkins X has promoted rsvpapp to the production environment. For further verification, visit the production URL http://rsvpapp.jx-production.your_IP_address.nip.io in your browser. You should see the working application, now runnning from "production":

      Sample RSVP Application in the Production Environment

      Finally, list your pods in the jx-production namespace.

      • kubectl get pod -n jx-production

      You will find that rsvpapp and the MongoDB backend pods are running in this namespace:

      NAME                                     READY     STATUS    RESTARTS   AGE
      jx-production-mongodb-replicaset-0       1/1       Running   0          1m
      jx-production-mongodb-replicaset-1       1/1       Running   0          1m
      jx-production-mongodb-replicaset-2       1/1       Running   0          55s
      jx-production-rsvpapp-54748d68bd-zjgv7   1/1       Running   0          1m 
      

      This shows that you have successfully promoted the RSVP sample application to your production environment, simulating the production-ready deployment of an application at the end of a CI/CD pipeline.

      Conclusion

      In this tutorial, you used Helm to manage packages on a simulated Kubernetes cluster and customized a Helm chart to package and deploy your own application. You also set up a Jenkins X environment on your Kubernetes cluster and run a sample application through a CI/CD pipeline from start to finish.

      You now have experience with these tools that you can use when building a CI/CD system on your own Kubernetes cluster. If you'd like to learn more about Helm, check out our An Introduction to Helm, the Package Manager for Kubernetes and How To Install Software on Kubernetes Clusters with the Helm Package Manager articles. To explore further CI/CD tools on Kubernetes, you can read about the Istio service mesh in the next tutorial in this webinar series.



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