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      Migrate

      How To Migrate a Docker Compose Workflow for Rails Development to Kubernetes


      Introduction

      When building modern, stateless applications, containerizing your application’s components is the first step in deploying and scaling on distributed platforms. If you have used Docker Compose in development, you will have modernized and containerized your application by:

      • Extracting necessary configuration information from your code.
      • Offloading your application’s state.
      • Packaging your application for repeated use.

      You will also have written service definitions that specify how your container images should run.

      To run your services on a distributed platform like Kubernetes, you will need to translate your Compose service definitions to Kubernetes objects. This will allow you to scale your application with resiliency. One tool that can speed up the translation process to Kubernetes is kompose, a conversion tool that helps developers move Compose workflows to container orchestrators like Kubernetes or OpenShift.

      In this tutorial, you will translate Compose services to Kubernetes objects using kompose. You will use the object definitions that kompose provides as a starting point and make adjustments to ensure that your setup will use Secrets, Services, and PersistentVolumeClaims in the way that Kubernetes expects. By the end of the tutorial, you will have a single-instance Rails application with a PostgreSQL database running on a Kubernetes cluster. This setup will mirror the functionality of the code described in Containerizing a Ruby on Rails Application for Development with Docker Compose and will be a good starting point to build out a production-ready solution that will scale with your needs.

      Prerequisites

      Step 1 — Installing kompose

      To begin using kompose, navigate to the project’s GitHub Releases page, and copy the link to the current release (version 1.22.0 as of this writing). Paste this link into the following curl command to download the latest version of kompose:

      • curl -L https://github.com/kubernetes/kompose/releases/download/v1.22.0/kompose-linux-amd64 -o kompose

      For details about installing on non-Linux systems, please refer to the installation instructions.

      Make the binary executable:

      Move it to your PATH:

      • sudo mv ./kompose /usr/local/bin/kompose

      To verify that it has been installed properly, you can do a version check:

      If the installation was successful, you will see output like the following:

      Output

      1.22.0 (955b78124)

      With kompose installed and ready to use, you can now clone the Node.js project code that you will be translating to Kubernetes.

      Step 2 — Cloning and Packaging the Application

      To use our application with Kubernetes, we will need to clone the project code and package the application so that the kubelet service can pull the image.

      Our first step will be to clone the rails-sidekiq repository from the DigitalOcean Community GitHub account. This repository includes the code from the setup described in Containerizing a Ruby on Rails Application for Development with Docker Compose, which uses a demo Rails application to demonstrate how to set up a development environment using Docker Compose. You can find more information about the application itself in the series Rails on Containers.

      Clone the repository into a directory called rails_project:

      • git clone https://github.com/do-community/rails-sidekiq.git rails_project

      Navigate to the rails_project directory:

      Now checkout the code for this tutorial from the compose-workflow branch:

      • git checkout compose-workflow

      Output

      Branch 'compose-workflow' set up to track remote branch 'compose-workflow' from 'origin'. Switched to a new branch 'compose-workflow'

      The rails_project directory contains files and directories for a shark information application that works with user input. It has been modernized to work with containers: sensitive and specific configuration information has been removed from the application code and refactored to be injected at runtime, and the application’s state has been offloaded to a PostgreSQL database.

      For more information about designing modern, stateless applications, please see Architecting Applications for Kubernetes and Modernizing Applications for Kubernetes.

      The project directory includes a Dockerfile with instructions for building the application image. Let’s build the image now so that you can push it to your Docker Hub account and use it in your Kubernetes setup.

      Using the docker build command, build the image with the -t flag, which allows you to tag it with a memorable name. In this case, tag the image with your Docker Hub username and name it rails-kubernetes or a name of your own choosing:

      • docker build -t your_dockerhub_user/rails-kubernetes .

      The . in the command specifies that the build context is the current directory.

      It will take a minute or two to build the image. Once it is complete, check your images:

      You will see the following output:

      Output

      REPOSITORY TAG IMAGE ID CREATED SIZE your_dockerhub_user/rails-kubernetes latest 24f7e88b6ef2 2 days ago 606MB alpine latest d6e46aa2470d 6 weeks ago 5.57MB

      Next, log in to the Docker Hub account you created in the prerequisites:

      • docker login -u your_dockerhub_user

      When prompted, enter your Docker Hub account password. Logging in this way will create a ~/.docker/config.json file in your user’s home directory with your Docker Hub credentials.

      Push the application image to Docker Hub with the docker push command. Remember to replace your_dockerhub_user with your own Docker Hub username:

      • docker push your_dockerhub_user/rails-kubernetes

      You now have an application image that you can pull to run your application with Kubernetes. The next step will be to translate your application service definitions to Kubernetes objects.

      Step 3 — Translating Compose Services to Kubernetes Objects with kompose

      Our Docker Compose file, here called docker-compose.yml, lays out the definitions that will run our services with Compose. A service in Compose is a running container, and service definitions contain information about how each container image will run. In this step, we will translate these definitions to Kubernetes objects by using kompose to create yaml files. These files will contain specs for the Kubernetes objects that describe their desired state.

      We will use these files to create different types of objects: Services, which will ensure that the Pods running our containers remain accessible; Deployments, which will contain information about the desired state of our Pods; a PersistentVolumeClaim to provision storage for our database data; a ConfigMap for environment variables injected at runtime; and a Secret for our application’s database user and password. Some of these definitions will be in the files kompose will create for us, and others we will need to create ourselves.

      First, we will need to modify some of the definitions in our docker-compose.yml file to work with Kubernetes. We will include a reference to our newly-built application image in our app service definition and remove the bind mounts, volumes, and additional commands that we used to run the application container in development with Compose. Additionally, we’ll redefine both containers’ restart policies to be in line with the behavior Kubernetes expects.

      If you have followed the steps in this tutorial and checked out the compose-workflow branch with git, then you should have a docker-compose.yml file in your working directory.

      If you don’t have a docker-compose.yml then be sure to visit the previous tutorial in this series, Containerizing a Ruby on Rails Application for Development with Docker Compose, and paste the contents from the linked section into a new docker-compose.yml file.

      Open the file with nano or your favorite editor:

      The current definition for the app application service looks like this:

      ~/rails_project/docker-compose.yml

      . . .
      services:
        app:
          build:
            context: .
            dockerfile: Dockerfile
          depends_on:
            - database
            - redis
          ports:
            - "3000:3000"
          volumes:
            - .:/app
            - gem_cache:/usr/local/bundle/gems
            - node_modules:/app/node_modules
          env_file: .env
          environment:
            RAILS_ENV: development
      . . .
      

      Make the following edits to your service definition:

      • Replace the build: line with image: your_dockerhub_user/rails-kubernetes
      • Remove the following context: ., and dockerfile: Dockerfile lines.
      • Remove the volumes list.

      The finished service definition will now look like this:

      ~/rails_project/docker-compose.yml

      . . .
      services:
        app:
          image: your_dockerhub_user/rails-kubernetes
          depends_on:
            - database
            - redis
          ports:
            - "3000:3000"
          env_file: .env
          environment:
            RAILS_ENV: development
      . . .
      

      Next, scroll down to the database service definition and make the following edits:

      • Remove the - ./init.sql:/docker-entrypoint-initdb.d/init.sql volume line. Instead of using values from the local SQL file, we will pass the values for our POSTGRES_USER and POSTGRES_PASSWORD to the database container using the Secret we will create in Step 4.
      • Add a ports: section that will make PostgreSQL available inside your Kubernetes cluster on port 5432.
      • Add an environment: section with a PGDATA variable that points to a directory inside /var/lib/postgresql/data. This setting is required when PostgreSQL is configured to use block storage, since the database engine expects to find its data files in a sub-directory.

      The database service definition should look like this when you are finished editing it:

      ~/rails_project/docker-compose.yml

      . . .
        database:
          image: postgres:12.1
          volumes:
            - db_data:/var/lib/postgresql/data
          ports:
            - "5432:5432"
          environment:
            PGDATA: /var/lib/postgresql/data/pgdata
      . . .
      

      Next, edit the redis service definition to expose its default TCP port by adding a ports: section with the default 6379 port. Adding the ports: section will make Redis available inside your Kubernetes cluster. Your edited redis service should resemble the following:

      ~/rails_project/docker-compose.yml

      . . .
        redis:
          image: redis:5.0.7
          ports:
            - "6379:6379"
      

      After editing the redis section of the file, continue to the sidekiq service definition. Just as with the app service, you’ll need to switch from building a local docker image to pulling from Docker Hub. Make the following edits to your sidekiq service definition:

      • Replace the build: line with image: your_dockerhub_user/rails-kubernetes
      • Remove the following context: ., and dockerfile: Dockerfile lines.
      • Remove the volumes list.

      ~/rails_project/docker-compose.yml

      . . .
        sidekiq:
          image: your_dockerhub_user/rails-kubernetes
          depends_on:
            - app
            - database
            - redis
          env_file: .env
          environment:
              RAILS_ENV: development
          entrypoint: ./entrypoints/sidekiq-entrypoint.sh
      

      Finally, at the bottom of the file, remove the gem_cache and node_modules volumes from the top-level volumes key. The key will now look like this:

      ~/rails_project/docker-compose.yml

      . . .
      volumes:
        db_data:
      

      Save and close the file when you are finished editing.

      For reference, your completed docker-compose.yml file should contain the following:

      ~/rails_project/docker-compose.yml

      version: '3'
      
      services:
        app:
          image: your_dockerhub_user/rails-kubernetes
          depends_on:
              - database
              - redis
          ports:
              - "3000:3000"
          env_file: .env
          environment:
              RAILS_ENV: development
      
        database:
          image: postgres:12.1
          volumes:
              - db_data:/var/lib/postgresql/data
          ports:
              - "5432:5432"
          environment:
              PGDATA: /var/lib/postgresql/data/pgdata
      
        redis:
          image: redis:5.0.7
          ports:
              - "6379:6379"
      
        sidekiq:
          image: your_dockerhub_user/rails-kubernetes
          depends_on:
              - app
              - database
              - redis
          env_file: .env
          environment:
              RAILS_ENV: development
          entrypoint: ./entrypoints/sidekiq-entrypoint.sh
      
      volumes:
        db_data:
      

      Before translating our service definitions, we will need to write the .env file that kompose will use to create the ConfigMap with our non-sensitive information. Please see Step 2 of Containerizing a Ruby on Rails Application for Development with Docker Compose for a longer explanation of this file.

      In that tutorial, we added .env to our .gitignore file to ensure that it would not copy to version control. This means that it did not copy over when we cloned the rails-sidekiq repository in Step 2 of this tutorial. We will therefore need to recreate it now.

      Create the file:

      kompose will use this file to create a ConfigMap for our application. However, instead of assigning all of the variables from the app service definition in our Compose file, we will only add settings for the PostgreSQL and Redis. We will assign the database name, username, and password separately when we manually create a Secret object in Step 4.

      Add the following port and database name information to the .env file. Feel free to rename your database if you would like:

      ~/rails_project/.env

      DATABASE_HOST=database
      DATABASE_PORT=5432
      REDIS_HOST=redis
      REDIS_PORT=6379
      

      Save and close the file when you are finished editing.

      You are now ready to create the files with your object specs. kompose offers multiple options for translating your resources. You can:

      • Create yaml files based on the service definitions in your docker-compose.yml file with kompose convert.
      • Create Kubernetes objects directly with kompose up.
      • Create a Helm chart with kompose convert -c.

      For now, we will convert our service definitions to yaml files and then add to and revise the files that kompose creates.

      Convert your service definitions to yaml files with the following command:

      After you run this command, kompose will output information about the files it has created:

      Output

      INFO Kubernetes file "app-service.yaml" created INFO Kubernetes file "database-service.yaml" created INFO Kubernetes file "redis-service.yaml" created INFO Kubernetes file "app-deployment.yaml" created INFO Kubernetes file "env-configmap.yaml" created INFO Kubernetes file "database-deployment.yaml" created INFO Kubernetes file "db-data-persistentvolumeclaim.yaml" created INFO Kubernetes file "redis-deployment.yaml" created INFO Kubernetes file "sidekiq-deployment.yaml" created

      These include yaml files with specs for the Rails application Service, Deployment, and ConfigMap, as well as for the db-data PersistentVolumeClaim and PostgreSQL database Deployment. Also included are files for Redis and Sidekiq respectively.

      To keep these manifests out of the main directory for your Rails project, create a new directory called k8s-manifests and then use the mv command to move the generated files into it:

      • mkdir k8s-manifests
      • mv *.yaml k8s-manifests

      Finally, cd into the k8s-manifests directory. We’ll work from inside this directory from now on to keep things tidy:

      These files are a good starting point, but in order for our application’s functionality to match the setup described in Containerizing a Ruby on Rails Application for Development with Docker Compose we will need to make a few additions and changes to the files that kompose has generated.

      Step 4 — Creating Kubernetes Secrets

      In order for our application to function in the way we expect, we will need to make a few modifications to the files that kompose has created. The first of these changes will be generating a Secret for our database user and password and adding it to our application and database Deployments. Kubernetes offers two ways of working with environment variables: ConfigMaps and Secrets. kompose has already created a ConfigMap with the non-confidential information we included in our .env file, so we will now create a Secret with our confidential information: our database name, username and password.

      The first step in manually creating a Secret will be to convert the data to base64, an encoding scheme that allows you to uniformly transmit data, including binary data.

      First convert the database name to base64 encoded data:

      • echo -n 'your_database_name' | base64

      Note down the encoded value.

      Next convert your database username:

      • echo -n 'your_database_username' | base64

      Again record the value you see in the output.

      Finally, convert your password:

      • echo -n 'your_database_password' | base64

      Take note of the value in the output here as well.

      Open a file for the Secret:

      Note: Kubernetes objects are typically defined using YAML, which strictly forbids tabs and requires two spaces for indentation. If you would like to check the formatting of any of your yaml files, you can use a linter or test the validity of your syntax using kubectl create with the --dry-run and --validate flags:

      • kubectl create -f your_yaml_file.yaml --dry-run --validate=true

      In general, it is a good idea to validate your syntax before creating resources with kubectl.

      Add the following code to the file to create a Secret that will define your DATABASE_NAME, DATABASE_USER and DATABASE_PASSWORD using the encoded values you just created. Be sure to replace the highlighted placeholder values here with your encoded database name, username and password:

      ~/rails_project/k8s-manifests/secret.yaml

      apiVersion: v1
      kind: Secret
      metadata:
        name: database-secret
      data:
        DATABASE_NAME: your_database_name
        DATABASE_PASSWORD: your_encoded_password
        DATABASE_USER: your_encoded_username
      

      We have named the Secret object database-secret, but you are free to name it anything you would like.

      These secrets are used with the Rails application so that it can connect to PostgreSQL. However, the database itself needs to be initialized with these same values. So next, copy the three lines and paste them at the end of the file. Edit the last three lines and change the DATABASE prefix for each variable to POSTGRES. Finally change the POSTGRES_NAME variable to read POSTGRES_DB.

      Your final secret.yaml file should contain the following:

      ~/rails_project/k8s-manifests/secret.yaml

      apiVersion: v1
      kind: Secret
      metadata:
        name: database-secret
      data:
        DATABASE_NAME: your_database_name
        DATABASE_PASSWORD: your_encoded_password
        DATABASE_USER: your_encoded_username
        POSTGRES_DB: your_database_name
        POSTGRES_PASSWORD: your_encoded_password
        POSTGRES_USER: your_encoded_username
      

      Save and close this file when you are finished editing. As you did with your .env file, be sure to add secret.yaml to your .gitignore file to keep it out of version control.

      With secret.yaml written, our next step will be to ensure that our application and database Deployments both use the values that we added to the file. Let’s start by adding references to the Secret to our application Deployment.

      Open the file called app-deployment.yaml:

      The file’s container specifications include the following environment variables defined under the env key:

      ~/rails_project/k8s-manifests/app-deployment.yaml

      apiVersion: apps/v1
      kind: Deployment
      . . .
          spec:
            containers:
              - env:
                  - name: DATABASE_HOST
                    valueFrom:
                      configMapKeyRef:
                        key: DATABASE_HOST
                        name: env
                  - name: DATABASE_PORT
                    valueFrom:
                      configMapKeyRef:
                        key: DATABASE_PORT
                        name: env
                  - name: RAILS_ENV
                    value: development
                  - name: REDIS_HOST
                    valueFrom:
                      configMapKeyRef:
                        key: REDIS_HOST
                        name: env
                  - name: REDIS_PORT
                    valueFrom:
                      configMapKeyRef:
                        key: REDIS_PORT
                        name: env
      . . .
      

      We will need to add references to our Secret so that our application will have access to those values. Instead of including a configMapKeyRef key to point to our env ConfigMap, as is the case with the existing values, we’ll include a secretKeyRef key to point to the values in our database-secret secret.

      Add the following Secret references after the - name: REDIS_PORT variable section:

      ~/rails_project/k8s-manifests/app-deployment.yaml

      . . .
          spec:
            containers:
              - env:
              . . .  
                  - name: REDIS_PORT
                    valueFrom:
                      configMapKeyRef:
                        key: REDIS_PORT
                        name: env
                  - name: DATABASE_NAME
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: DATABASE_NAME
                  - name: DATABASE_PASSWORD
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: DATABASE_PASSWORD
                  - name: DATABASE_USER
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: DATABASE_USER
      . . .
      
      

      Save and close the file when you are finished editing. As with your secrets.yaml file, be sure to validate your edits using kubectl to ensure there are no issues with spaces, tabs, and indentation:

      • kubectl create -f app-deployment.yaml --dry-run --validate=true

      Output

      deployment.apps/app created (dry run)

      Next, we’ll add the same values to the database-deployment.yaml file.

      Open the file for editing:

      • nano database-deployment.yaml

      In this file, we will add references to our Secret for following variable keys: POSTGRES_DB, POSTGRES_USER and POSTGRES_PASSWORD. The postgres image makes these variables available so that you can modify the initialization of your database instance. The POSTGRES_DB creates a default database that is available when the container starts. The POSTGRES_USER and POSTGRES_PASSWORD together create a privileged user that can access the created database.

      Using the these values means that the user we create has access to all of the administrative and operational privileges of that role in PostgreSQL. When working in production, you will want to create a dedicated application user with appropriately scoped privileges.

      Under the POSTGRES_DB, POSTGRES_USER and POSTGRES_PASSWORD variables, add references to the Secret values:

      ~/rails_project/k8s-manifests/database-deployment.yaml

      apiVersion: apps/v1
      kind: Deployment
      . . .
          spec:
            containers:
              - env:
                  - name: PGDATA
                    value: /var/lib/postgresql/data/pgdata
                  - name: POSTGRES_DB
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: POSTGRES_DB
                  - name: POSTGRES_PASSWORD
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: POSTGRES_PASSWORD        
                  - name: POSTGRES_USER
                    valueFrom:
                      secretKeyRef:
                        name: database-secret
                        key: POSTGRES_USER
      . . .
      

      Save and close the file when you are finished editing. Again be sure to lint your edited file using kubectl with the --dry-run --validate=true arguments.

      With your Secret in place, you can move on to creating the database Service and ensuring that your application container only attempts to connect to the database once it is fully set up and initialized.

      Step 5 — Modifying the PersistentVolumeClaim and Exposing the Application Frontend

      Before running our application, we will make two final changes to ensure that our database storage will be provisioned properly and that we can expose our application frontend using a LoadBalancer.

      First, let’s modify the storage resource defined in the PersistentVolumeClaim that kompose created for us. This Claim allows us to dynamically provision storage to manage our application’s state.

      To work with PersistentVolumeClaims, you must have a StorageClass created and configured to provision storage resources. In our case, because we are working with DigitalOcean Kubernetes, our default StorageClass provisioner is set to dobs.csi.digitalocean.com — DigitalOcean Block Storage.

      We can check this by typing:

      If you are working with a DigitalOcean cluster, you will see the following output:

      Output

      NAME PROVISIONER RECLAIMPOLICY VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE do-block-storage (default) dobs.csi.digitalocean.com Delete Immediate true 76m

      If you are not working with a DigitalOcean cluster, you will need to create a StorageClass and configure a provisioner of your choice. For details about how to do this, please see the official documentation.

      When kompose created db-data-persistentvolumeclaim.yaml, it set the storage resource to a size that does not meet the minimum size requirements of our provisioner. We will therefore need to modify our PersistentVolumeClaim to use the minimum viable DigitalOcean Block Storage unit: 1GB. Please feel free to modify this to meet your storage requirements.

      Open db-data-persistentvolumeclaim.yaml:

      • nano db-data-persistentvolumeclaim.yaml

      Replace the storage value with 1Gi:

      ~/rails_project/k8s-manifests/db-data-persistentvolumeclaim.yaml

      apiVersion: v1
      kind: PersistentVolumeClaim
      metadata:
        creationTimestamp: null
        labels:
          io.kompose.service: db-data
        name: db-data
      spec:
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 1Gi
      status: {}
      

      Also note the accessMode: ReadWriteOnce means that the volume provisioned as a result of this Claim will be read-write only by a single node. Please see the documentation for more information about different access modes.

      Save and close the file when you are finished.

      Next, open app-service.yaml:

      We are going to expose this Service externally using a DigitalOcean Load Balancer. If you are not using a DigitalOcean cluster, please consult the relevant documentation from your cloud provider for information about their load balancers. Alternatively, you can follow the official Kubernetes documentation on setting up a highly available cluster with kubeadm, but in this case you will not be able to use PersistentVolumeClaims to provision storage.

      Within the Service spec, specify LoadBalancer as the Service type:

      ~/rails_project/k8s-manifests/app-service.yaml

      apiVersion: v1
      kind: Service
      . . .
      spec:
        type: LoadBalancer
        ports:
      . . .
      

      When we create the app Service, a load balancer will be automatically created, providing us with an external IP where we can access our application.

      Save and close the file when you are finished editing.

      With all of our files in place, we are ready to start and test the application.

      Note:
      If you would like to compare your edited Kubernetes manifests to a set of reference files to be certain that your changes match this tutorial, the companion Github repository contains a set of tested manifests. You can compare each file individually, or you can also switch your local git branch to use the kubernetes-workflow branch.

      If you opt to switch branches, be sure to copy your secrets.yaml file into the new checked out version since we added it to .gitignore earlier in the tutorial.

      Step 6 — Starting and Accessing the Application

      It’s time to create our Kubernetes objects and test that our application is working as expected.

      To create the objects we’ve defined, we’ll use kubectl create with the -f flag, which will allow us to specify the files that kompose created for us, along with the files we wrote. Run the following command to create the Rails application and PostgreSQL database, Redis cache, and Sidekiq Services and Deployments, along with your Secret, ConfigMap, and PersistentVolumeClaim:

      • kubectl create -f app-deployment.yaml,app-service.yaml,database-deployment.yaml,database-service.yaml,db-data-persistentvolumeclaim.yaml,env-configmap.yaml,redis-deployment.yaml,redis-service.yaml,secret.yaml,sidekiq-deployment.yaml

      You receive the following output, indicating that the objects have been created:

      Output

      deployment.apps/app created service/app created deployment.apps/database created service/database created persistentvolumeclaim/db-data created configmap/env created deployment.apps/redis created service/redis created secret/database-secret created deployment.apps/sidekiq created

      To check that your Pods are running, type:

      You don’t need to specify a Namespace here, since we have created our objects in the default Namespace. If you are working with multiple Namespaces, be sure to include the -n flag when running this kubectl create command, along with the name of your Namespace.

      You will see output similar to the following while your database container is starting (the status will be either Pending or ContainerCreating):

      Output

      NAME READY STATUS RESTARTS AGE app-854d645fb9-9hv7w 1/1 Running 0 23s database-c77d55fbb-bmfm8 0/1 Pending 0 23s redis-7d65467b4d-9hcxk 1/1 Running 0 23s sidekiq-867f6c9c57-mcwks 1/1 Running 0 23s

      Once the database container is started, you will have output like this:

      Output

      NAME READY STATUS RESTARTS AGE app-854d645fb9-9hv7w 1/1 Running 0 30s database-c77d55fbb-bmfm8 1/1 Running 0 30s redis-7d65467b4d-9hcxk 1/1 Running 0 30s sidekiq-867f6c9c57-mcwks 1/1 Running 0 30s

      The Running STATUS indicates that your Pods are bound to nodes and that the containers associated with those Pods are running. READY indicates how many containers in a Pod are running. For more information, please consult the documentation on Pod lifecycles.

      Note:
      If you see unexpected phases in the STATUS column, remember that you can troubleshoot your Pods with the following commands:

      • kubectl describe pods your_pod
      • kubectl logs your_pod

      Now that your application is up and running, the last step that is required is to run Rails’ database migrations. This step will load a schema into the PostgreSQL database for the demo application.

      To run pending migrations you’ll exec into the running application pod and then call the rake db:migrate command.

      First, find the name of the application pod with the following command:

      Find the pod that corresponds to your application like the highlighted pod name in the following output:

      Output

      NAME READY STATUS RESTARTS AGE app-854d645fb9-9hv7w 1/1 Running 0 30s database-c77d55fbb-bmfm8 1/1 Running 0 30s redis-7d65467b4d-9hcxk 1/1 Running 0 30s sidekiq-867f6c9c57-mcwks 1/1 Running 0 30s

      With that pod name noted down, you can now run the kubectl exec command to complete the database migration step.

      Run the migrations with this command:

      • kubectl exec your_app_pod_name -- rake db:migrate

      You should receive output similar to the following, which indicates that the database schema has been loaded:

      Output

      == 20190927142853 CreateSharks: migrating ===================================== -- create_table(:sharks) -> 0.0190s == 20190927142853 CreateSharks: migrated (0.0208s) ============================ == 20190927143639 CreatePosts: migrating ====================================== -- create_table(:posts) -> 0.0398s == 20190927143639 CreatePosts: migrated (0.0421s) ============================= == 20191120132043 CreateEndangereds: migrating ================================ -- create_table(:endangereds) -> 0.8359s == 20191120132043 CreateEndangereds: migrated (0.8367s) =======================

      With your containers running and data loaded, you can now access the application. To get the IP for the app LoadBalancer, type:

      You will receive output like the following:

      Output

      NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE app LoadBalancer 10.245.73.142 your_lb_ip 3000:31186/TCP 21m database ClusterIP 10.245.155.87 <none> 5432/TCP 21m kubernetes ClusterIP 10.245.0.1 <none> 443/TCP 21m redis ClusterIP 10.245.119.67 <none> 6379/TCP 21m

      The EXTERNAL_IP associated with the app service is the IP address where you can access the application. If you see a <pending> status in the EXTERNAL_IP column, this means that your load balancer is still being created.

      Once you see an IP in that column, navigate to it in your browser: http://your_lb_ip:3000.

      You should see the following landing page:

      Application Landing Page

      Click on the Get Shark Info button. You will have a page with a button to create a new shark:

      Shark Info Form

      Click it and when prompted, enter the username and password from earlier in the tutorial series. If you did not change these values then the defaults are sammy and shark respectively.

      In the form, add a shark of your choosing. To demonstrate, we will add Megalodon Shark to the Shark Name field, and Ancient to the Shark Character field:

      Filled Shark Form

      Click on the Submit button. You will see a page with this shark information displayed back to you:

      Shark Output

      You now have a single instance setup of a Rails application with a PostgreSQL database running on a Kubernetes cluster. You also have a Redis cache and a Sidekiq worker to process data that users submit.

      Conclusion

      The files you have created in this tutorial are a good starting point to build from as you move toward production. As you develop your application, you can work on implementing the following:



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      How To Back Up, Restore, and Migrate a MongoDB Database on Ubuntu 18.04


      The author selected the COVID-19 Relief Fund to receive a donation as part of the Write for DOnations program.

      Introduction

      MongoDB is one of the most popular NoSQL database engines. It is famous for being scalable, robust, reliable, and easy to use. In this article, you will back up, restore, and migrate a sample MongoDB database.

      Importing and exporting a database means dealing with data in a human-readable format that is compatible with other software products. In contrast, MongoDB’s backup and restore operations create or use MongoDB-specific binary data, which preserves not only the consistency and integrity of your data but also its specific MongoDB attributes. Thus, for migration, it’s usually preferable to use backup and restore as long as the source and target systems are compatible.

      Prerequisites

      Before following this tutorial, please make sure you complete the following prerequisites:

      Except otherwise noted, all of the commands that require root privileges in this tutorial should be run as a non-root user with sudo privileges.

      Step 1 — Using JSON and BSON in MongoDB

      Before continuing further with this article, some basic understanding of the matter is needed. If you have experience with other NoSQL database systems such as Redis, you may find some similarities when working with MongoDB.

      MongoDB uses JSON and BSON (binary JSON) formats for storing its information. JSON is the human-readable format that is perfect for exporting and, eventually, importing your data. You can further manage your exported data with any tool that supports JSON, including a simple text editor.

      An example json document looks like this:

      Example of JSON Format

      {"address":[
          {"building":"1007", "street":"Park Ave"},
          {"building":"1008", "street":"New Ave"},
      ]}
      

      JSON is convenient to work with, but it does not support all the data types available in BSON. This means that there will be the so-called ‘loss of fidelity’ of the information if you use JSON. For backing up and restoring, it’s better to use the binary BSON.

      Second, you don’t have to worry about explicitly creating a MongoDB database. If the database you specify for import doesn’t already exist, it is automatically created. Even better is the case with the collections’ (database tables) structure. In contrast to other database engines, in MongoDB, the structure is again automatically created upon the first document (database row) insert.

      Third, in MongoDB, reading or inserting large amounts of data, such as this article’s tasks, can be resource-intensive and consume much of your CPU, memory, and disk space. This is critical considering that MongoDB is frequently used for large databases and Big Data. The simplest solution to this problem is to run the exports and backups during the night or non-peak hours.

      Fourth, information consistency could be problematic if you have a busy MongoDB server where the information changes during the database export or backup process. One possible solution for this problem is replication, which you may consider when you advance in the MongoDB topic.

      While you can use the import and export functions to backup and restore your data, there are better ways to ensure the full integrity of your MongoDB databases. To backup your data, you should use the command mongodump. For restoring, use mongorestore. Let’s see how they work.

      Step 2 — Using mongodump to Back Up a MongoDB Database

      Let’s cover backing up your MongoDB database first.

      An essential argument to mongodump is --db, which specifies the name of the database you want to back up. If you don’t specify a database name, mongodump backs up all of your databases. The second important argument is --out, which defines the directory into which the data will be dumped. For example, let’s back up the newdb database and storing it in the /var/backups/mongobackups directory. Ideally, we’ll have each of our backups in a directory with the current date like /var/backups/mongobackups/10-29-20.

      First create that directory /var/backups/mongobackups:

      • sudo mkdir /var/backups/mongobackups

      Then run mongodump:

      • sudo mongodump --db newdb --out /var/backups/mongobackups/`date +"%m-%d-%y"`

      You will see an output like this:

      Output

      2020-10-29T19:22:36.886+0000 writing newdb.restaurants to 2020-10-29T19:22:36.969+0000 done dumping newdb.restaurants (25359 documents)

      Note that in the above directory path, we have used date +"%m-%d-%y" which automatically gets the current date. This will allow us to have backups inside the directory like /var/backups/10-29-20/. This is especially convenient when we automate the backups.

      At this point you have a complete backup of the newdb database in the directory /var/backups/mongobackups/10-29-20/newdb/. This backup has everything to restore the newdb properly and preserve its so-called “fidelity.”

      As a general rule, you should make regular backups and preferably when the server is least loaded. Thus, you can set the mongodump command as a cron job so that it runs regularly, e.g., every day at 03:03 AM.

      To accomplish this open crontab, cron’s editor:

      Note that when you run sudo crontab, you will be editing the cron jobs for the root user. This is recommended because if you set the crons for your user, they might not execute properly, especially if your sudo profile requires password verification.

      Inside the crontab prompt, insert the following mongodump command:

      crontab

      3 3 * * * mongodump --out /var/backups/mongobackups/`date +"%m-%d-%y"`
      

      In the above command, we omit the --db argument on purpose because you will typically want to have all of your databases backed up.

      Depending on your MongoDB database sizes, you may soon run out of disk space with too many backups. That’s why it’s also recommended to clean the old backups regularly or to compress them.

      For example, to delete all the backups older than seven days, you can use the following bash command:

      • find /var/backups/mongobackups/ -mtime +7 -exec rm -rf {} ;

      Similarly to the previous mongodump command, you can also add this as a cron job. It should run just before you start the next backup, e.g., at 03:01 AM. For this purpose, open crontab again:

      After that insert the following line:

      crontab

      3 1 * * * find /var/backups/mongobackups/ -mtime +7 -exec rm -rf {} ;
      

      save and close the file.

      Completing all the tasks in this step will ensure a proper backup solution for your MongoDB databases.

      Step 3 — Using mongorestore to Restore and Migrate a MongoDB Database

      When you restore your MongoDB database from a previous backup, you have the exact copy of your MongoDB information taken at a particular time, including all the indexes and data types. This is especially useful when you want to migrate your MongoDB databases. For restoring MongoDB, we’ll use the command mongorestore, which works with the binary backups that mongodump produces.

      Let’s continue our examples with the newdb database and restore it from the previously taken backup. As arguments, we’ll specify first the name of the database with the --db argument. Then with --drop, we’ll make sure that the target database is first dropped so that the backup is restored in a clean database. As a final argument we’ll specify the directory of the last backup, which will look something like this: /var/backups/mongobackups/10-29-20/newdb/.

      Once you have a timestamped backup, you can restore it using this command:

      • sudo mongorestore --db newdb --drop /var/backups/mongobackups/10-29-20/newdb/

      You will see an output like this:

      Output

      2020-10-29T19:25:45.825+0000 the --db and --collection args should only be used when restoring from a BSON file. Other uses are deprecated and will not exist in the future; use --nsInclude instead 2020-10-29T19:25:45.826+0000 building a list of collections to restore from /var/backups/mongobackups/10-29-20/newdb dir 2020-10-29T19:25:45.829+0000 reading metadata for newdb.restaurants from /var/backups/mongobackups/10-29-20/newdb/restaurants.metadata.json 2020-10-29T19:25:45.834+0000 restoring newdb.restaurants from /var/backups/mongobackups/10-29-20/newdb/restaurants.bson 2020-10-29T19:25:46.130+0000 no indexes to restore 2020-10-29T19:25:46.130+0000 finished restoring newdb.restaurants (25359 documents) 2020-10-29T19:25:46.130+0000 done

      In the above case, we are restoring the data on the same server where we created the backup. If you wish to migrate the data to another server and use the same technique, you should copy the backup directory, which is /var/backups/mongobackups/10-29-20/newdb/ in our case, to the other server.

      Conclusion

      You have now performed some essential tasks related to backing up, restoring, and migrating your MongoDB databases. No production MongoDB server should ever run without a reliable backup strategy, such as the one described here.



      Source link

      How To Back Up, Restore, and Migrate a MongoDB Database on Ubuntu 20.04


      The author selected the COVID-19 Relief Fund to receive a donation as part of the Write for DOnations program.

      Introduction

      MongoDB is one of the most popular NoSQL database engines. It is famous for being scalable, robust, reliable, and easy to use. In this article, you will back up, restore, and migrate a sample MongoDB database.

      Importing and exporting a database means dealing with data in a human-readable format that is compatible with other software products. In contrast, MongoDB’s backup and restore operations create or use MongoDB-specific binary data, which preserves not only the consistency and integrity of your data but also its specific MongoDB attributes. Thus, for migration, it’s usually preferable to use backup and restore as long as the source and target systems are compatible.

      Prerequisites

      Before following this tutorial, please make sure you complete the following prerequisites:

      Except otherwise noted, all of the commands that require root privileges in this tutorial should be run as a non-root user with sudo privileges.

      Step 1 — Using JSON and BSON in MongoDB

      Before continuing further with this article, some basic understanding of the matter is needed. If you have experience with other NoSQL database systems such as Redis, you may find some similarities when working with MongoDB.

      MongoDB uses JSON and BSON (binary JSON) formats for storing its information. JSON is the human-readable format that is perfect for exporting and, eventually, importing your data. You can further manage your exported data with any tool that supports JSON, including a simple text editor.

      An example json document looks like this:

      Example of JSON Format

      {"address":[
          {"building":"1007", "street":"Park Ave"},
          {"building":"1008", "street":"New Ave"},
      ]}
      

      JSON is convenient to work with, but it does not support all the data types available in BSON. This means that there will be the so-called ‘loss of fidelity’ of the information if you use JSON. For backing up and restoring, it’s better to use the binary BSON.

      Second, you don’t have to worry about explicitly creating a MongoDB database. If the database you specify for import doesn’t already exist, it is automatically created. Even better is the case with the collections’ (database tables) structure. In contrast to other database engines, in MongoDB, the structure is again automatically created upon the first document (database row) insert.

      Third, in MongoDB, reading or inserting large amounts of data, such as this article’s tasks, can be resource-intensive and consume much of your CPU, memory, and disk space. This is critical considering that MongoDB is frequently used for large databases and Big Data. The simplest solution to this problem is to run the exports and backups during the night or non-peak hours.

      Fourth, information consistency could be problematic if you have a busy MongoDB server where the information changes during the database export or backup process. One possible solution for this problem is replication, which you may consider when you advance in the MongoDB topic.

      While you can use the import and export functions to backup and restore your data, there are better ways to ensure the full integrity of your MongoDB databases. To backup your data, you should use the command mongodump. For restoring, use mongorestore. Let’s see how they work.

      Step 2 — Using mongodump to Back Up a MongoDB Database

      Let’s cover backing up your MongoDB database first.

      An essential argument to mongodump is --db, which specifies the name of the database you want to back up. If you don’t specify a database name, mongodump backs up all of your databases. The second important argument is --out, which defines the directory into which the data will be dumped. For example, let’s back up the newdb database and storing it in the /var/backups/mongobackups directory. Ideally, we’ll have each of our backups in a directory with the current date like /var/backups/mongobackups/10-29-20.

      First create that directory /var/backups/mongobackups:

      • sudo mkdir /var/backups/mongobackups

      Then run mongodump:

      • sudo mongodump --db newdb --out /var/backups/mongobackups/`date +"%m-%d-%y"`

      You will see an output like this:

      Output

      2020-10-29T19:22:36.886+0000 writing newdb.restaurants to 2020-10-29T19:22:36.969+0000 done dumping newdb.restaurants (25359 documents)

      Note that in the above directory path, we have used date +"%m-%d-%y" which automatically gets the current date. This will allow us to have backups inside the directory like /var/backups/10-29-20/. This is especially convenient when we automate the backups.

      At this point you have a complete backup of the newdb database in the directory /var/backups/mongobackups/10-29-20/newdb/. This backup has everything to restore the newdb properly and preserve its so-called “fidelity.”

      As a general rule, you should make regular backups and preferably when the server is least loaded. Thus, you can set the mongodump command as a cron job so that it runs regularly, e.g., every day at 03:03 AM.

      To accomplish this open crontab, cron’s editor:

      Note that when you run sudo crontab, you will be editing the cron jobs for the root user. This is recommended because if you set the crons for your user, they might not execute properly, especially if your sudo profile requires password verification.

      Inside the crontab prompt, insert the following mongodump command:

      crontab

      3 3 * * * mongodump --out /var/backups/mongobackups/`date +"%m-%d-%y"`
      

      In the above command, we omit the --db argument on purpose because you will typically want to have all of your databases backed up.

      Depending on your MongoDB database sizes, you may soon run out of disk space with too many backups. That’s why it’s also recommended to clean the old backups regularly or to compress them.

      For example, to delete all the backups older than seven days, you can use the following bash command:

      • find /var/backups/mongobackups/ -mtime +7 -exec rm -rf {} ;

      Similarly to the previous mongodump command, you can also add this as a cron job. It should run just before you start the next backup, e.g., at 03:01 AM. For this purpose, open crontab again:

      After that insert the following line:

      crontab

      3 1 * * * find /var/backups/mongobackups/ -mtime +7 -exec rm -rf {} ;
      

      save and close the file.

      Completing all the tasks in this step will ensure a proper backup solution for your MongoDB databases.

      Step 3 — Using mongorestore to Restore and Migrate a MongoDB Database

      When you restore your MongoDB database from a previous backup, you have the exact copy of your MongoDB information taken at a particular time, including all the indexes and data types. This is especially useful when you want to migrate your MongoDB databases. For restoring MongoDB, we’ll use the command mongorestore, which works with the binary backups that mongodump produces.

      Let’s continue our examples with the newdb database and see how we can restore it from the previously taken backup. We’ll first specify the name of the database with the --nsInclude argument. We’ll be using newdb.* to restore all collections. To restore a single collection such as restaurants, use newdb.restaurants instead.

      Then, using --drop, we’ll make sure that the target database is first dropped so that the backup is restored in a clean database. As a final argument we’ll specify the directory of the last backup, which will look something like this: /var/backups/mongobackups/10-29-20/newdb/.

      Once you have a timestamped backup, you can restore it using this command:

      • sudo mongorestore --db newdb --drop /var/backups/mongobackups/10-29-20/newdb/

      You will see an output like this:

      Output

      2020-10-29T19:25:45.825+0000 the --db and --collection args should only be used when restoring from a BSON file. Other uses are deprecated and will not exist in the future; use --nsInclude instead 2020-10-29T19:25:45.826+0000 building a list of collections to restore from /var/backups/mongobackups/10-29-20/newdb dir 2020-10-29T19:25:45.829+0000 reading metadata for newdb.restaurants from /var/backups/mongobackups/10-29-20/newdb/restaurants.metadata.json 2020-10-29T19:25:45.834+0000 restoring newdb.restaurants from /var/backups/mongobackups/10-29-20/newdb/restaurants.bson 2020-10-29T19:25:46.130+0000 no indexes to restore 2020-10-29T19:25:46.130+0000 finished restoring newdb.restaurants (25359 documents) 2020-10-29T19:25:46.130+0000 done

      In the above case, we are restoring the data on the same server where we created the backup. If you wish to migrate the data to another server and use the same technique, you should copy the backup directory, which is /var/backups/mongobackups/10-29-20/newdb/ in our case, to the other server.

      Conclusion

      You have now performed some essential tasks related to backing up, restoring, and migrating your MongoDB databases. No production MongoDB server should ever run without a reliable backup strategy, such as the one described here.



      Source link