Open Source - Red Hat OpenShift

Standard open-source Kubernetes distributions do not contain any user management features. Kubectl can be used with Red Hat OpenShift.

1. What is OpenShift?

• Enterprise Features: OpenShift is an enterprise-class platform built on Kubernetes, offering enhanced security, high availability, and integrated DevOps tools.

• Integrated Tools: It includes built-in user and group management, a visual management console, an embedded container registry, CI/CD pipelines, and integrated monitoring and logging.

• Deployment Options: OpenShift can be installed on-premise, run locally using CodeReady Containers, or accessed through managed services on major cloud providers like AWS, Azure, and IBM Cloud.

These features make OpenShift a robust solution for enterprise users looking to leverage Kubernetes with added enterprise-grade capabilities.

2. What are the available Red Hat OpenShift tools:

• Web Console and Command-Line Tools: OpenShift provides a graphical web console and command-line tools (oc and odo) tailored for developers and cluster administrators, enhancing productivity and efficiency.

• Developer and Administrator Perspectives: The web console offers different views for developers and administrators, allowing them to perform tasks relevant to their roles, such as deploying and debugging applications or managing cluster resources.

• Compatibility with kubectl: The standard kubectl tool is fully compatible with OpenShift, enabling DevOps engineers to leverage their existing Kubernetes knowledge and scripts seamlessly.

These tools make it easier to manage and deploy applications on OpenShift, aligning well with your interest in cloud computing and software development.

3. How significant are Red Hat OpenShift CRDs?

   • Custom Resource Definitions (CRDs): OpenShift extends Kubernetes with additional CRDs I like to call “customizable building blocks”, such as the project object and route object, which offer more flexibility and integration into the security system.

   • OpenShift Projects: These are similar to Kubernetes namespaces but include additional metadata and tighter security integration, allowing cluster administrators to delegate tasks to regular users.

   • Deployment Configs and Build Configs: OpenShift includes unique objects like deployment configs and build configs, which provide advanced features such as automatic rollbacks and integrated build processes for applications.

These points highlight how OpenShift enhances Kubernetes with additional features and flexibility, making it a powerful tool for DevOps engineers.

4. Red Hat OpenShift Developer Sandbox?

   • Free Access: The Developer Sandbox for Red Hat OpenShift provides free access to a fully managed OpenShift cluster for 30 days, allowing developers to deploy and test applications in a secure environment.

   • Easy Setup: You only need a free Red Hat developer account to get started. The setup process involves account verification via SMS and email.

   • Integrated Development Environment: The sandbox includes Red Hat OpenShift Dev Spaces, which offers a web-based version of Visual Studio Code and supports various programming languages and frameworks, making it easy to develop and deploy applications directly within the OpenShift cluster.

This sandbox environment is an excellent way to get hands-on experience with OpenShift and explore its features.

5. "Red Hat OpenShift Local":

   • Local Testing Environment: OpenShift Local, formerly known as CodeReady Containers (CRC), allows developers to test OpenShift on their own computers using a minimalistic environment.

   • System Requirements: It requires specific operating systems (Windows 10, macOS 11, or certain Linux distributions) and hardware (recent Intel CPU, 16GB RAM minimum, and 35GB of free disk space).

   • Installation Process: The installation involves downloading OpenShift Local and a pull secret file, unzipping the executable, running setup commands, and starting the cluster, which can take around 20 minutes.

This setup helps developers explore OpenShift features without needing a full production environment.

6. When users create an Ingress object for their deployments, OpenShift automatically creates a Route. Route objects can also be created on demand.

7. Understanding OpenShift security:

   • Enhanced Security Defaults: OpenShift places more restrictive conditions around containers compared to other Kubernetes distributions to prevent privilege escalation and other security threats.

   • User Roles and Service Accounts: OpenShift uses specific user roles (e.g., admin, basic user, cluster admin) and service accounts to manage access and ensure secure interactions with external services like CI/CD systems.

   • Base Images and Non-Root Accounts: To ensure container images run securely on OpenShift, developers should use Red Hat Universal Base Images (UBI) or Bitnami images and configure containers to run as non-root users with ports above 1024.

These points highlight how OpenShift prioritizes security to protect containerized applications.

8. Deploying and debugging containers:

   • Deployment Methods: OpenShift allows deploying containers using various methods, including YAML manifests, the web console, Git repositories, CI/CD pipelines, and the odo tool with dev files.

   • Web Console Deployment: You can deploy applications immediately using the web console by creating a project, selecting the "+Add" option, and specifying the URL of a container image or source code project.

   • Debugging with odo: The odo tool enables developers to create applications using dev files and deploy them directly from the command line, supporting debugging with breakpoints and step-by-step execution.

These points illustrate how OpenShift provides flexible and powerful tools for deploying and debugging containerized applications.

9. You can leverage OpenShift's ability to build containers directly from your Git repositories to streamline your development workflow. By integrating your Python projects with OpenShift, you can automate the build and deployment processes, ensuring that your applications are consistently packaged and deployed across different environments. This is particularly useful for maintaining the high standards required in the motor vehicle manufacturing industry.

   Here are some steps you can take to apply this content:

   1. Set Up a Project: Use the OpenShift web console to create a new project where you can manage your work.

   2. Import from Git: Navigate to the developer perspective and use the "Import from Git" option to paste the URL of your Python project's repository.

   3. Automated Builds: OpenShift will analyze your project's structure and recommend build options. Once you initiate the build, OpenShift will compile your code into a container.

   4. Deployment: After the build, you can deploy the containerized application directly from the OpenShift web console, making it easy to test and run your Python applications.

This process will help you automate and streamline your development and deployment workflows, enhancing efficiency and reliability in your projects.

10. Using CI/CD pipelines:

    CI/CD Integration: OpenShift includes the Tekton Open Source project, providing a complete CI/CD environment for continuous integration and continuous delivery.

    • Pipeline Setup: Administrators must install the Red Hat OpenShift Pipelines Operator to enable CI/CD pipelines. Once installed, developers can use the OpenShift web console or command-line tools to create and manage pipelines.

    • Pipeline Components: Tekton pipelines consist of tasks (individual operations), pipelines (sets of tasks), and workspaces (shared storage). These can be created using YAML or the Visual Editor in the OpenShift web console.

These points highlight how OpenShift facilitates automated and efficient CI/CD processes for application development and deployment.

11. Here are the key takeaways from the video "Solution: Setup a CI/CD pipeline in your cluster":

    • Pipeline Creation: You manually create a CI/CD pipeline in OpenShift by downloading source code from GitLab, building a container image, and storing it in the OpenShift Container Registry.

    • Graphical Pipeline Builder: The OpenShift web console provides a graphical pipeline builder to add tasks like Git Clone and Kaniko for building container images.

    • Pipeline Execution: After setting up the pipeline with required tasks and parameters, you can start the pipeline run, which clones the source code, builds the container image, and stores it in the registry.

These steps illustrate how to set up and run a CI/CD pipeline in OpenShift, enhancing your ability to automate and streamline the development process.

12. OpenShift operators and templates:

    • Operators: These are software extensions that automate the deployment and management of Kubernetes-native applications on OpenShift. They can handle tasks like provisioning, scaling, backup, and recovery, reducing the operational burden on users.

    • Templates: YAML or JSON files that describe the desired state of application components. They simplify and automate the creation of complex applications and can be instantiated with a single command or through the web console.

    • Integration and Customization: Operators can integrate with other OpenShift features and expose configuration options through custom resource definitions (CRDs), while templates can be populated with environment variables to define reusable and parameterized application configurations.

These tools provide powerful ways to manage and deploy applications efficiently on OpenShift.

13. Serverless applications with Knative:

    • Serverless Model: Knative enables serverless functionality on OpenShift, allowing applications to scale automatically based on demand without human intervention.

    • Knative Services: These are defined using YAML and follow a versioning schema, allowing multiple versions of the same service to run simultaneously.

    • Automatic Scaling: Knative uses standard containers as serverless units of work, automatically scaling the number of pods up or down based on demand.

This functionality helps streamline the deployment and management of serverless applications in OpenShift.

14. Service mesh with Istio:

    • Service Mesh Benefits: A service mesh provides reliable and secure communication between microservices, offering features like load balancing, service discovery, encryption, authentication, authorization, observability, fault tolerance, and resilience.

    • OpenShift Service Mesh: This is based on the Istio project and integrates with Kiali for a graphical UI to visualize and manage the service mesh.

    • Deployment and Management: Istio integrates transparently with existing applications through sidecar proxies, and OpenShift Service Mesh is installed using the Red Hat operator.

These points highlight how Istio and OpenShift Service Mesh enhance the management and security of microservices.

15. Logging and adding probes to applications:

    • Integrated Logging Tools: OpenShift includes built-in tools like Prometheus and Kibana for monitoring and logging, following Kubernetes best practices.

    • Log Management: Applications should publish log messages to standard output, which can be accessed via the OpenShift web console. For more extensive logging, Elasticsearch and Kibana operators can be used.

    • Configuration for Monitoring: To enable monitoring on OpenShift Local, you need to configure your CRC cluster, ensuring enough disk space and RAM for Elasticsearch and Kibana.

These points highlight how OpenShift simplifies monitoring and logging for cloud-native applications.

16. Manual, horizontal, and vertical scaling:

    • Manual Scaling: Cluster operators can manually adjust the number of pods in a deployment through the OpenShift console, but this can lead to inconsistencies between environments.

    • Horizontal Scaling: This involves adding or removing nodes or pods to handle more traffic and improve availability. It uses a HorizontalPodAutoscaler object to automatically adjust the number of pods based on CPU or memory utilization.

    • Vertical Scaling: This adjusts the resource limits and requests of pods to optimize resource utilization. A VerticalPodAutoscaler object automatically updates resource values based on historical and current usage data.

These points explain how OpenShift provides both manual and automated methods to scale applications efficiently.

In essence, horizontal scaling increases the number of instances to handle more traffic, while vertical scaling optimizes the resources of existing instances for better performance. Both methods can be automated to ensure your application scales efficiently without manual intervention.

17. What project provides log aggregation for microservice applications deployed on OpenShift?onitoring apps with Prometheus:

    • Real-Time Monitoring: Prometheus is integrated into OpenShift to monitor applications in real-time, tracking metrics like memory and disk usage.

    • Metrics Export: Many programming languages and frameworks support Prometheus-compatible libraries, making it easy to export metrics to Prometheus using endpoints like /metrics.

    • Visualization Tools: Prometheus data can be queried using PromQL and visualized in the OpenShift web console or with Grafana for a comprehensive view of application health and behavior.

These points highlight how Prometheus helps you monitor and understand the performance of your applications on OpenShift.

18. Elastic Search project provides log aggregation for microservice applications deployed on OpenShift?

19. Why isn't manual scaling a recommended technique? It can lead to inconsistencies between development, staging, and production environments.

    The 12 Factor principles recommend keeping all environments in sync.

20. Vertical scaling consists of adjusting the ______ of your application.

    • resource limits and requests