How to deploy web application in openshift web console

To deploy a web application in OpenShift using the web console, follow these steps:

  1. Create a new project: Before deploying your application, you need to create a new project. You can do this by navigating to the OpenShift web console, selecting the “Projects” dropdown menu, and then clicking on “Create Project”. Enter a name for your project and click “Create”.
  2. Add a new application: In the left-hand navigation menu, click on “Add” and select “From Catalog”. This will open the “Catalog” page, which contains a list of available application templates.
  3. Select an application template: Search for the application template that you want to use and click on it. You can also filter the list of templates by category or language.
  4. Configure your application: On the application configuration page, you can configure various settings for your application, such as the name, version, and route. You can also select additional options, such as whether to enable autoscaling or configure environment variables.
  5. Deploy your application: After you have configured your application, click on “Create” to deploy it to your OpenShift cluster. OpenShift will automatically create the necessary resources, such as pods, services, and routes, to run your application.
  6. Monitor your application: Once your application is deployed, you can monitor its status and performance by navigating to the “Topology” page in the OpenShift web console. Here, you can view the status of your application’s pods and services, as well as any logs or metrics.

In summary, deploying a web application in OpenShift using the web console involves creating a new project, selecting an application template, configuring your application, and deploying it to your cluster. Once your application is deployed, you can monitor its status and performance using the OpenShift web console.

Introduction to Openshift – Introduction to Openshift online cluster

OpenShift is a platform-as-a-service (PaaS) offering from Red Hat. It provides a cloud-like environment for deploying, managing, and scaling applications in a secure and efficient manner. OpenShift uses containers to package and deploy applications, and it provides built-in tools for continuous integration, continuous delivery, and automated testing.

An OpenShift online cluster is a managed instance of OpenShift that is hosted in the cloud. This means that the infrastructure, including the servers and storage, is managed by Red Hat. Customers only need to focus on developing and deploying their applications, without worrying about the underlying infrastructure. OpenShift online clusters can be accessed from anywhere with an internet connection, making it easy for developers to work from anywhere.

OpenShift provides a web-based user interface, as well as command-line tools for managing applications and resources. It also provides built-in support for a wide range of programming languages, databases, and other tools. This makes it easy to get started with OpenShift, regardless of the technology stack you are using.

Overall, OpenShift provides a robust and scalable platform for deploying, managing, and scaling applications. With OpenShift online clusters, you can take advantage of the benefits of OpenShift without having to worry about managing the infrastructure.

OpenShift is a container application platform that provides a platform for developing, deploying, and managing containerized applications. It is built on top of Kubernetes and provides additional functionality, including integrated CI/CD pipelines, integrated registry for storing and sharing images, and a web console for managing the application.

OpenShift provides an online cluster, which is a cluster that is hosted on OpenShift’s servers. This allows users to quickly and easily spin up a cluster without having to manage the infrastructure themselves. The online cluster provides a way to test and develop applications without having to worry about the underlying infrastructure.

Some of the key features of OpenShift’s online cluster include:

  1. Easy deployment: OpenShift makes it easy to deploy and manage applications, with a web-based console and command-line tools.
  2. Scalability: OpenShift provides automatic scaling of applications, so you can scale up or down based on demand.
  3. Integrated CI/CD pipelines: OpenShift provides built-in CI/CD pipelines, so you can automate the process of building, testing, and deploying your applications.
  4. Security: OpenShift provides built-in security features, including role-based access control and security scanning, to help secure your applications and data.

Overall, OpenShift’s online cluster provides a convenient and easy-to-use platform for developing, deploying, and managing containerized applications. Whether you’re a developer, DevOps engineer, or application owner, OpenShift provides the tools you need to build and run your applications in a secure and scalable environment.

JEP 390: Warnings for Value-Based Classes Java17 in detail

JEP 390 (Warnings for Value-Based Classes) is a feature in Java 17 that provides warnings to developers when they use value-based classes in an unintended way.

Value-based classes are a new feature in Java 9 that provide a simpler, more efficient alternative to traditional classes for modeling immutable objects. The main advantage of value-based classes is that they can be compared and hashed based on their contents rather than their references, which can result in better performance and simpler code.

However, because value-based classes are meant to be used in specific ways, it’s possible for developers to use them in unintended ways that can lead to bugs and performance issues. JEP 390 provides warnings to developers when they use value-based classes in an unintended way, such as by trying to extend them or call their equals method.

Here’s an example of how JEP 390 might be used in Java 17:

public class MyValueBasedClass extends java.lang.Number {
// Warning: Cannot inherit from final class java.lang.Number
}

MyValueBasedClass vbc = new MyValueBasedClass();
vbc.equals(vbc); // Warning: equals() not supported for value-based classes

In this example, the first line of code attempts to extend the java.lang.Number class, which is a final class. JEP 390 will generate a warning to inform the developer that extending final classes is not allowed for value-based classes.

The second line of code calls the equals method on a value-based class, which is also not allowed. JEP 390 will generate another warning to inform the developer that the equals method is not supported for value-based classes.

JEP 390 helps to prevent unintended use of value-based classes and ensures that they are used in the intended way, which can improve the performance and stability of Java applications.

JEP 388: Windows/AArch64 Port Java 17 in detail

JEP 388 (Windows/AArch64 Port) is a feature in Java 17 that adds support for running Java on Windows systems with AArch64 (also known as ARM64) architecture.

AArch64 is a 64-bit architecture used by many popular mobile devices, such as smartphones and tablets, as well as high-performance servers. By adding support for AArch64 in Java 17, developers can now write and run Java applications on these platforms using the Java Virtual Machine (JVM).

JEP 388 also adds support for running Java on Windows systems, making it easier for developers to write and run Java applications on Windows computers. This allows for greater flexibility in the deployment of Java applications and makes it possible to target a wider range of devices and platforms.

Here’s an example of how to run a Java application on a Windows system with AArch64 architecture:

java -version
java version "17"
Java(TM) SE Runtime Environment (build 17+0)
Java HotSpot(TM) AArch64 Bit Server VM (build 17+0, mixed mode)

In this example, the java -version command is used to display the version of Java that is installed on the system. The output shows that Java 17 is installed and running on an AArch64 architecture, which is running on a Windows system.

JEP 388 expands the range of platforms that Java can run on and makes it easier for developers to write and run Java applications on these platforms. This opens up new opportunities for the deployment of Java applications and makes it possible to target a wider range of devices and platforms.

JEP 384: Records and Pattern Matching for switch Java 17 in detail

JEP 384 (Records and Pattern Matching for switch) is a feature in Java 17 that enhances the switch statement to support pattern matching with both classes and records. This feature makes the switch statement more powerful and expressive, and simplifies common programming tasks such as working with complex data structures.

Records are a new feature in Java 17 that provide a concise and readable way to define simple classes that act as transparent holders for data. Records can be used as data structures, similar to structs or tuples in other programming languages, and they automatically provide getters, equals, hashCode, and toString methods based on their fields.

The new pattern matching capability in Java 17 allows you to use a switch statement to match against records and other objects in a type-safe and efficient manner. The switch statement can now be used to perform complex data-driven computations and make type-based decisions based on the fields of records and other objects.

Here is an example of how you can use the enhanced switch statement in Java 17 to perform pattern matching with records:

record Point(int x, int y) {}

Point p = new Point(10, 20);

switch (p) {
case var (x, y) when x > 0 && y > 0:
System.out.println("Point is in the first quadrant: " + p);
break;
case var (x, y) when x < 0 && y < 0:
System.out.println("Point is in the third quadrant: " + p);
break;
case var (x, y) when x == 0 || y == 0:
System.out.println("Point is on the x or y axis: " + p);
break;
default:
System.out.println("Point is in the second or fourth quadrant: " + p);
break;
}

In this example, a record Point with two fields, x and y, is defined. The switch statement then matches against the Point object p, and the cases of the switch statement use pattern matching to perform computations based on the values of the x and y fields of the Point record.

Records are a new type of class in Java that provide a compact and concise way to define simple data classes. Records have a fixed number of fields and automatically derive equals, hashCode, toString, and other methods from those fields.

Here’s an example of a record definition in Java 17:

record Point(int x, int y) {}

Pattern matching allows you to match objects against patterns, and the switch statement has been extended to support pattern matching in Java 17. This makes it possible to write more concise and readable code by matching objects against patterns in a switch statement, instead of using a series of if-else statements.

Here’s an example of a switch statement that uses pattern matching in Java 17:

Point p = new Point(1, 2);

switch (p) {
case Point(0, 0):
System.out.println("The point is at the origin");
break;
case Point(x, y):
System.out.println("The point is at (" + x + ", " + y + ")");
break;
}

In this example, the Point record is used to create a Point object with the x and y values of 1 and 2, respectively. The switch statement matches the Point object against two different patterns. If the Point object matches the Point(0, 0) pattern, the code prints “The point is at the origin”. If it matches the Point(x, y) pattern, the code prints the values of x and y.

JEP 384 makes it possible to write more concise and readable code by using records and pattern matching in switch statements. This enhances the expressiveness of the Java language and makes it easier to write elegant and maintainable code.

JEP 384 provides a powerful and expressive way to perform pattern matching with records and other objects in Java, making it easier to write clean and maintainable code that works with complex data structures.

JEP 387: Elastic Metaspace Java 17 in detail

JEP 387 (Elastic Metaspace) is a feature in Java 17 that aims to improve the performance of the Java Virtual Machine (JVM) by making the metaspace, which is the part of the JVM that stores class metadata, more scalable and efficient.

In previous versions of Java, the size of the metaspace was limited by the amount of physical memory available on the system. When the metaspace was full, the JVM would throw an OutOfMemoryError, which could lead to unexpected behavior or crashes in applications.

JEP 387 introduces an elastic metaspace, which dynamically adjusts its size based on the needs of the application. When the metaspace is low on memory, it can automatically reclaim memory by freeing unused class metadata. When the metaspace is running low on memory, the JVM will also try to acquire more memory from the operating system.

Here’s an example of using the elastic metaspace in Java 17:

java -XX:MetaspaceSize=64m -XX:MaxMetaspaceSize=128m MyApplication

In this example, the metaspace size is set to 64 MB with a maximum size of 128 MB. The elastic metaspace will dynamically adjust its size based on the needs of the MyApplication program, freeing unused class metadata and acquiring more memory from the operating system as needed.

JEP 387 improves the performance and stability of the JVM by making the metaspace more scalable and efficient. This makes it possible to run larger and more complex applications with a smaller memory footprint and reduces the risk of OutOfMemoryError exceptions.