Interview Experience at Vrize

Question: what is a microservices architecture from your perspective? 

Mastering Microservices Pattern: Essential Patterns and the Challenges They Solve

Question : Why do you need an object relational mapper when working with databases? Object relational mapper?

An Object-Relational Mapper (ORM) is a code library that provides a way to map object-oriented programming languages to relational databases. The main reasons why you need an ORM when working with databases are:

1. Impedance Mismatch: There is a conceptual mismatch between the object-oriented programming paradigm and the relational database model. Objects are structured hierarchically, have inheritance, and support complex relationships, while relational databases store data in tables with rows and columns. ORMs bridge this gap by allowing developers to work with objects instead of dealing directly with database tables and SQL queries.
2. Abstraction and Portability: ORMs provide an abstraction layer over the database, hiding the complexity of low-level database operations and SQL dialects. This abstraction makes it easier to work with different databases without having to rewrite large portions of data access code. ORMs support multiple database engines, improving code portability and reducing vendor lock-in.
3. Productivity and Maintainability: Writing raw SQL queries and mapping result sets to objects can be tedious, error-prone, and time-consuming, especially for complex data models. ORMs allow developers to work with objects and their relationships, reducing boilerplate code and improving productivity. This also makes the code more maintainable, as the object model is easier to understand and modify compared to complex SQL queries.
4. Database Independence: ORMs provide a database-independent way of working with data, allowing developers to switch between different database engines without having to rewrite the entire data access layer. This flexibility is particularly useful in scenarios where the application needs to support multiple database systems or when migrating from one database to another.
5. Separation of Concerns: By abstracting away the database implementation details, ORMs promote a better separation of concerns between the application logic and the data access layer. Developers can focus on writing business logic using objects, while the ORM handles the translation between objects and database representations.
6. Object Caching and Performance Optimizations: Many ORMs provide built-in caching mechanisms and optimization strategies, such as lazy loading and eager loading, to improve application performance by minimizing unnecessary database queries and optimizing data retrieval.

While ORMs offer several benefits, they also have some potential drawbacks, such as increased complexity, performance overhead, and the risk of over-abstraction. Additionally, ORMs may not always be suitable for extremely complex or performance-critical scenarios, where direct SQL queries and low-level database optimization techniques might be more appropriate.

Overall, ORMs simplify database interaction in object-oriented programming environments, improving developer productivity, code maintainability, and database portability. They are widely used in various application frameworks and development stacks, such as Java (Hibernate, EclipseLink), .NET (Entity Framework), Python (Django ORM, SQLAlchemy), and Ruby (Active Record), among others.

what about in Spring Boot? Have you solved anything in Spring Boot? Like some kind of optimization of the architecture, stripping out any modalities, anything? So, one year like in last organization, we are building, we are trying to build like a microservices architecture. Question number? So, what is a microservices architecture from your perspective? Okay

Question: Could you explain how one would enable communication between multiple microservices in a proof-of-concept project? Specifically, if you were developing three or four services as a hobby and wanted them to interact with each other, how would you achieve this?

Microservices communicate with each other primarily through two main methods: synchronous communication via RESTful APIs and asynchronous communication using message queues¹.

1. Synchronous Communication with RESTful APIs: Microservices communicate directly with each other synchronously using RESTful APIs (Representational State Transfer). This means that one microservice can send a request to another microservice, and the receiving microservice responds to that request¹. For example, if you have a user service and an order service, the order service might make a RESTful API call to the user service to get details about a user.
2. Asynchronous Communication with Message Queues: In some cases, microservices need to communicate asynchronously, meaning they don’t have to wait for an immediate response. This is especially useful in scenarios where services may be running at different speeds or experiencing varying levels of load. When a microservice publishes a message to a message queue, it’s essentially sending a piece of data to a central storage location. This message contains information or instructions that another microservice might need to know about¹. For example, an order service might publish a message to a queue whenever a new order is created, and a notification service might listen to that queue and send a notification whenever it sees a new message.

There are also other methods of communication such as RPC (Remote Procedure Calls) and event streaming². Additionally, a service mesh can provide features like service discovery, load balancing, encryption, and observability, enhancing the reliability and security of microservices communication².

Remember, the choice of communication method depends on your specific use case and requirements. For more detailed steps and code examples, you might want to check out some tutorials or videos¹²³.

Question: How do your frontend and backend application talk to each other? How do they communicate with each other? 

In a typical web application architecture, the frontend (client-side) and backend (server-side) communicate with each other through an HTTP-based protocol, typically over the internet or a local network. Here’s a general overview of how this communication occurs:

1. Client-Server Architecture: The frontend is typically a web application running in a user’s web browser, while the backend is a server-side application running on a remote server or a cluster of servers.
2. HTTP Requests and Responses: When a user interacts with the frontend (e.g., clicking a button, submitting a form), the frontend sends an HTTP request to the backend server. This request contains information such as the requested resource (URL), request method (GET, POST, PUT, DELETE), headers, and optional request body (e.g., form data or JSON payload).
3. Backend Processing: The backend server receives the HTTP request and processes it based on the requested URL and method. This might involve querying a database, executing business logic, or performing other server-side operations.
4. Response from Backend: After processing the request, the backend server sends an HTTP response back to the frontend. This response contains a status code (e.g., 200 OK, 404 Not Found), headers, and an optional response body (e.g., HTML, JSON, or XML data).
5. Frontend Rendering: The frontend receives the HTTP response from the backend and processes it accordingly. For example, if the response contains HTML, the browser will render the HTML content. If the response contains JSON data, the frontend JavaScript code can handle and display the data appropriately.

The communication between the frontend and backend can be facilitated using different techniques and protocols, depending on the application’s requirements and architecture:

• RESTful APIs: In modern web applications, it’s common to use RESTful APIs (Representational State Transfer) to facilitate communication between the frontend and backend. The frontend sends HTTP requests to specific API endpoints on the backend, and the backend responds with JSON or XML data.
• WebSockets: For real-time, bidirectional communication between the frontend and backend, WebSockets can be used. WebSockets establish a persistent connection between the client and server, allowing for efficient data transfer in both directions without the overhead of HTTP requests and responses.
• Server-Sent Events (SSE): SSE is a standard for establishing a one-way communication channel from the server to the client. It allows the server to push data to the client in real-time, without the client having to repeatedly poll the server for updates.
• GraphQL: GraphQL is an open-source data query and manipulation language that provides an alternative to traditional REST APIs. It allows clients to specify the data they need in a single request, reducing over-fetching and under-fetching of data.

The choice of communication method depends on the specific requirements of the application, such as real-time data updates, data transfer efficiency, and the complexity of the data being exchanged.

Regardless of the method used, it’s essential to implement secure communication channels, handle errors and edge cases appropriately, and ensure proper data validation and sanitization on both the frontend and backend to prevent security vulnerabilities and ensure a reliable and robust application.

Question: Why do we use singleton pattern? What is the need for singleton pattern? 

The Singleton pattern is used to ensure that a class has only one instance and provide a global point of access to that instance. The main reasons for using the Singleton pattern are:

1. Control of resource access: Certain resources, such as database connections, file system objects, or configuration settings, are expensive to create or should be shared across the application to ensure consistency. The Singleton pattern allows you to control and limit the number of instances of such resources, preventing unnecessary duplication and potential conflicts.
2. Global access point: The Singleton pattern provides a global access point to an object instance. This can be useful when you need to access the object from various parts of your application without having to pass the object reference around or creating multiple instances unnecessarily.
3. Lazy initialization: The Singleton pattern allows you to implement lazy initialization, where the object instance is created only when it is first accessed. This can improve performance by avoiding the creation of expensive objects until they are actually needed.
4. Controlled access to instance modification: The Singleton pattern can help control and restrict the modification of an object’s state by providing a single point of access to the instance. This can be particularly useful in multi-threaded environments, where you need to ensure thread-safe access to the object.
5. Caching and Logging: Singleton instances can be used for caching data or logging purposes, where a single instance can serve the entire application, ensuring consistency and centralized management.

However, it’s important to note that the Singleton pattern should be used judiciously, as it can introduce several potential issues and trade-offs:

1. Visibility and testability issues: Singleton objects are globally accessible, which can make them harder to test and reason about, especially in large and complex systems.
2. Concurrency issues: If not implemented correctly, Singleton instances can introduce concurrency issues, such as race conditions and thread safety problems, especially in multi-threaded environments.
3. Difficulty in mocking and dependency injection: Singleton objects can be difficult to mock or replace with test doubles, making it harder to write isolated unit tests or use dependency injection frameworks effectively.
4. Tight coupling: Singletons can lead to tight coupling between different parts of the application, making it harder to maintain, extend, or refactor the code.
5. Memory leaks: If not properly managed, Singleton instances can cause memory leaks, especially in long-running applications or when using class loaders dynamically.

In general, the Singleton pattern should be used when you have a genuine need for a single instance of a class throughout your application, and the benefits of using the pattern outweigh the potential drawbacks. It’s often recommended to consider alternative approaches, such as dependency injection or the use of static utility classes, before resorting to the Singleton pattern, especially in modern, modular, and testable software designs.

Question: What is Rest?

REST (Representational State Transfer) is an architectural style for building web services and APIs (Application Programming Interfaces). It is a set of principles and constraints that define how web services should be designed and implemented to facilitate communication between different systems over the internet.

The key principles and characteristics of REST include:

1. Client-Server Architecture: In REST, the client (typically a web browser or mobile app) and the server (the web service) are separated and communicate through a standardized interface, typically using HTTP protocols.
2. Statelessness: REST services are stateless, meaning that each request from the client to the server must contain all the necessary information for the server to understand and process the request. The server does not store any client context between requests.
3. Caching: Responses from the server can be explicitly marked as cacheable or non-cacheable to improve performance and scalability.
4. Uniform Interface: REST services follow a uniform interface between components, ensuring that data transfer between the client and server follows a consistent and predictable pattern. This is achieved through the use of standard HTTP methods (GET, POST, PUT, DELETE) and resource identifiers (URIs).
5. Layered System: REST allows for the use of intermediary layers, such as load balancers or caching servers, without the client or server being aware of their existence.
6. Code on Demand (Optional): REST services can optionally provide executable code or scripts to be executed on the client-side, enabling dynamic functionalities.

In a RESTful web service, resources (data entities) are identified by URIs (Uniform Resource Identifiers), and the client can interact with these resources using HTTP methods:

• GET: Retrieve a resource or collection of resources
• POST: Create a new resource
• PUT: Update an existing resource
• DELETE: Delete an existing resource

REST promotes the use of hypermedia (links between resources) to guide the client through the application’s state transitions, making the API more self-descriptive and easier to navigate.

REST APIs have become widely popular due to their simplicity, scalability, and the ability to leverage the existing HTTP infrastructure. They are commonly used in modern web and mobile applications, as well as in microservices architectures, where different services communicate with each other through RESTful APIs.

However, it’s important to note that while REST provides guidelines and principles, it does not strictly define a specific set of rules or protocols. As a result, different REST APIs may have slight variations in implementation, making it essential to follow best practices and provide clear documentation for consuming and interacting with the API.

What is the difference between a class and an enum?

The main differences between a class and an enum (enumeration) in programming are:

1. Purpose:

• A class is a blueprint or template for creating objects that can have properties (data members) and methods (functions).
• An enum is a special data type that consists of a set of named constants or values.

1. Instantiation:

• A class can have multiple instances (objects) created from it.
• An enum itself is a singleton; you cannot create instances of an enum directly. Instead, you access the predefined constant values within the enum.

1. Data Members:

• A class can have any number of data members (fields, properties) of various types, including primitive types, objects, and even nested classes.
• An enum can have a limited set of value identifiers (constants) that are typically represented as name=value pairs, where the value is an integer (by default, starting from 0) or a custom value.

1. Methods:

• A class can have any number of methods (functions, behaviors) that operate on its data members and perform various operations.
• An enum has a limited set of predefined methods, such as valueOf() and values(), but you can also define custom methods within an enum.

1. Inheritance:

• A class can inherit from another class (single inheritance) or implement multiple interfaces.
• Enums cannot inherit from other enums, but they can implement interfaces.

1. Use Cases:

• Classes are used to create objects that represent real-world entities, data structures, or components of an application.
• Enums are typically used to represent a fixed set of constant values or choices, such as days of the week, months, or predefined application states or modes.

1. Memory Usage:

• Each instance of a class occupies separate memory space.
• Enum constants are shared across the application, and only one instance of each constant value exists in memory, making them memory-efficient for storing a set of constant values.

Here’s a simple example to illustrate the differences:

// Class
class Person {
    private String name;
    private int age;

    // Constructors, getters, setters, and other methods...
}

// Enum
enum Day {
    MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY, SUNDAY;

    public boolean isWeekday() {
        return this != SATURDAY && this != SUNDAY;
    }
}

In this example, Person is a class that can have multiple instances with different names and ages, while Day is an enum that has a fixed set of constant values representing the days of the week. The Day enum also has a custom method isWeekday() to check if the day is a weekday or not.

 Why do you use synchronized key? 

The synchronized keyword in Java is used to control access to a shared resource (such as an object, method, or block of code) by allowing only one thread to execute the synchronized code at a time. The primary reasons for using the synchronized keyword are:

1. Thread Safety: The synchronized keyword ensures thread safety by preventing multiple threads from accessing a shared resource simultaneously, which could lead to race conditions and data inconsistency. By allowing only one thread to execute the synchronized code at a time, it prevents concurrent modifications that could corrupt the data or state of the shared resource.
2. Mutual Exclusion: The synchronized keyword implements mutual exclusion, which means that if one thread is executing a synchronized block or method, all other threads attempting to execute the same synchronized block or method will be blocked until the first thread completes its execution and releases the lock.
3. Critical Section Protection: The code block or method protected by the synchronized keyword is known as a critical section. It ensures that only one thread can execute the critical section at a time, preventing data corruption or race conditions that could occur if multiple threads modified the shared resource concurrently.
4. Visibility Guarantee: In addition to providing thread safety and mutual exclusion, the synchronized keyword also provides a visibility guarantee. It ensures that any changes made to the shared resource by a thread within the synchronized block are visible to other threads after the synchronization lock is released.

Here’s an example that illustrates the use of the synchronized keyword:

public class Counter {
    private int count = 0;

    public synchronized void increment() {
        count++;
    }

    public synchronized void decrement() {
        count--;
    }

    public synchronized int getCount() {
        return count;
    }
}

In this example, the increment(), decrement(), and getCount() methods are declared as synchronized. This ensures that when one thread is executing any of these methods, no other thread can execute them simultaneously. If multiple threads attempt to call these methods concurrently, they will be blocked and executed one at a time, preventing race conditions and ensuring thread safety.

It’s important to note that using the synchronized keyword can impact performance due to the overhead of acquiring and releasing locks, as well as potential thread contention if multiple threads are frequently trying to acquire the same lock. Therefore, it’s recommended to use the synchronized keyword judiciously and only synchronize the critical sections of code that require thread safety.

Additionally, Java provides other synchronization mechanisms, such as ReentrantLock, Semaphore, and atomic classes, which offer more flexibility and advanced features compared to the basic synchronized keyword. These mechanisms are often preferred in more complex concurrent programming scenarios or when fine-grained locking is required for better performance.