Question 1

What is caching and why is it important in a backend application?

Accepted Answer

Caching is the practice of temporarily storing frequently accessed data in a fast storage layer to avoid recalculating or retrieving it from a slower source.

In a backend application, the cache typically sits between the application and the database. Instead of making an expensive database query every time, we first check if the data is in the cache. If it is, that is a cache hit and we return the data directly. If not, that is a cache miss and we query the database, then store the result in the cache.

The importance of caching is multifaceted.

First, latency reduction. In-memory cach

Question 2

Explain the Cache-Aside pattern and how you implement it.

Accepted Answer

The Cache-Aside pattern, also called Lazy Loading, is the most common caching strategy. The application manages the interactions between the cache and the database itself.

The read flow works as follows. First, the application receives a request for data. Second, it checks if the data exists in the cache. Third, if it exists, that is a cache hit, and we return the data directly. Fourth, if it does not exist, that is a cache miss, and we query the database. Fifth, we store the result in the cache with a TTL, time to live. Sixth, we return the data.

For writes, the application updates the

Question 3

What is a message queue and why would you use it in a backend architecture?

Accepted Answer

A message queue is an infrastructure component that allows applications to communicate asynchronously by exchanging messages through an intermediate queue.

The principle is simple. A producer sends a message to the queue. The message is stored until a consumer retrieves and processes it. The producer does not wait for a response, it continues execution immediately after sending.

The advantages of using a message queue are numerous.

First, decoupling. The producer and consumer do not know each other directly. They communicate through the queue. You can modify, update, or replace one wi

Question 4

What is the difference between the point-to-point pattern and the publish-subscribe pattern?

Accepted Answer

Point-to-point and publish-subscribe are two fundamental messaging communication patterns.

In the point-to-point pattern, a message is consumed by exactly one consumer. The producer sends a message to a queue. Multiple consumers can listen to this queue, but each message is only processed by one of them. This is the classic queue model.

This pattern is ideal for task distribution. For example, a job queue where multiple workers each take one job. Each e-commerce order should only be processed once, even if multiple workers are available.

In the publish-subscribe pattern, or pub/sub, a

Question 5

What are microservices, and how do they differ from traditional monolithic architecture?

Accepted Answer

Microservices are an architectural approach where an application is built as a collection of small, independent services. Each service focuses on a specific business capability and runs in its own process.

Unlike monolithic architecture, where all functionality lives in a single codebase and deployment unit, microservices offer key differences.

First, regarding independence. Each microservice can be developed, deployed, and scaled independently. Teams can work on different services without affecting others.

Second, concerning technology diversity. Different services can use different

Question 6

What is service discovery in microservices, and why is it necessary?

Accepted Answer

Service discovery is a mechanism that allows microservices to find and communicate with each other dynamically, without hardcoding network locations.

In a microservices environment, services are constantly starting, stopping, and moving across servers. IP addresses and ports change frequently, especially in containerized or cloud environments. Hardcoding these locations would be impractical and fragile.

Service discovery solves this through a service registry, a central database where services register themselves when they start and deregister when they stop.

There are two main patter

Question 7

What is the difference between horizontal scaling and vertical scaling?

Accepted Answer

Horizontal and vertical scaling are two approaches to increasing a system's capacity to handle more load.

Vertical scaling, also called scaling up, means adding more power to an existing machine. You might upgrade the CPU, add more RAM, or use faster storage. It is like replacing a small car engine with a bigger one.

The advantages of vertical scaling include simplicity. There is no need to change your application architecture. A single powerful server is easier to manage than multiple servers. It works well for applications that are difficult to distribute.

The disadvantages include

Question 8

What is load balancing, and what are common load balancing algorithms?

Accepted Answer

Load balancing distributes incoming network traffic across multiple servers to ensure no single server becomes overwhelmed. It improves reliability, availability, and response times by spreading the workload evenly.

A load balancer sits between clients and servers, receiving all incoming requests and forwarding them to available backend servers based on certain algorithms.

Common load balancing algorithms include several approaches.

Round robin is the simplest method. Requests are distributed sequentially to each server in turn. Server one gets the first request, server two gets the s

Question 9

What is the difference between latency and throughput, and how do they relate to system performance?

Accepted Answer

Latency and throughput are two fundamental metrics for measuring system performance, but they measure different things.

Latency is the time it takes for a single request to complete, from when it is sent until the response is received. It is measured in time units like milliseconds. Low latency means fast individual responses. For example, if a database query takes fifty milliseconds, that is the query latency.

Throughput is the number of requests a system can handle per unit of time. It is measured in requests per second, transactions per second, or similar units. High throughput means

Question 10

How do database indexes improve query performance, and what are the trade-offs?

Accepted Answer

Database indexes are data structures that improve the speed of data retrieval operations. They work similarly to an index in a book, allowing the database to find specific rows without scanning the entire table.

Without an index, the database performs a full table scan, examining every row to find matches. For a table with one million rows, this means reading one million rows even if only one matches. With an appropriate index, the database can locate the matching rows directly, often examining only a handful of entries.

Most databases use B-tree indexes by default. These maintain data i

Backend Developer

Topics

Caching Strategies

Message Queues

Microservices

System Design

Performance & Scalability

Mock Interview

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