Today, in order to help you ace your job interview, I want to provide you a technical overview of several key systems design interview topics. Interviews for systems design may not be primarily focused on coding skills. It's not so much about showcasing your ability to churn out code but rather your proficiency in building fragments of a cohesive system. This aspect of the interview is particularly important for senior engineering positions.
During a typical software engineering interview, you might encounter two sessions, one behavioral interview, and a systems design interview. For senior candidates, the stakes are higher, sometimes requiring two systems design interviews. My own experience highlighted how these interviews are often not constrained to a particular language or paradigm. But there is an emphasis on the importance of understanding frameworks, APIs, design patterns, and their integration in system architecture. Scalability and wise design choices are key aspects.
To streamline your preparation, let's look into several key concepts that you should be familiar with for your systems design interview.
Load Balancing
Load balancers play a role in distributing traffic across multiple web servers, enhancing throughput, latency, and scalability. Instead of overburdening a single server, a load balancer intelligently routes client requests to several web servers based on predefined rules.
There are various load balancing techniques worth noting. For instance, using specialized software like Nginx enables routing of HTTP requests to different IP addresses or host machines capable of serving those requests. Another technique I like is DNS load balancing, which involves having a website's URL resolve to multiple IP addresses. This approach is straightforward, requiring no additional machines, though it offers limited customization.
Load balancing can be implemented through several strategies, such as round-robin distribution, hash-based distribution focusing on the IP address, or based on the current load of the servers, directing traffic to the least burdened machine. Identifying offline machines and rerouting traffic is another crucial function of load balancers.
Caching
The concept of caching emerges as a solution to the frequent bottleneck caused by database servers under heavy load. Often, databases are taxed by numerous reads and writes, particularly with complex SQL queries. A classic example is the homepage of a major news website, which, while consistent for all users on any given day, requires frequent database queries.
Inserting a caching layer can significantly reduce the strain on the database by storing the results of frequent queries in memory. This makes data retrieval exceedingly fast, as it avoids disk access altogether. Common caching systems include memcache, Redis, and Cassandra, all of which are used in production environments across the tech industry. For instance, Facebook extensively utilizes memcache.
CDN (Content Delivery Network)
Beyond caching dynamic content, CDNs are helpful in caching static assets such as images, JavaScript, HTML, and CSS files. By caching this content on a global network of servers, CDNs reduce the load on primary servers and expedite content delivery to users worldwide.
The speed at which content is delivered can significantly enhance user experience. CDNs are strategically located to serve users efficiently across the globe. Setting up a CDN can involve using a pull technique, where content is initially slow to access as it's fetched and cached. But the subsequent accesses are very fast. Alternatively, a push technique involves actively storing files on the CDN, ensuring faster access at the cost of higher upfront storage.
Database Design and Indexing
In a systems design interview, you may be asked to design a database schema, including tables, primary keys, and indexes. Database indexes are integral for speeding up queries. For instance, a compound index sorted by latitude, longitude, and last active date can optimize queries for a dating app, allowing quick searches within a user's vicinity.
Indexes aren't limited to compound structures; they can be as varied as the application's needs. Additional indexes on attributes like 'last active' can provide a global view of user activity, enhancing the app's responsiveness and user experience.
Replication
Dealing with the limitations of database performance, especially under heavy load, requires strategies like replication. For example, in a slave-master setup, a master database handles all write operations, which are then replicated across multiple slave databases designated solely for read operations.
This configuration helps balance the load by distributing read requests among several slaves, thereby reducing the strain on the master database. While there might be a slight delay in data replication, this is often acceptable in scenarios where immediate consistency is not critical. It's essential to understand that consistency, in database terms, means that any read operation following a write returns the updated value. In some cases, reading from the master database or a consistently updated cache can ensure data accuracy.
Database Writes and Sharding
One of the most challenging aspects of scaling a web application is managing database writes, particularly for applications with high write volumes, like Twitter. Database sharding presents a solution by partitioning the database into multiple masters, each responsible for a subset of the data.
Sharding can be vertical - distributing tables across different machines - or horizontal - splitting a single table across multiple machines. In horizontal sharding, a common approach is to use the user ID to determine the target database by applying a modulo operation on the total number of available machines.
NoSQL Databases
The advent of NoSQL databases has introduced a paradigm shift in handling data that doesn't fit well in traditional relational database models. NoSQL databases, characterized by their key-value pair structure, excel in scalability and flexibility, making them ideal for certain types of applications. So if you haven't yet acquired an understanding of them and some experience working with them, you definitely should.
Common NoSQL databases include MongoDB, DynamoDB, and Firebase Firestore. Their key-value nature allows for effortless scaling across multiple machines. These databases are particularly suited for applications with less complex query requirements but need to scale horizontally, such as chat systems or real-time analytics. You can also use them in combination with relational databases.
API Design
Another crucial component of systems design interviews is API design, which involves defining the communication protocols between the client and server. It is highly unlikely that you will not be asked about it during the interview. API design interview questions often touch on determining the functions, methods, data transport mechanisms (such as JSON or protocol buffers), security measures, and support for offline usage. The goal is to demonstrate that you are capable of ensuring fast, secure, and efficient communication that caters to the specific needs of an application.
So, it's essential to ask clarifying questions during the interview to understand the specific requirements and challenges of the system you're designing. Remember, simplicity is key; avoid premature optimizations and focus on building a system that is easy to understand and maintain.
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