System Design 101: Understanding Caching

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In our last episode, we discussed Load Balancing-the ability of a system to distribute traffic evenly across servers to avoid overload. We used Flutterwave and MTN Mobile Money as examples to explain how load balancing ensures systems stay fast and reliable during peak traffic.

Now, let’s dive into Caching-a concept that helps systems retrieve data quickly by storing frequently accessed information in a fast-access storage layer.

What is Caching?

Imagine you’re a chef in a busy restaurant. Every time a customer orders a popular dish, you have to go to the market to buy the ingredients. That would take forever, right? Instead, you keep the most-used ingredients in your kitchen for quick access. That’s caching in action.

Caching is about storing copies of frequently accessed data in a fast-access storage layer (like memory) so that future requests for that data can be served faster. It’s like keeping your most-used ingredients close at hand to save time.

Why is Caching Important?

Let’s take a real-life example: YouTube, one of the most popular video platforms in the world. YouTube serves billions of videos every day. Imagine if every time you clicked on a video, YouTube had to fetch it from a remote server. The video would take forever to load, and users would get frustrated.

For platforms like YouTube and Twitter, caching is critical because:

• It reduces the time it takes to retrieve data.

• It decreases the load on databases and servers.

• It improves the overall user experience by making the system faster.

How Do Businesses Use Caching?

Here are a few simple strategies businesses use to implement caching:

1. In-Memory Caching: Storing data in memory (like Redis or Memcached) for lightning-fast access. For example, Twitter might cache tweets and user profiles in memory so they can be retrieved instantly.

2. Content Delivery Networks (CDNs): Storing static content (like images and videos) on servers closer to users. For example, YouTube uses a CDN to cache videos, so they load quickly for users across the globe.

3. Browser Caching: Storing static resources (like CSS and JavaScript files) on the user’s device so they don’t have to be downloaded repeatedly.

4. Database Query Caching: Storing the results of frequently run database queries so they don’t have to be recomputed.

Real-Life Example: YouTube

Let’s look at YouTube. When you click on a video, it starts playing almost instantly. How does YouTube achieve this?

• It uses a CDN to cache videos on servers closer to users, reducing load times.

• It caches thumbnails and metadata in memory, so they can be retrieved quickly.

• It ensures that even during peak usage, videos load seamlessly.

This level of caching is why YouTube can provide a fast and smooth streaming experience.

Real-Life Example: Twitter

Now, let’s consider Twitter. When you scroll through your timeline, tweets load instantly. How does Twitter achieve this?

• It caches frequently accessed data, like tweets and user profiles, in memory.

• It uses database query caching to store the results of common queries, reducing the load on the database.

• It ensures that even during high traffic, users can access their timelines quickly.

This caching is why Twitter remains fast and responsive, even during major global events.

Caching is the secret to making systems faster and more efficient. Whether it’s YouTube streaming videos instantly or Twitter loading tweets in a flash, caching ensures users get the information they need without delays.

In the next episode of our System Design series, we’ll dive into Database Sharding—what it means to split a database into smaller, more manageable pieces to improve performance. Stay tuned!

Until then, think about this: How would you feel if your favorite app took forever to load every time you used it? That’s why caching matters.