Source: cloudplatform.googleblog.com

Background

Streaming data processing, while providing benefits such as freshness and smoother resource consumption compared to their batch counterpart, has historically been associated with disadvantages like being unreliable and having approximate results. Those disadvantages, however, are not inherent characteristics of streaming data processing itself, but rather artifacts of how they have previously been implemented. As shown by Google Cloud Dataflow and the Apache Beam movement in recent years, streaming processing can be just as robust as batch processing. In this blog post, we’ll discuss how to make streaming data processing robust. …


Source: vectorified.com

Motivating Examples

Let’s say you have a distributed cache service hosted on multiple servers. Each server is responsible for a partition of the keyspace. You will want your requests to land on the right servers. Or maybe you want to track the IP addresses of mobile users, and you want to scale out to multiple servers. When users need to initiate direct connections with each other, they will query your service for peers’ IP addresses. Your service needs to locate the appropriate server for the information. Or maybe your service wants to establish some “sticky” ephemeral session for a user…


Source: developers.google.com

Background

Search, in its most basic form, can be implemented as a plain inverted index. See Figure-1 for an illustration. We build the index as we add/delete/update documents, and use it during search to go from a search term to the documents that contain it. That’s all good. But if you’re more ambitious than building a simplistic lookup by keyword system, read on. This blog post is a gentle introduction to the core ideas behind some of the advanced search functions. By the way, you may recognize that a lot of the ideas here are based on the lucene index.


Source: Facebook Symbols

Background

String encoding is probably not something you’ll get asked directly in a system design interview. But it may come up as a side question. Let’s say you want to send a long string over the network and print it out piece by piece on the other end. The interviewer may ask if there is anything you need to watch out for when the character set is not ASCII. The answer is yes. For example, you can’t arbitrarily segment the byte array because a character may be encoded in multiple bytes. …


Prologue

Let me state upfront, this is not an easy system design interview question. If you don’t have a good understanding of distributed systems, you may not even know where to start. It’s no doubt difficult. But unless you’re in a domain specific interview, chances are that the interviewer probably just wants to test your ability of navigating complex system design problems. So I’m hoping to present exactly that — working through this question bit by bit and see how far we’d get. In the end, we’ll not only arrive at some solutions, but also practice problem solving in the…


Designing a replicated and strongly consistent key-value store, which sounds seemingly simple, is actually quite a tricky interview question. You’d need to have a good understanding of some of the distributed systems concepts to be able to answer this question well. If you’re not in a domain specific interview, for this kind of questions, chances are that the interviewer just wants to observe how well you can navigate through a complex design problem. In that case, the discussion itself is usually more important than the final solution. So rather than just giving you the straight answer, I think it’d be…


Cover Image

I quite often ran into system design discussions in which people seemed to have the tendency to use Kafka as a magic box, as if drawing out that horizontal cylinder would just magically make problems go away. It may. After all, “80% of all fortune 100 trust and use Kafka” [1]. It’s such a versatile tool that I think we should give it the credit. Personally, I like it very much as well.

When it comes to a system design interview however, I think we should do better than the superficial name dropping. Knowing a specific product is good. But…


Photo by Samuel Hinton on cosmiccoding.com.au

Background

The top k frequent elements question is a classic coding interview question. Viewing through the lens of system design interview however, it suddenly has a special appeal. But before we start our usual system design interview discussion, let’s quickly talk about how it’s solved in the coding interview context, which will facilitate the design discussion that follows.

In the coding interview context, the question is often posed as given an array of elements, find k elements of the highest frequency. We first go through the array and count each element’s frequency, creating a distribution map.

distribution := map<element, int>{}…


Test your system design abilities before the next interview

Diagram explaining cloud monitoring
Diagram explaining cloud monitoring
Photo from Google Cloud.

I read this system design interview question online and wanted to write about it. When I initially tried to answer this question, I embarrassingly didn’t have a good way to structure my thoughts. I had a couple of ideas floating around, but I didn’t know where to start. I later realized that it was probably because server monitoring was so prevalent in modern web development that I had been taking it for granted. So I seemed to know a good deal about it, but I couldn’t really connect the dots. …


Source: nginx.com

Background

Nginx is an open source web server that can be used as a reserve proxy, load balancer, HTTP cache, and mail proxy. It’s capable of supporting a high number of concurrent connections, which is one of its flagship features. The Nginx website has a blog post [1] that explains the event driven architecture behind its stellar scalability. While that’s an excellent deep dive, hardcore engineers may still feel unsatisfied because we’re always looking for a level of understanding that involves actual code.

Nginx’s source code, albeit openly available, is challenging to read because of its humongous size and slim comments…

Eileen Pangu

Eng @ FANG. Enthusiastic tech generalist. Enjoy distilling wisdom from experiences. Believe in that learning is a lifelong journey.

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