Low Code: The Only Article You Will Ever Need
What Is Low Code? Low code tools and platforms, just like no code, offer visual drag and drop builders along with pre-built components and features aiming to build applications fast. Compared with no code, low code tools provide developers access to the code they generate to enable them to customize…
No Code: A Profound Insight For Citizen and Professional Developers
The no code movement is quite picking up steam these days, as you might know. Also, the no code tools, especially the full-stack no code platforms, have come across as a silver bullet, claiming to empower a citizen developer to develop an app like Instagram, at the scale of Instagram in just a few weeks as…
Distributed Systems and Scalability Feed #1 – Heroku Client Rate Throttling, Tail Latency and more
What does 100 million users on a Google service mean? 10 billion requests/day100k requests/second (average)200k requests/second (peak)2 million disk seeks per second (IOPS) How are these served?100 million users need (at peak) 2 million IOPS at 100 IOPS per disk, that’s 20k disk drives at…
Java Full Stack Developer – The Complete Roadmap – Part 2 – Let’s Talk
This write-up is part 2 of the discussion on how to become a full-stack Java developer. If you haven’t read the first part. Here you go – Time to talk about the database component… The resources stated in this article contain affiliate links. That…
Java Full Stack Developer – The Complete Roadmap – Part 1 – Let’s Talk
Hello readers, This write-up takes a deep dive into full-stack Java development. We will have an insight into what it is? What are the job requirements of a full-stack Java developer? How do I become one? What should be the salary expectations of the devs…
Distributed Systems and Scalability Feed
Facebook photo storage architecture
Facebook built Haystack, an object storage system designed for storing photos on a large scale. The platform stores over 260 billion images which amounts to over 20 petabytes of data. One billion new photos are uploaded each week which is approx—60 terabytes of data. At peak, the platform serves over one million images per second.
In the original NAS-based photo storage architecture, Facebook faced throughput and latency issues as the photos and the associated metadata lookups in NAS caused excessive disk operations almost upto ten just for retrieving a single image.
Tail latency in distributed systems
Tail latency is that tiny percentage of responses from a system that are the slowest in comparison to most of the responses. They are often called as the 98th or 99th percentile response times. This may seem insignificant at first but for large applications like LinkedIn, this has noticeable effects. This could mean that for a page having a million views per day 10,000 of those page views would experience the delay. Read how LinkedIn deals with longtail network latencies.
There can be multiple causes of tail latency: increasing load on the system, complex and distributed systems, application bottlenecks, slow network, slow disk access and more. Read more on it.
RobinHood: Tail latency-aware caching
RobinHood is a research caching system for application servers in large distributed systems having diverse backends. The cache system dynamically partitions the cache space between different backend services and continuously optimizes the partition sizes.
Microsoft research has a talk on getting rid of long-tail latencies.
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