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client server in a distributed file system
Distributed Systems

Network file system – A deep dive

A network file system is a distributed file system protocol; an open protocol that specifies message formats regarding how a client and a server should communicate in a distributed environment.  NFS being an open protocol enables third parties to write their own implementations of it….

tired of learning new technology
Career & Learning

The Technology Upskill Mess For Application Developers

It’s been a few years since Oliver kicked off his career, as a full-stack Java developer, in this BigCorp. Inc. He learned quite a bit, primarily working on the backend: writing features, plumbing APIs, debugging code, fixing bugs, DENTTAL (Documentation, Exception Handling, Null pointers, Time complexity, Test coverage, Analysis of code…

Low code
Software Engineering

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…

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.

Read more about it here

facebook haystack photo storage min 1


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.