How to choose the right cloud provider for your application – A thorough guide
In the present startup and enterprise landscape cloud deployments is a norm. If you want to scale seamlessly, you need to be on the cloud either on public or on-prem. There are numerous reasons why a business would want to deploy its services on the…
How many developers do I need for my startup/app – A deep dive
In this write-up, we will have an in-depth discussion on how many developers we really need for our startup or to build an app. Is it just one, a couple or more than a couple? Finding out the optimum number of developers to work on…
Designing A Video Search Service with AWS – AWS Cloud Computing Architecture
Hello there, how are you doing? Welcome to the system design & architecture series of scaleyourapp.com In this write-up, we will be designing A Scalable Video Search Service with AWS Amazon Web Services Platform. So, without any further ado. Let’s have a look at the…
A Super Helpful Guide to Avoiding Cloud Vendor Lock-In When Running Your Service on Cloud
Hello there, how is it going?Welcome to scaleyourapp.com This article is a comprehensive write-up on the techniques & best practices to avoid cloud vendor lock-in when building & deploying our services on the cloud. Vendor lock-in is something which gets unavoidable, especially when using a…
LinkedIn Real-Time Architecture: How Does LinkedIn Identify Its Users Online?
This write-up is an insight into LinkedIn’s Real-Time Platform Architecture. I talk about how does LinkedIn identify its users online? How does it know when a user on its platform is online or has gone offline? How does it show the online status of our…
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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