Infrastructure

Learn how Mintlify built and scaled their multi-tenant docs platform with custom domains

Learn how we approached migrating our Wafris v1 client based on Redis to a new faster, easier to use SQLite architecture.

Read how we’re scaling PostgreSQL at the petabyte scale to power our query monitoring feature, Insights.

Everything you need to quickly get prepared for FAANG system design interviews. Written by former Meta and Amazon interviewers, this guide breaks down the core concepts, patterns, frameworks, and technologies needed to ace your system design interviews. It also breaks down some of the most commonly asked system design questions and provides detailed answers.

Distributed Tracing is scary and complicated... right?

A simple solution that only relies on the tools you already have

At our organization, Redis plays a crucial role in various capacities — as shared memory, for attack detection based on concentrated…

Templates and checklists are helpful tools, but they only work if you dive deep to understand the problem. Here’s how:

Coupling is integration's magic word

Focus on security

Golden rules to answer in System Design Interviews.

S3 is more weirder than you think. Make sure you know all the quirks before they turn into vulnerabilities in your AWS infrastructure.

Caches help reduce latency, scale read-heavy workloads, and save cost. They are literally everywhere. Caches run on your phone and in your browser. For example, CDNs and DNS are essentially geo-rep…

Introduction The OpenTelemetry ecosystem has grown significantly busier compared to a...

REST APIs everywhere!

The CAP Theorem is an important concept in distributed database systems that helps architects and designers understand the trade offs while…

Explanation of this topic starts with an analogy, taking an example from real life to understand the concept better.

#1 System Design - Scalability

Sahil: Hi Sourajit! Let’s play something.

#51: Break Into Saga Design Pattern (4 Minutes)

Enterprise applications often have a hefty and complex code base, mission-critical functionality, and a constant influx of feature demands that can result in a slower pace of dependency updates and a tendency to lag behind. This situation can worsen over time, as certain high-profile dependencies become outdated or discontinued, preventing the update of interlocked dependencies and leading to a cascade of technological stagnation. Eventually, this can reach a critical point, requiring big bang migrations to break free from the constraints of problematic legacy technologies.

In this blog, we go on an interactive journey to understand common queueing strategies for handling HTTP requests.

In this blog post we’ll share an overview of Stripe’s database infrastructure and discuss the design and application of the Data Movement Platform.

Assortment of technology startup infrastructure recommendations

#47: Break Into Live Streaming Architecture (6 minutes)

A closer look at Figma’s custom PostgreSQL sharding solution with motivations and future predictions.