Rebuilding Netflix Video Processing Pipeline with Microservices
Infrastructure
How Meta built the infrastructure for Threads
How to arrange GitHub actions to improve feedback cycles | LeanIX Engineering
Visibility of System Status - Pencil & Paper
How Apple built iCloud to store billions of databases
Databases are the endgame for data-oriented design
ServerFree Architecture - subZero Blog
A deep dive into CPU requests and limits in Kubernetes | Datadog
10 insights on real world container usage | Datadog
How GitLab's Red Team automates C2 testing
Let's talk about joins | Crystal Lewis
Slashing Data Transfer Costs in AWS by 99%
Why decentralization matters
Simplifying Complexity: The Journey from WebSockets to HTTP Streams
The Architecture of DoorDash's Caching System
How to Build a Scalable Notification Service
How CloudFlare Processes a Million Logs per Second
How Lyft Processes Terabytes of Real Time Data
How Discord Modernized MFA with WebAuthn
Unbloating the buffers | Dan Groshev
How to design resilient and large scale data systems
Whenever you’re building a data system, there’s a million things to consider. Gone are the days of just shoving everything into MongoDB and calling it “web scale.” In this newsletter, we’ll be going over the considerations you should be thinking about when building out large scale data systems.
Meta reveals their serverless platform processing trillions of function calls a day
XFaaS is Meta's private platform for "Hyperscale and Low Cost Serverless Functions." It is more efficient than AWS Lambda, Azure Functions, and Google Cloud Functions.
How Discord Serves 15-Million Users on One Server
4 Strategies for Migrating Monolithic Apps to Microservices
Real-time Messaging - Slack Engineering
The Scary Thing About Automating Deploys - Slack Engineering
Slack's Migration to a Cellular Architecture - Slack Engineering
The package that broke NPM (accidentally) - uncenter.dev
Native mobile apps are optional for B2B startups in 2024
The Big Cloud Exit FAQ