Monthly Readings 2016

31 Dec 2016 by fleuria

Monthly Readings: 09

TAO: Facebook’s Distributed Data Store for the Social Graph

Building Microservices: Testing

Feature Toggle

Monthly Readings: 10

How we ended up with microservices

Logging v. instrumentation

Advanced Caching: Part 2 - Using Caching Strategies

Increasing Application Performance with HTTP Cache Headers

What design decisions make the GC for Go so much faster?

Monthly Readings: 11

thrift Field Requiredness

Open-source Service Discovery

From Python to Go, and back again


Continuous Deployment at Instagram

Why It Matters: CORS

Strategic Scala Style: Principle of Least Power

What is JBOD — And Why Should You Care?


Monthly Readings: 12

Building Timeline: Scaling up to hold your life story

Facebook News Feed: Social data at scale

ZooKeeper Resilience at Pinterest

Top 5 Docker Logging Methods to Fit Your Container Deployment Strategy

Web Service Efficiency at Instagram with Python

Kubernates: Pods

Monthly Readings: 13 Sep

*Don’t Share Libraries among Microservices:


Canary All the Things

How to deploy software


Monthly Readings #15: November

Druid: A Real-time Analytical Data Store

Error Handling in Node.js

Putting Apache Kafka To Use: A Practical Guide to Building a Stream Data Platform

Making “Push on Green” a Reality

Big Data in Real-Time at Twitter

Monthly Readings #14: Oct

FollowFeed: LinkedIn’s Feed Made Faster and Smarter

Design Decisions For Scaling Your High Traffic Feeds

Etsy Activity Feeds Architecture

What I Wish I Had Known Before Scaling Uber to 1000 Services

Wasting Time TDDing The Wrong Things

There is not Fork: an Abstraction for Efficient, Concurrent, and Concise Data Access


Comparing Redux and Relay

Monthly Readings #16: Dec

Apache Hadoop Goes Realtime at Facebook:


LVS: How virtual server works?:

Ten years of KVM: