How We Improved DNS Record Build Speed By More Than 4,000x

- Alex Fattouche tl;dr: "Our network now spans over 270 cities in over 100 countries, interconnecting with more than 10,000 networks globally. According to w3 stats, “Cloudflare is used as a DNS server provider by 15.3% of all the websites.” This means we have an enormous responsibility to serve DNS in the fastest and most reliable way possible."

featured in #383

In-Depth: ClickHouse vs PostgreSQL

- Mathew Pregasen tl;dr: "Most companies that invest in an online analytical processing (OLAP) database like ClickHouse originally used an online transaction processing (OLTP) stack like MySQL or Postgres." Despite the two being built for different purposes, most companies leverage features in both during their scaling period. The author compares the two technologies here. 

featured in #372

I/O Is No Longer The Bottleneck

- Ben Hoyt tl;dr: "When interviewing programmers, I often ask them to code a simple program to count word frequencies in a text file. It’s a good problem that tests a bunch of skills, and with some follow-up questions, allows you to go surprisingly deep. One of the follow-up questions I ask is, “What’s the performance bottleneck in your program?” Most people say something like “reading from the input file”." Ben discusses why that's not usually the case.

featured in #370

Making A Go Program 42% Faster With A One Character Change

- Harry Marr tl;dr: "If you read the title and thought “well, you were probably just doing something silly beforehand”, you’re right! But what is programming if not an exercise in making silly mistakes? Tracking down silly mistakes is where all the fun is to be had! I’ll also state the usual benchmarking caveat up front: the 42% speedup was measured while running the program on my data on my computer, so take that number with a big old pinch of salt."

featured in #369

Seeing Through Hardware Counters: A Journey To Threefold Performance Increase

- Vadim Filanovsky Harshad Sane tl;dr: "There is, however, a class of problems that requires an even stronger level of magnification going deeper down the stack to introspect CPU microarchitecture. In this blogpost we describe one such problem and the tools we used to solve it."

featured in #368

Where Exactly Does Python 3.11 Get Its ~25% Speedup?

- Beshr Kayali tl;dr: "Python 3.11 was released a few days ago and as usual, it comes with more than a few new features that make it ever more interesting, from exception groups and fine-grained error locations and tracebacks to TOML parsing support in the standard library and of course the much awaited speedup as part of the faster CPython project. CPython 3.11 is 25% faster than CPython 3.10 on average according to benchmarks with pyperformance."

featured in #367

Prioritizing App Stability - Mobile Performance @ Lyft

- Wen Zhao tl;dr: We focused our investment in mobile performance into the 3 metrics with the highest opportunity for improvement: (1) Time to interact: continuing reducing app startup time. (2) Stability: reducing the number of crashes any given user experiences. (3) Rendering performance: maintaining a high, buttery smooth frame rate. 

featured in #358

Why Your Website Should Be Under 14B In Size 

tl;dr: "Having a smaller website makes it load faster — that's not surprising. What is surprising is that a 14kB page can load much faster than a 15kB page — maybe 612ms faster — while the difference between a 15kB and a ;16kB page is trivial. This is because of the TCP slow start algorithm. This article will cover what that is, how it works, and why you should care. But first we'll quickly go over some of the basics."

featured in #346

Python 3.11 Is Up To 10 - 60% Faster Than Python 3.10

tl;dr: "CPython 3.11 is on average 25% faster than CPython 3.10 when measured with the pyperformance benchmark suite, and compiled with GCC on Ubuntu Linux. Depending on your workload, the speedup could be up to 10-60% faster. This project focuses on two major areas in Python: faster startup and faster runtime."

featured in #332

The Two Generals Problem

- Seth Archer Brown tl;dr: "Imagine there’s a city in a valley. On either side of the valley, there’s an army commanded by a general. On one side stands General Alice and her army. On the other, General Bob and his army. Alice and Bob want to capture the city, but neither has an army large enough to do so alone. Alice and Bob must attack at the same time, but Alice and Bob can only communicate by sending messengers through the valley, who have a chance of being captured by the city’s army. How do Alice and Bob coordinate their attack?"

featured in #319