Better Dev Link

Alfred Menezes, a professor in the Department of Combinatorics and Optimization, Faculty of Mathematics, at the University of Waterloo in Canada. His research field is cryptography. He has made quite a few of his lecture available for free, both of slide, video, exercises and handout.

Engineer no doubt encounters the term entropy quite a bit when it come to randomess. But what is it? how to define it? This is the draft to a book about that exact topic. And here is the introduction post by author.

WebAssembly, or WASM for short, is a new technology for running portable programs in a safe and efficient manner primarily aimed at the web platform. Similarly to ASM.js, WASM aims at a low level-of abstraction suitable as an intermediate representation of a higher-level program — i.e. WebAssembly code is intended to be generated by compilers rather than being written by humans. T

Developers tend to treat tracing as deep magic, and OpenTelemetry is no exception. OpenTelemetry may be even more mysterious given how many concepts your are exposed to even with beginning examples. They are likely a lot simpler than you expect! Once you peel back the layers, I find a useful mental model of tracing looks like “fancy logging” combined with “context propagation” a.k.a “passing some IDs around”. The examples are JS code but the concept can be applied to your favorite language SDK given OpenTelemetry popularity.

If you always confuse with ssh remote port, local port forwarding this visualization might help.

On Mastodon, an opensource platform that is similar to Twitter. People can define custom emoji. The op library call emoji-picker-element is used to render the picker. It’s choke with 19k emoji. How can we improve performance here to render a bunch of emojis as fast as possible.

Your database is configured for the needs of your day-to-day application activity, but what if you need to run complex analytics queries against your application data? Let’s look at how you can optimise your database for an analytics workload without compromising the performance of your application.

Installing software by piping from curl to bash is obviously a bad idea and a knowledgable user will most likely check the content first. So wouldn’t it be great if a malicious payload would only render when piped to bash? A few people have tried this before by checking for the curl user agent which is by no means fail safe - the user may simply curl the url on the commandline revealing your malicious code. Luckily the behaviour of curl (and wget) changes subtely when piped into bash. This allows an attacker to present two different versions of their script depending on the context :)

Lets learn how to encryption and decrypt with AES. You will learn stuff like AES-CBC or AWS-GCM. It uses Go as the language but the idea can be applied to your favorite langugage.

Replication being slow—replication lag—is a common complaint, but MySQL replication is actually really fast. Let’s run a controlled experiment and peek inside the Performance Schema and binary logs to see why.

In other words, LLM-powered applications are a lot like other modern cloud-native applications: they require excellent support for REST and RPC protocols, concurrency and performance. These just so happen to be the areas where Go excels, making it a fantastic language for writing LLM-powered applications. This blog post works through an example of using Go for a simple LLM-powered application. It starts by describing the problem the demo application is solving, and proceeds by presenting several variants of the application that all accomplish the same task, but use different packages to implement it. All the code for the demos of this post is available online.