知鸦日报2024-09-11

状态机（State Machine）是一种数学模型，用于描述系统状态以及在这些状态之间的流转和动作等行为。

Luhn算法，（鲁恩/卢恩算法 ）也被称作“模10算法”（Mod 10）。是由IBM科学家Hans Peter Luhn发明的一种简单的校验和计算算法。主要用来计算信用卡、银行卡、社保卡号、会员卡号、设备IMEI、部分手机ICCID等号码的合法性。

In our system, we use the term “treatment” to refer to the core unit of a full IFTTT data structure. A treatment is an amalgamation of three key elements - an event, conditions (which are optional), and actions. For example, consider a promotional campaign that offers “100 GrabPoints for completing a ride paid with GrabPay Credit”. This campaign can be transformed into a treatment in which the event is “ride completion”, the condition is “payment made using GrabPay Credit”, and the action is “awarding 100 GrabPoints”.

Data generated across various Kafka streams by multiple services within Grab forms the crux of events and conditions for a treatment. Trident processes these Kafka streams, treating each data object as an event for the treatments. It evaluates the set conditions against the data received from these events. If all conditions are met, Trident then executes the actions.

A deep dive into the streaming aspect of the Lambda architecture framework of Riverbed.

Learn how Uber is streamlining the Cloud migration of its massive Data Lake by incorporating key Data Mesh principles.

The Compute and Performance Engineering teams at Netflix regularly investigate performance issues in our multi-tenant environment. The first step is determining whether the problem originates from the application or the underlying infrastructure. One issue that often complicates this process is the "noisy neighbor" problem. On Titus, our multi-tenant compute platform, a "noisy neighbor" refers to a container or system service that heavily utilizes the server's resources, causing performance degradation in adjacent containers. We usually focus on CPU utilization because it is our workloads’ most frequent source of noisy neighbor issues.

Detecting the effects of noisy neighbors is complex. Traditional performance analysis tools such as perf can introduce significant overhead, risking further performance degradation. Additionally, these tools are typically deployed after the fact, which is too late for effective investigation. Another challenge is that debugging noisy neighbor issues requires significant low-level expertise and specialized tooling. In this blog post, we'll reveal how we leveraged eBPF to achieve continuous, low-overhead instrumentation of the Linux scheduler, enabling effective self-serve monitoring of noisy neighbor issues. You’ll learn how Linux kernel instrumentation can improve your infrastructure observability with deeper insights and enhanced monitoring.

Pushy is Netflix’s WebSocket server that maintains persistent WebSocket connections with devices running the Netflix application. This allows data to be sent to the device from backend services on demand, without the need for continually polling requests from the device. Over the last few years, Pushy has seen tremendous growth, evolving from its role as a best-effort message delivery service to be an integral part of the Netflix ecosystem. This post describes how we’ve grown and scaled Pushy to meet its new and future needs, as it handles hundreds of millions of concurrent WebSocket connections, delivers hundreds of thousands of messages per second, and maintains a steady 99.999% message delivery reliability rate.

本文将带读者了解RAG技术，并以知识问答为例帮助读者快速搭建一套属于自己RAG。

有句话叫做互联网技术中的银弹，加一层解决各种问题。我们在微服务架构设计的时候会碰到分层，数据仓库设计的时候也有分层，协议设计的的时候也有分层，大部分的设计模式也是多加一层抽象。这些所有的分层都有什么共同点，分层的优缺点是什么，分层的原则是什么。我们经常拿到各种眼花缭乱的分层概念，在实践中又感觉无法完全套上去。

本文详细阐述了如何通过二级缓存架构设计提升高并发下的系统性能。

I was curious about how a component was implemented in a minified JavaScript file and used ChatGPT to reverse engineer the component.

本文将尝试在ComfyUI中使用Flux.1进行生产，实现图生图、区域重绘的工作流。

实践发现就算不使用提示词和ControlNet，Flux.1在重绘时会”很容易“保持原图的姿态并且不容易生成杂乱的手指，而在指定生成英文字母时几乎能做到完全跟随。