知鸦日报2023-09-07

作为58自研的一站式性能测试平台，麒麟旨在帮助业务线便捷地完成性能测试，精准评估服务性能和容量等，从而提升服务的稳定性和可靠性。

本篇文章，主要是介绍了内存的分配的工作，以及其他的额外的特性；对内存管理有一定程度的认识；里面的内存释放，涉及到的操作细节非常多，例如内存合并操作；以及内存真正释放的时机；更多细节还是需要通过源码了解。

就在 Chrome 115 版本，浏览器开始了对 scheduler.yield 的灰度测试。scheduler.yield 是 scheduler API 中新增的一个功能，它能以更简单、更好的方式将控制权交还给主线程。在开始讲解这个 API 之前，我们先来看一个新的性能指标。

本文主要指出 @Builder 存在的一些问题，指出它并不是链式编程的最佳实践。

一直想开发一个自己的短信过滤 APP，但是一直没有具体实施，现在终于静下心来，边开发边记录下整体的开发过程。

How Dropbox re-wrote its core web serving stack for the next decade—sunsetting technical debt accrued over 13 years, and migrating high-traffic surfaces to a future-proofed platform ready for the company’s multi-product evolution.

Dropbox is well known for storing users’ files—but it’s equally important we can retrieve content quickly when our users need it most. For the Retrieval Experiences team, that means building a search experience that is as fast, simple, and powerful as possible. But when we conducted a research study in July 2022, one of the most common complaints was that search was still too slow. If search was faster, these users said, they would be more likely to use Dropbox on a regular basis.

Like many companies, Dropbox has been experimenting with large language models (LLMs) as a potential backend for product and research initiatives. As interest in leveraging LLMs has increased in recent months, the Dropbox Security team has been advising on measures to harden internal Dropbox infrastructure for secure usage in accordance with our AI principles. In particular, we’ve been working to mitigate abuse of potential LLM-powered products and features via user-controlled input.

Injection attacks that manipulate inputs used in LLM queries have been one such focus for Dropbox security engineers. For example, an adversary who is able to modify server-side data can then manipulate the model’s responses to a user query. In another attack path, an abusive user may try to infer information about the application’s instructions in order to circumvent server-side prompt controls for unrestricted access to the underlying model.

As part of this work, we recently observed some unusual behavior with two popular large language models from OpenAI, in which control characters (like backspace) are interpreted as tokens. This can lead to situations where user-controlled input can circumvent system instructions designed to constrain the question and information context. In extreme cases, the models will also hallucinate or respond with an answer to a completely different question.

When was the last time you were about to click a button on a website, only to have the page shift—causing you to click the wrong button instead? Or the last time you rage-quit a page that took too long to load?

These problems are only amplified in applications as rich and interactive as ours. The more front-end code is written to support more complex features, the more bytes are sent to the browser to be parsed and executed, and the worse performance can get.

At Dropbox, we understand how incredibly annoying such experiences can be. Over the past year, our web performance engineering team narrowed some of our performance problems down to an oft-overlooked culprit: the module bundler.

At Twitter, our on premise data centers contain hundreds of thousands of hardware servers and millions of server hardware components.

Twitter aims to deliver you the best of what’s happening in the world right now. This requires a recommendation algorithm to distill the roughly 500 million Tweets posted daily down to a handful of top Tweets that ultimately show up on your device’s For You timeline. This blog is an introduction to how the algorithm selects Tweets for your timeline.

Our recommendation system is composed of many interconnected services and jobs, which we will detail in this post. While there are many areas of the app where Tweets are recommended—Search, Explore, Ads—this post will focus on the home timeline’s For You feed.

本文主要讲述了一些对于k8s多集群管理的思考，包括为什么需要多集群、多集群的优势以及现有的一些基于Kubernetes衍生出的多集群管理架构实践。

REDck 通过云原生架构升级，能够处理万亿级数据规模，实现秒级 OLAP 查询，支持分钟级自动故障恢复、弹性扩缩容能力，成本优化效果显著。

AB实验平台这几年在互联网公司得到了越来越广泛的应用，采用AB实验来评估产品和技术迭代效果也成为主流的业务新功能效果评估方式，数据驱动的文化在这几年得到了不少公司的广泛的认同，通过数据和指标来说明产品效果也得到了越来越多的公司的认可和应用。

本文中我们介绍百度基于eBPF实现的网络框架：DeeTune，包含构建服务拓扑、流量录制、无侵入指标监控等能力。

本文介绍了Hologres RoaringBitmap的功能。

在AIGC市场发展的趋势下，如何帮助设计工作者解放双手。本文将从图像生成方向切入，帮助大家体系化的学习Stable diffusion的使用，完成自有IP的训练以及生成，主要从部署、训练、生成3大核心进行系统性的讲解。