工作台用户界面延迟问题调查

With special thanks to our stunning colleagues Amer Ather, Itay Dafna, Luca Pozzi, Matheus Leão, and Ye Ji.

特别感谢我们出色的同事 Amer Ather，Itay Dafna，Luca Pozzi，Matheus Leão 和 Ye Ji。

Overview

概述

At Netflix, the Analytics and Developer Experience organization, part of the Data Platform, offers a product called Workbench. Workbench is a remote development workspace based on Titus that allows data practitioners to work with big data and machine learning use cases at scale. A common use case for Workbench is running JupyterLab Notebooks.

在Netflix，分析和开发者体验组织是数据平台的一部分，提供一个名为Workbench的产品。Workbench是一个基于Titus的远程开发工作空间，允许数据从业者在大规模数据和机器学习用例中工作。Workbench的一个常见用例是运行JupyterLab Notebooks。

Recently, several users reported that their JupyterLab UI becomes slow and unresponsive when running certain notebooks. This document details the intriguing process of debugging this issue, all the way from the UI down to the Linux kernel.

最近，有几位用户报告说，他们在运行某些笔记本时，JupyterLab UI变得缓慢且无响应。本文详细介绍了从UI到Linux内核调试此问题的有趣过程。

Symptom

症状

Machine Learning engineer Luca Pozzi reported to our Data Platform team that their JupyterLab UI on their workbench becomes slow and unresponsive when running some of their Notebooks. Restarting the ipykernel process, which runs the Notebook, might temporarily alleviate the problem, but the frustration persists as more notebooks are run.

机器学习工程师 Luca Pozzi 向我们的数据平台团队报告说，他们的 JupyterLab UI 在工作台上运行某些笔记本时变得缓慢且无响应。 重启运行笔记本的 ipykernel 进程可能会暂时缓解问题，但随着更多笔记本的运行，挫败感依然存在。

Quantify the Slowness

量化缓慢

While we observed the issue firsthand, the term “UI being slow” is subjective and difficult to measure. To investigate this issue, we needed a quantitative analysis of the slowness.

虽然我们亲眼观察到了这个问题，但“UI 变慢”这个术语是主观的，难以衡量。为了调查这个问题，我们需要对这种缓慢进行定量分析。

Itay Dafna devised an effective and simple method to quantify the UI slowness. Specifically, we opened a terminal via JupyterLab and held down a key (e.g., “j”) for 15 seconds while running the user’s notebook. The input to stdin is sent to the backe...