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How To Make Performance Visible With GitLab CI And Hoodoo Of GitLab Artifacts

Smashing Magazine

This article will help you with exactly that. The metrics selection is outside of the scope of this article and depends highly on the project context, but I recommend that you start by reading User-centric Performance Metrics by Philip Walton. Now we can use git hook to check the file size against the limit before every commit.

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Frankenstein Migration: Framework-Agnostic Approach (Part 1)

Smashing Magazine

Typically, front-end migration, which is the main subject of this article, does not allow even that: “cheap” is out of reach for any migration , and you have to pick either “good” or “fast.” In particular, those running through CI/CD every time you push things into master (that might take very long) and helps to save time on feature releases.

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Tools for successful implementation of insprint test automation

Testsigma

The scrum master should take insprint test automation seriously and only mark a story done when its corresponding test cases have been executed and automated. Also, if you’re keen on understanding how to perform regression testing at DevOps speed with Testsigma, we recommend reading this article. Sign up Now. Supports Shift-Left.

Testing 52
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HammerDB Concepts and Architecture

HammerDB

HammerDB is open source and all of the source code is available at the sourceforge Git development site here [link] or the github mirror here [link]. This Git repository is updated with every release. In fact all of this source code is also included in readable form with each and every release. Virtual Users.

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Data pipeline asset management with Dataflow

The Netflix TechBlog

The answers to these questions is something we would like to address in this article and propose a clean solution to this problem. Later in the article we’ll cover this referencing system in some detail. Or what if Alice wanted to add new backup functionality and she accidentally broke existing code while updating it?

Storage 201
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MLOps and DevOps: Why Data Makes It Different

O'Reilly

In this article, we want to dig deeper into the fundamentals of machine learning as an engineering discipline and outline answers to key questions: Why does ML need special treatment in the first place? ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

DevOps 138
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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

In this article, I will share the current architecture and some of the lessons we learned scaling it along with some of the things we are looking to improve upon in the near future. We use a variant of git-flow, for every ticket, we clone the repo and we run automation tests on every merge request. Master/slave? Confluence.