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An educational side project

The Pragmatic Engineer

I’d like to share a story about an educational side project which could prove fruitful for a software engineer who’s seeking a new job. Juraj included system monitoring parts which monitor the server’s capacity he runs the app on: The monitoring page on the Rides app And it doesn’t end here.

Education 363
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Zenlytic Is Building You A Better Coworker With AI Agents

Data Engineering Podcast

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Are data agents harder to build?

Building 278
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Build faster with Buck2: Our open source build system

Engineering at Meta

Buck2, our new open source, large-scale build system , is now available on GitHub. Buck2 is an extensible and performant build system written in Rust and designed to make your build experience faster and more efficient. In our internal tests at Meta, we observed that Buck2 completed builds 2x as fast as Buck1.

Building 145
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A Tour Around Buck2, Meta's New Build System

Tweag

Buck2 is a from-scratch rewrite of Buck , a polyglot, monorepo build system that was developed and used at Meta (Facebook), and shares a few similarities with Bazel. As you may know, the Scalable Builds Group at Tweag has a strong interest in such scalable build systems. Bazel recording steps: 1.

Systems 141
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Building cost effective data pipelines with Python & DuckDB

Start Data Engineering

Project demo 3. Building efficient data pipelines with DuckDB 4.1. Distributed systems are scalable, resilient to failures, & designed for high availability 4.5. Introduction 2. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3.

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Build Better Tests For Your dbt Projects With Datafold And data-diff

Data Engineering Podcast

Summary Data engineering is all about building workflows, pipelines, systems, and interfaces to provide stable and reliable data. Datafold has invested a lot of time into integrating with the workflow of dbt projects to add early verification that the changes you are making are correct. freshness, time to delivery, etc.)

Project 130
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Data Migration Strategies For Large Scale Systems

Data Engineering Podcast

Summary Any software system that survives long enough will require some form of migration or evolution. When that system is responsible for the data layer the process becomes more challenging. Sriram Panyam has been involved in several projects that required migration of large volumes of data in high traffic environments.

Systems 130