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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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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
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Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

Data Engineering Podcast

Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. Decodable was built with a mission of eliminating all of the painful aspects of developing and deploying stream processing systems for engineering teams. How can you get the best results for your use case?

Process 182
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X-Ray Vision For Your Flink Stream Processing With Datorios

Data Engineering Podcast

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. How have the requirements of generative AI shifted the demand for streaming data systems? Can you describe how Datorios is implemented?

Process 147
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Designing Data Transfer Systems That Scale

Data Engineering Podcast

Summary The first step of data pipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. When is DoubleCloud Data Transfer the wrong choice?

Systems 130
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Pushing The Limits Of Scalability And User Experience For Data Processing WIth Jignesh Patel

Data Engineering Podcast

Summary Data processing technologies have dramatically improved in their sophistication and raw throughput. What are the experimental methods that you are using to gain understanding in the opportunities and practical limits of those systems? If you've learned something or tried out a project from the show then tell us about it!

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Supporting Diverse ML Systems at Netflix

Netflix Tech

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.

Systems 95