Thoughts on a personal journey into the world of developer advocacy at an open-source data project.

lakeFS the Project

> git checkout -b my-amazing-branch

Rid yourself of these troubling habits and start the journey towards data lake mastery

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Anti-Pattern #1

You click around the S3 (or comparable) storage console often

What can we learn from high performers in other disciplines?

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You have a burning passion inside you.

“The emotions you are feeling at this very moment are a gift, a guideline, a support system, a call to action. If you suppress your emotions and try to drive them out of your life… you’re squandering one of life’s most precious resources” — Tony Robbins, Awaken the Giant Within

Keeping the flame alive

If you’re as sick of this three-letter phrase as I am, you’ll be happy to know there is another way.

Take a Look Around You…

Can you consider yourself a great developer if you aren’t producing quality code?

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You want to work with great code

But I don’t have time to write beautiful code…

Learning why the Webster’s Director of Analytics doesn’t immediately fix problems, but takes the time to understand them first.

They say to not wait for a promotion.

Efficient debugging in AWS is something you must constantly strive for.

Setting the Scene

Setting up the Problem

If you agree that “the faintest ink is more powerful than the strongest memory” then you should know how to cheaply spin up your own homegrown transcription service.

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AWS released a new feature last week to export a full Dynamo table with a few clicks, but it’s also worth knowing how to hydrate a table with data at any scale.

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Knowing when and how to deploy this simple and versatile tool can be an extremely powerful option in data system design.

Friday Afternoon

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Paul Singman

DevRel @lakeFS. Ex-ML Engineering Lead @Equinox. Whisperer of data and productivity wisdom. Standing on the shoulders of giants.

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