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🍔🧠 How Uber Drives 40M Reads/Sec with Integrated Cache

PLUS: Scaling ChatGPT challenges 🛠️, 1 Dev Platform to level-up 🔥, and Hands-On RL 🎮

Author

Alex Zajac
February 26th, 2024

Happy Monday! ☀️

Welcome to the 323 new hungry minds who have joined us since last Monday!
If you aren’t subscribed yet, join smart, curious, and hungry folks by subscribing here.

🍔 THIS WEEK’S MENU 🥗

  1. 📚 Uber's integrated cache, level up skills with a dev course, and learn from scaling challenges for ChatGPT.

  2. 🗞️ Google unveils Gemini 1.5, an early preview of Stable Diffusion 3 and Neuralink brain implants.

  3. 👨🏻‍💻 Quick byte: React Query for efficient data fetching and caching.

Reading time: 5 minutes

Food for Thought
A mindset, an example, and an action item to start the week
❝

‘A person who never made a mistake never tried anything new.’

Albert Einstein


Mindset: Mistakes enable growth and innovation. We must embrace them.

Example: Southwest Airlines pioneered low-cost air travel despite early stumbles.

Action item: Propose one new idea at work today.

The Rabbit Hole
Deep dives, trends, and resources curated to stay ahead

How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache

Docstore is Uber’s in-house, distributed database built on top of MySQL®. Storing tens of PBs of data and serving tens of millions of requests/second, it is one of the largest database engines at Uber used by microservices from all business verticals.

A Deep Dive into HTTP and its Evolution

We'll delve into HTTP/1, HTTP/2, and HTTP/3 and talk about the issues each of them solved. We'll end with delving into Facebook and Dropbox's implementation of HTTP/3 and the results they saw.

Scaling ChatGPT: Five Real-World Engineering Challenges

Just one year after its launch, ChatGPT had more than 100M weekly users. To meet this explosive demand, the team at OpenAI had to overcome several scaling challenges. An exclusive deep dive.

LUC #42: Efficiency Over Perfection: The Role of Heuristics in Engineering

Plus, SQL execution order explained, and edge computing vs cloud computing — which is best?

How to select a Design Pattern?

In this issue, we will talk about design patterns, explaining them in a simple language, what kinds of patterns we have, when to use them, and when not, all with source code examples in C#.

Stick to boring architecture for as long as possible.

Don't get lost in the tech; keep your sight fixed on the value created.

Taking Decisions in Engineering Teams

Strategies for Effective Decision-Making in Engineering Environments

💾 SIDE DISHES 💾

GITHUB REPO (google’s magic)
Detect the content types of any file with DL

The Weekly Digest
Software, AI, and startup news worth your time

Brief: Google introduces Gemma 2B and 7B, open-source lightweight AI models for tasks like simple chatbots, aiming to expand AI accessibility and customization beyond its closed Gemini model.

Brief: Startup Groq introduces LPUs - specialized hardware running language models - showcasing up to 500 tokens per second speed, emphasizing efficiency and scalability over GPUs.

Brief: Elon Musk reveals progress as Neuralink's brain chip allows patient to control a cursor by thought, raising ethical concerns on transparency and scientific validity.

Brief: Apple's rumored "Apple Ring" is potentially nearing launch as more reports suggest an imminent entry into the smart ring market, influenced by Samsung's unveiling, amidst forecasts of significant market growth.

Brief: Google launches Gemini 1.5 Pro, an AI model with a significantly expanded context window capacity to enhance information processing and improve task efficiency in AI development.

Brief: Announcing Stable Diffusion 3, an advanced text-to-image model with improved performance, quality, and safety measures, now open for early preview and feedback to enhance AI practices.

The Quick Byte
One coding tip because you’re technical after all

This week’s coding challenge:

Coding Challenge #50 - xargs

This challenge is to build your own version of the Unix command line tool xargs!

This week’s tip:

React Query is a powerful library for fetching, caching, and updating data in React applications, providing a set of hooks for managing server state.

Wen?

  • Automatic Caching and Invalidations: Ideal for reducing the number of requests to the server by caching data and automatically invalidating it when necessary.

    Background Data Fetching: Enhances user experience by fetching data in the background and seamlessly updating the UI without interrupting the user's interactions.

    Synchronization Across Components: Efficient for maintaining consistency across components by ensuring that they all react to the latest data updates.

Why?

  • Improved User Experience: By managing server state, data fetching, caching, and synchronization efficiently, React Query enhances the overall user experience.

    Reduced Boilerplate Code: Minimizes the need for managing loading and error states manually, leading to cleaner and more maintainable code.

    Declarative Data Fetching: Encourages a more declarative approach to data fetching, making the codebase more intuitive and easier to reason about.

Burp-A-Laugh
The most important meal of your day

That’s it for today! ☀️

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Thanks for spending part of your Monday morning with Hungry Minds.
See you in a week — Alex.

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