**REGISTER HERE TO GET THE STREAMING LINK AND RECORDING:**
https://www.eventbrite.com/e/scaling-ai-pipelines-to-the-next-level-with-flyte-union-tickets-1323728620939?utm-campaign=social&utm-content=attendeeshare&utm-medium=discovery&utm-term=listing&utm-source=cp&aff=ebdsshcopyurl

### **What you’ll learn & do:**

**Scale Workflows Effortlessly**
Discover how to **expand compute clusters** across clouds and reuse containerized tasks to slash latency and resource waste. *Live Demo*: Configure multi-cluster Flyte deployments and workload placement to balance cost, performance, and reliability.
**Master Parallelism with MapTasks (and Beyond)**
Learn when to use Flyte’s MapTasks for high-fan-out workflows. We’ll explore their power (low overhead, programmatic iteration) *and* their limits (Kubernetes metadata bottlenecks).
*Live demo*: Optimize a real-world workflow using MapTasks, then push it to its breaking point to see where Kubernetes struggles.
**Break Through Kubernetes Limits with Union**
Go beyond Flyte’s native capabilities with **Union**, a control plane that eliminates Kubernetes bottlenecks. See how it:
**Auto-offloads metadata** to blob storage when K8s etcd is overwhelmed.
**Orchestrates multi-cloud clusters** seamlessly, with execution placement you control.
Introduces **Actors**: reusable, hot containers that bypass Pod startup delays for rapid iteration.
*Deep Dive*: Refactor a failing MapTask into a Union-powered workflow using Actors and cross-cluster mapping.

### **About Union.ai**

Union is the developer suite powering compound AI systems. We make building AI
fast, easy, and scalable.

### **Stay Connected**

💬 Join our AI & MLOps Slack: [https://slack.flyte.org/](https://slack.flyte.org/ "https://slack.flyte.org/")
⭐ Explore Flyte on GitHub: [https://github.com/flyteorg/flyte](https://github.com/flyteorg/flyte "https://github.com/flyteorg/flyte")
🌐 Learn more: [https://union.ai/](https://union.ai/ "https://union.ai/")

Building AI Together - Seattle

David Espejo

Lada Kesseler

Farida Mishra

Boyd Thomson

Scaling AI pipelines to the next level with Flyte & Union

Online event

**May's book is "Hands-On APIs for AI and Data Science"!**

This is a casual-style event. Not a structured presentation on topics. Sometimes, the discussion even drifts away from the chapters, but feel free to grab the mic to help steer it back.

Feel free to join the discussion even if you have not read the book chapters! :)

Want to discuss the contents during the reading week? Join the Slack Flyte MLOps Slack group and search for the "ai-reading-club" channel. [https://slack.flyte.org/](https://slack.flyte.org/)

\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-
About the book:
Title: [Hands-On APIs for AI and Data Science](https://learning.oreilly.com/library/view/hands-on-apis-for/9781098164409/)
Authors: Ryan Day
Published: March 2025
[Hands-On APIs for AI and Data Science](https://learning.oreilly.com/library/view/hands-on-apis-for/9781098164409/)

Chapters:

* I. Building APIs for Data Science
1\. Creating APIs That Data Scientists Will Love
2\. Selecting Your API Architecture
3\. Creating Your Database
4\. Developing the FastAPI Code
5\. Documenting Your API
6\. Deploying Your API to the Cloud
7\. Batteries Included: Creating a Python SDK
II. Using APIs in Your Data Science Project
8\. What Data Scientists Should Know About APIs
9\. Using APIs for Data Analytics
10\. Using APIs in Data Pipelines
11\. Using APIs in Streamlit Data Apps
III. Using APIs with Artificial Intelligence
12\. Using APIs with Artificial Intelligence
13\. Deploying a Machine Learning API
14\. Using APIs with LangChain
15\. Using ChatGPT to Call Your API

**Book Description:**
Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data science success, because they are used in a variety of ways in these fields. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit.
As you complete the chapters in the book, you'll be creating portfolio projects that teach you how to:

* Design APIs that data scientists and AIs love
* Develop APIs using Python and FastAPI
* Deploy APIs using multiple cloud providers
* Create data science projects such as visualizations and models using APIs as a data source
* Access APIs using generative AI and LLMs

Learn more about the book here:
https://learning.oreilly.com/library/view/hands-on-apis-for/9781098164409/

Sage Elliott

Sheikh Muthiah

Shreya

AI Book Club: Hands-On APIs for AI and Data Science

Union

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