🏭 Production Grade API Development - Part 2

Learn about production grade API development. This is the second of two sessions.

Target Audience

This session is suitable for:

• Cloud/Infra Engineers
• Data Analysts
• Data Engineers
• Data Scientists
• Machine Learning Engineers
• Software Development Engineers
• University students with an interest in Data Engineering, Software Development

What Will Be Covered

In this session, you will,

• Learn more about the alternatives to RESTful APIs.
• Learn about authentication using JWT, and gain experience implementing it.
• Gain knowledge and experience implementing and testing Rate Limiting.
• Learn about profiling Python code.

What This Session Will Not Cover

This session builds upon the material covered during part 1 of this series of sessions. There will be a brief recap of the material covered during part 1.

The topics indicated with a ❌ will not be covered, whereas topics with a 👉 will be covered in subsequent parts in this series of sessions or other sessions.

• ❌ Deploying and managing containerized applications with Kubernetes
• ❌ Details of Kubernetes architecture
• ❌ Get an overview of popular frameworks used to develop RESTful APIs (refer to Part 1)
• ❌ Learn how to write unit tests (refer to Part 1)
• ❌ Get an overview of Pydantic and how it can help with API development (refer to Part 1)
• ❌ Learn about various ways to deploy your API on to the cloud (refer to Part 1)
• 👉 Learn about APIs for machine learning (ML) models (refer to ML Model Deployment 101)

Frequently Asked Questions

A few frequently asked questions regarding what will be covered during this session.

• What are RESTful APIs? RESTful APIs allows different servers to securely exchange information over the internet. ‘REST’ is an acronym for Representational State Transfer. REST is a software architecture that defines how applications communicate with each other over the internet using resources, representations, and HTTP methods.
• What is JWT? JWT (acronym for JSON Web Token) is a standard used to securely transmit information between two parties. It contains encoded JSON objects, including a set of claims, and is signed using a cryptographic algorithm to ensure that the claims cannot be altered after the token is issued.
• What is Pydantic? Pydantic is a Python library for data modelling/parsing and validation. It has efficient error handling and a custom validation mechanism.

Upcoming Sessions

Please note:

• All times above are expressed in SGT. Click on the 🌏 icon next to sessions of interest to get your location’s corresponding date and time.
• For reference, 8 PM SGT is 5:30 PM (Bangalore), 7 PM (Jakarta), 5 PM (Lahore)

Other Dates & Times

👋 I am interested but don’t see a date or time that works for me.

You can indicate your preferred date & time when you register.

What’s Next?

What should I learn after attending this session?

• 🎖️ Minimum Python Expected - if you feel the need to become better at Python programming
• 🛠️ Deploy ML Models On The Cloud

Tracks

This session covers content that is part of the following tracks:

• Become Better At Python Programming
• Data Engineering
• ML Engineering

Full List

• Check out the complete list of upcoming sessions.
• Alternatively, if you are a hands-on creator, check out the upcoming Hands-On Learning Sessions.

Further Reading

1. What is a REST API? (Oct, 2020) 🎥 9m 11s
2. JWT Explained - in 2 minutes (May, 2022) 🎥 2m 14s