EP126：你不可错过的终极 Kafka 101_AI阅读总结 — 包阅AI

This week’s system design refresher:

• How the Internet Works in 9 Minutes (Youtube video)

• AWS Services Cheat Sheet

• The Ultimate Kafka 101 You Cannot Miss

• 8 Tips for Efficient API Design

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AWS grew from an in-house project to the market leader in cloud services, offering so many different services that even experts can find it a lot to take in.

The platform not only caters to foundational cloud needs but also stays at the forefront of emerging technologies such as machine learning and IoT, establishing itself as a bedrock for cutting-edge innovation. AWS continuously refines its array of services, ensuring advanced capabilities for security, scalability, and operational efficiency are available.

For those navigating the complex array of options, this AWS Services Guide is a helpful visual aid.

It simplifies the exploration of AWS’s expansive landscape, making it accessible for users to identify and leverage the right tools for their cloud-based endeavors.

Over to you: What improvements would you like to see in AWS services based on your usage?

If you’re not a paid subscriber, here’s what you missed.

1. A Crash Course on Scaling the API Layer

2. A Crash Course on Architectural Scalability

3. A Crash Course on Microservices Design Patterns

4. A Crash Course on Domain-Driven Design

5. “Tidying” Code

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Kafka is super-popular but can be overwhelming in the beginning.

Here are 8 simple steps that can help you understand the fundamentals of Kafka.

1. What is Kafka?
   Kafka is a distributed event store and a streaming platform. It began as an internal project at LinkedIn and now powers some of the largest data pipelines in the world in orgs like Netflix, Uber, etc.

2. Kafka Messages
   Message is the basic unit of data in Kafka. It’s like a record in a table consisting of headers, key, and value.

3. Kafka Topics and Partitions
   Every message goes to a particular Topic. Think of the topic as a folder on your computer. Topics also have multiple partitions.

4. Advantages of Kafka
   Kafka can handle multiple producers and consumers, while providing disk-based data retention and high scalability.

5. Kafka Producer
   Producers in Kafka create new messages, batch them, and send them to a Kafka topic. They also take care of balancing messages across different partitions.

6. Kafka Consumer
   Kafka consumers work together as a consumer group to read messages from the broker.

7. Kafka Cluster
   A Kafka cluster consists of several brokers where each partition is replicated across multiple brokers to ensure high availability and redundancy.

8. Use Cases of Kafka
   Kafka can be used for log analysis, data streaming, change data capture, and system monitoring.

Over to you: What else would you add to get a better understanding of Kafka?

• Domain Model Driven
  When designing the path structure of a RESTful API, we can refer to the domain model.

• Choose Proper HTTP Methods
  Defining a few basic HTTP Methods can simplify the API design. For example, PATCH can often be a problem for teams.

• Implement Idempotence Properly
  Designing for idempotence in advance can improve the robustness of an API. GET method is idempotent, but POST needs to be designed properly to be idempotent.

• Choose Proper HTTP Status Codes
  Define a limited number of HTTP status codes to use to simplify application development.

• Versioning
  Designing the version number for the API in advance can simplify upgrade work.

• Semantic Paths
  Using semantic paths makes APIs easier to understand, so that users can find the correct APIs in the documentation.

• Batch Processing
  Use batch/bulk as a keyword and place it at the end of the path.

• Query Language
  Designing a set of query rules makes the API more flexible. For example, pagination, sorting, filtering etc.

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