Using ChatGPT to Help Author a Blog Post on Event-Driven Architecture

Yesterday I posted about "What's All The Hype About Prompt Engineering About ?" and I got a few questions in my DMs. I thought I'd provide a more real-life example. So I created a blog post on something I had expertise in, Event-Driven Architecture. I wanted to have a good level of expertise in the topic so I could judge the quality of the post and its accuracy.

Here's an example of the prompt I used for Chat GPT this is verbatim what I put into the ChatGPT Playground.

Write a blog post in a professional tone about how Event-Driven Architecture is a growing part of cloud computing.

1. Include key technologies from various cloud computing that are using event-driven architecture.

2. List top open source projects that help build event-driven architecture

3. List the top uses cases for Event-driven architecture

4. Provide a list of user cases that are not ideal for Event-Driven Architecture

5. Summarize the blog post with a call to action on the best places to look for opportunities to upgrade legacy systems to a more modern Event-Driven architecture

This is the blog post that I got from that prompt. It's actually pretty good and since the technology has been talked about for the last few years the model had pretty decent and relevant information around it. (Remember the model is the knowledge base that an AI draws from). Though I wouldn't say it's a finished blog post it's a good start.

Event-Driven Architecture (EDA) is becoming an increasingly popular approach to designing and building scalable, responsive, and resilient cloud computing systems. In an EDA, services and components communicate with each other asynchronously via events, rather than through synchronous request/response interactions. This allows for a more decoupled, flexible, and distributed system, where services can react to and process events in real-time, and where components can scale independently based on the volume and complexity of the events they handle.

In this blog post, we'll explore the growing trend of Event-Driven Architecture in cloud computing, the key technologies that are using it, the top open source projects that help build it, and the top use cases for it.

Key technologies using Event-Driven Architecture in cloud computing

Many cloud computing platforms and services are now built on an Event-Driven Architecture, such as:

AWS Lambda: AWS Lambda is a serverless computing platform that uses an Event-Driven Architecture to execute functions in response to events, such as HTTP requests, database changes, or file uploads.

Apache Kafka: Apache Kafka is an open-source distributed streaming platform that uses an Event-Driven Architecture to process streams of records in real-time, with high throughput and fault tolerance.

Azure Event Grid: Azure Event Grid is a fully-managed event routing service that uses an Event-Driven Architecture to route events from any source to any destination, with low latency and high reliability.

Google Cloud Pub/Sub: Google Cloud Pub/Sub is a fully-managed messaging service that uses an Event-Driven Architecture to deliver messages between independent applications and services, with global scalability and durability.

Top open source projects for building Event-Driven Architecture

There are many open source projects that help build an Event-Driven Architecture, such as:

Apache Flink: Apache Flink is an open-source distributed stream processing framework that supports real-time processing of data streams, with low-latency and high-throughput.

Apache Beam: Apache Beam is an open-source unified programming model for batch and streaming data processing, that can run on various execution engines such as Apache Flink, Apache Spark, and Google Cloud Dataflow.

RabbitMQ: RabbitMQ is an open-source message broker that supports multiple messaging protocols, such as AMQP, MQTT, and STOMP, and that can be used to implement a wide range of messaging patterns, such as publish/subscribe, request/reply, and point-to-point.

Top use cases for Event-Driven Architecture

Event-Driven Architecture is particularly useful for the following use cases:

Real-time data processing and analytics: EDA can be used to process and analyze large volumes of data in real-time, such as IoT sensor data, financial market data, or social media streams, and to trigger actions or notifications based on the analysis results.

Microservices architecture: EDA can be used to implement a microservices architecture, where each service is responsible for a specific business capability and communicates with other services via events, without knowing their implementation details.

Serverless computing: EDA can be used to implement serverless computing, where functions are triggered by events and run on-demand, without the need for managing servers or infrastructure.

User cases that are not ideal for Event-Driven Architecture

EDA may not be the best fit for the following use cases:

Request/response interactions: EDA is not well-suited for request/response interactions, where a client expects a synchronous response from a service, since events are asynchronous and decoupled.

Transactional consistency: EDA is not well-suited for maintaining transactional consistency across multiple services, since events may be lost or duplicated.

Simple and linear workflows: EDA may add unnecessary complexity to simple and linear workflows, where a series of steps

So I took another shot with my prompt to see if I could make some changes. Some formatting (e.g. use the Oxford comma) and provide a summary in a paragraph, not a bulleted list. Also, I asked that they include TriggerMesh (a company I co-founded) as one of the technologies.

Here's the updated blog post which was markedly better. Including more flowing prose than the original blog post. Though for sure it'd need to be edited but it provided a very logical and decently well-written blog post.

Event-Driven Architecture (EDA) is quickly becoming a crucial part of cloud computing. With its ability to handle large amounts of data in real-time, it has become a popular choice for many businesses. In this blog post, we will explore the key technologies from various cloud computing platforms that are using EDA and highlight the top open-source projects that can help build event-driven architecture.

Key Technologies from Cloud Computing Platforms

AWS Lambda, Azure Functions, and Google Cloud Functions are some of the popular serverless computing technologies that support EDA. TriggerMesh is another technology that has been gaining traction, as it allows developers to build event-driven applications using serverless computing functions.

Top Open-Source Projects for Event-Driven Architecture

Apache Kafka, RabbitMQ, and NATS are some of the most widely used open-source messaging systems that support event-driven architecture. They provide scalable and reliable messaging services that can handle millions of messages per second, making them ideal for real-time applications.

Top Use Cases for Event-Driven Architecture

Real-time analytics: EDA can be used to process large amounts of data in real-time, allowing businesses to make informed decisions quickly.

IoT Applications: EDA can be used to connect and manage devices in real-time, making it ideal for building IoT applications.

Microservices Architecture: EDA can be used to build a scalable and fault-tolerant microservices architecture that can handle large volumes of requests.

Real-time Fraud Detection: EDA can be used to detect fraudulent transactions in real-time, minimizing losses for businesses.

User Cases Not Ideal for Event-Driven Architecture

Batch Processing: EDA is not ideal for batch processing as it is designed for real-time data processing.

Applications with High Latency: EDA may not be suitable for applications that require low latency as it involves processing and transmitting data over a network.

In conclusion, Event-Driven Architecture is an important part of cloud computing that enables real-time data processing and analysis. Apache Kafka, RabbitMQ, NATS, and TriggerMesh are some of the technologies that support EDA. While EDA is ideal for real-time analytics, IoT applications, microservices architecture, and real-time fraud detection, it may not be suitable for batch processing and applications with high latency. For businesses looking to upgrade their legacy systems to EDA, they should consider looking at cloud providers that support EDA, or leveraging open-source projects such as Apache Kafka or NATS.

Now, this final article was much better but it still had some things I'd tweak as it provides a good overview but not a tone of detail. A lot of it works with the narrative I wanted to create and the tone isn't necessarily my tone but it's good. If I was going to publish this, I'd probably want to hyperlink to appropriate resources and maybe come up with some good stats to support this. I'd also play with the formatting and use headings to break up the text. But all of that could be done in a few minutes. Hope this helps someone trying to leverage AI. Also, I think there's an ethical dilemma of whether you credit ChatGPT for helping you or not. I think that it's probably fine not to credit if you are editing and fact-checking but if not I think you could look bad and not serve your reader by leaving it to its own devices.