Application Architecture

Webhooks

Pros:

1. Real-Time Updates: Webhooks provide real-time data and updates, making them ideal for applications that require immediate notification of events.

2. Efficiency: Instead of constantly polling an API for changes, webhooks push changes as they happen, reducing unnecessary network traffic and computational resources.

3. Simplicity: Webhooks are conceptually simple and easy to implement. They are essentially just HTTP callbacks.

4. Flexibility: Webhooks can be used to trigger a wide variety of actions and workflows, making them a flexible tool for integrating different services.

Cons:

1. Security: Webhooks can pose a security risk if not properly secured. They can be exploited to execute unauthorized commands or leak sensitive information.

2. Error Handling: If a webhook fails to deliver, there’s often no built-in mechanism for retrying the failed delivery. This means you need to build robust error handling and potentially a system for retrying failed deliveries.

3. Scaling: Webhooks can be difficult to scale. If your application needs to handle a large number of webhook events, it can put a significant load on your server.

4. Debugging: Debugging webhook issues can be challenging. Since webhooks involve requests coming from a third-party service, it can be difficult to trace and debug issues.

5. Dependency: Your application becomes dependent on the third-party service’s availability. If the third-party service goes down, your application won’t receive webhook events.

Macro Service Architecture

Macro service architecture, also known as monolithic architecture, is a software design pattern where all components of an application are interconnected and interdependent. In this architecture, the software is written as one cohesive unit of code. Its components are tightly coupled and run as a single service.

• Single Codebase: All the application’s functionalities reside in a single codebase which is deployed as a single artifact.
• Tightly Coupled Components: Components of the application are tightly coupled. A change in one component might require changes in other components.
• Scalability: Scaling a monolithic application can be challenging as it requires scaling the entire application rather than individual components.
• Development: As the application grows, the codebase can become more complex and harder to understand, making development and maintenance more difficult.
• Deployment: Since everything is tightly coupled, a small change in the code requires the entire application to be redeployed.
• Technology Stack: Monolithic applications typically use a single technology stack (e.g., Java, .NET, Node.js, etc.).
• While monolithic (macro service) architecture has its drawbacks, it’s not always a bad choice. For small applications, a monolithic architecture can be simpler to develop, test, and deploy. It’s also easier to manage as everything is in one place. However, for larger, more complex applications, a microservice architecture might be a better choice as it allows for more flexibility, scalability, and resilience.

7 fallacies of distributed computing

These fallacies are common misconceptions that can lead to design flaws in distributed systems. It’s important to understand and consider these fallacies when designing a distributed system.

1. The network is reliable: This fallacy assumes that there will never be any network issues, such as dropped packets, latency, or outages. In reality, network issues are common and should be planned for in the system design.

2. Latency is zero: This fallacy assumes that there is no delay in sending or receiving data over the network. In reality, latency can vary greatly and can significantly impact system performance.

3. Bandwidth is infinite: This fallacy assumes that the network can handle as much data as necessary. In reality, bandwidth is limited and can become a bottleneck in system performance.

4. The network is secure: This fallacy assumes that the network is safe from security breaches. In reality, security should be a major concern in any distributed system.

5. Topology doesn’t change: This fallacy assumes that the network layout, or topology, does not change. In reality, the network topology can change frequently, and the system should be designed to handle these changes.

6. There is one administrator: This fallacy assumes that there is a single authority managing the entire system. In reality, a distributed system often spans multiple administrative domains.

7. Transport cost is zero: This fallacy assumes that there is no cost to send data over the network. In reality, there are costs associated with data transmission, such as the time it takes to serialize and deserialize data, and the monetary cost of the network infrastructure.