To better understand the concept of application dependency mapping, the ideal approach is to explore a real-world example of a distributed system architecture deployed on Amazon Web Services (AWS).

The following example system consists of several components, each playing a crucial role in the overall functionality and performance of the application.

Public Web and Mobile Clients

The system includes public web and mobile clients, which serve as the primary user interface for accessing the application. These clients interact with the system's backend services through well-defined APIs, ensuring a seamless user experience across different devices and platforms.

Private Internal Core API

At the heart of the system lies a private internal core API, which acts as the central hub for processing requests and orchestrating interactions between various components. This API is responsible for handling business logic, data validation, and communication with other services within the architecture.

Analytics Server and Data Management

To gain insights into system performance and user behavior, the architecture includes a private, in-house analytics server for logs and metrics analysis. This server collects and processes data from various sources, enabling the team to make data-driven decisions and optimize the application.

Additionally, the system relies on Snowflake for efficient data management, storage, and retrieval.

Caching and Message Queuing

To improve performance and reduce latency, the system incorporates caching mechanisms using Redis. This allows frequently accessed data to be stored in memory, minimizing the need for expensive database queries.

Furthermore, the architecture utilizes Kafka for communication between system components, enabling reliable, real-time message queuing and event-driven processing.

Security and Access Control

To ensure the security of the system and protect sensitive data, all services are hidden behind proxies and gateways. These components act as a secure interface for clients to access the network, while preventing unauthorized access to internal services. This multi-layered approach to security helps maintain the integrity and confidentiality of the system.

Conclusion

By creating a visual representation of this system architecture using application dependency mapping, the team can clearly identify the relationships and dependencies between each component. This high-level overview serves as a valuable reference for both technical and non-technical stakeholders, facilitating effective communication and decision-making.

For instance, when assessing the potential for data loss in the analytics service, the dependency map reveals that the core service pushes data to both Kafka and Amazon S3. By understanding the service-level availability guarantees of these components, the team can make informed decisions regarding data retention policies, backup strategies, and risk mitigation measures.

What's Next

This is just a brief overview and it doesn't include many important aspects of Application Dependency Mapping such as:

• System discovery techniques
• The role of architecture diagrams
• Application dependency mapping best practices

If you are interested in a deep dive in the above concepts, visit the original:Application Dependency Mapping: Tutorial & Best Practices