In the realm of microservice architecture, numerous challenges persist, encompassing accessibility, acquiring configuration details, effective messaging, and service discovery. Addressing these challenges involves the employment of common solutions known as patterns. These patterns represent established methodologies and strategies designed to tackle these hurdles, ultimately fortifying the microservices architecture.

These patterns serve as tried-and-tested blueprints, offering a structured approach to resolve common obstacles encountered within microservice frameworks. They encapsulate a range of solutions tailored to streamline accessibility, simplify the retrieval of configuration information, optimize messaging frameworks, and enhance the process of service discovery. By adopting these patterns, architects and developers can build robust and resilient architectures, effectively mitigating the hurdles posed by the intricacies of microservices. In this post we will be talking about API Gateway/BFF and External Configuration Store patterns. 

API Gateway/BFF

The API Gateway pattern serves as a singular point of access for client applications to interact with the associated microservices, offering a range of functionalities, including routing, authentication, and load balancing. However, as the architecture scales and business requirements evolve, a single API Gateway might encounter limitations due to the increasing number and diverse needs of client applications. The Backends for Frontends (BFF) design pattern addresses this challenge by segmenting client applications, employing multiple API Gateways that cater to specific types of clients.

Different applications, such as an MVC web application, a mobile app, or connections from 3rd party consumers, demand varying levels of content. For instance, mobile clients often require a different subset of content compared to a full website. The BFF pattern, used in conjunction with API Gateways, facilitates the segregation required to manage these differences efficiently, optimizing the content provided to different client types.

This approach is crucial, especially considering mobile app users who might have limited data usage. By tailoring the information transmitted to the specific needs of different applications, the BFF pattern minimizes unnecessary data exchange, aligning with the end user's data usage requirements.

While employing the API Gateway pattern, certain precautions should be taken. There exists a level of coupling between microservices and the API Gateway, leading to evolving infrastructure needs. Maintenance is crucial to avoid excessive coupling, ensuring that the API Gateway doesn't become overly responsible for operations. In instances where multiple Gateways are deployed and microservices are distributed among them, potential bottlenecks and latency issues associated with a single Gateway can be mitigated, promoting smoother system performance.

External Configuration Store

Configuration management within a microservices architecture is critical, analogous to the requirements in monolithic systems. However, in a microservices environment with multiple instances, managing individual configuration files for each instance becomes impractical and arduous to maintain. To address this issue, the External Configuration Store pattern offers a solution by providing a centralized repository for storing configuration information, ensuring consistency across all microservice instances.

This common storage area, often housed in a data store such as SQL Server or Azure Cosmos DB, serves as a single source for configuration values. To facilitate environment-specific settings in different stages like Development, Staging, or Production, separate Configuration Stores can be utilized, enabling the same code to function seamlessly across various environments.

However, each microservice instance needs to be informed of how to access the Configuration Store. This information is typically outlined in the local configuration files, providing sufficient details on the location and access methods to retrieve all other application settings.

One significant challenge lies in determining when to retrieve the settings from the Configuration Store. There are two primary approaches: fetching all settings at the startup or acquiring them on an as-needed basis. Opting for retrieving settings at startup implies that the behavior of the microservice will remain constant until the next restart, which is suitable for some static settings, such as environmental distinctions, like logging configurations. For instance, a microservice operating in a Development environment may log more verbose information compared to other environments. Such settings are less likely to change frequently.

However, other settings, like defining an HTTP timeout value or the maximum number of retries in a business function, can fluctuate and should be checked more regularly. These dynamic settings might directly influence the behavior of the microservice and hence require frequent verification and updates. Adjusting these parameters, especially in scenarios like error handling, could be crucial for the service's functioning based on specific conditions or operational requirements.

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