In a microservices architecture, making synchronous calls only can lead to cascading failures due to the lack of guarantees on service availability and response time. Asynchronous communication is generally recommended, but it requires careful consideration of issues such as network instability, high latency, or temporary unavailability of services. To address these challenges, frameworks like Netflix's Hystrix provide a set of patterns, including local caches, timeouts, retries, circuit breakers, bulkheads, etc., to prevent cascading failures. However, this approach can add unnecessary complexity to the system. An alternative is the Service Mesh pattern, which externalizes this complexity in a sidecar container and provides standardized metrics, making it language agnostic and easier to manage. Choosing an inappropriate database for a microservices system can also lead to poor performance and high costs. Specialized storage solutions like NoSQL databases offer benefits such as higher performance, lower cost, and improved scalability. Finally, debugging and observability in a distributed system require careful planning and consideration of tools like Event Sourcing/Logging, which can help identify issues and provide insights into the system's behavior.