Decoding synchronous and asynchronous communication in cloud native applications

Designing cloud-native applications involves managing a complex system of microservices and serverless components that need to communicate with each other effectively. Synchronous communication uses HTTP or gRPC calls, waiting for a response within a specified time range, providing real-time feedback, and is suitable for scenarios that require immediate response. Asynchronous communication utilizes message brokers (such as RabbitMQ or Kafka) to exchange messages without requiring immediate responses, enhancing the scalability of the system. By understanding the advantages and disadvantages of each communication mode, architects can design systems that effectively coordinate these independent elements to deliver high-performance, scalable, and reliable cloud-native applications.

Imagine building a complex machine with many independent parts, each performing its function, but all needing to communicate effectively with each other to do so Task. This is the challenge we face when designing cloud-native applications composed of interconnected microservices and serverless components. In this article, we explore the details of designing a robust and resilient communication system that can effectively coordinate these independent elements inside and outside the application boundary.

These fine-grained services employ various synchronous or asynchronous communication methods for internal and external interactions. In synchronous communication, one service calls another service using HTTP or gRPC, waits for a response within a specified time frame, and then continues. In contrast, asynchronous communication involves exchanging messages without expecting an immediate response. A message broker such as RabbitMQ or Kafka acts as an intermediary, buffering messages to ensure reliable delivery. In cloud-native applications, employing a combination of communication patterns is often a practical approach. Let's start with synchronous communication.

What is synchronous communication?

Synchronous communication is like a conversation. One service (let's call it service A) makes a request and then waits for a response from another service (service B) or an external API. This is similar to asking a question and waiting for the answer. Service A sends the request via HTTP and waits. It either waits for a response from service B or waits for the maximum wait time to expire. During this waiting period, Service A is temporarily blocked, just as one pauses its activity to wait for a response. This mode is often called the request-response mode and is relatively simple to implement. However, its widespread use may present challenges that require careful consideration.

Challenges of Synchronous Communication

While synchronous communication is a powerful tool in our cloud native toolkit, it also comes with its own set of challenges that require careful consideration. .

Temporal Coupling

Over-reliance on synchronous communication throughout the solution can lead to temporal coupling issues. This happens when a large number of synchronous calls are chained together, causing the client application to wait longer to receive a response.

Availability Dependencies

Synchronous communication requires that all communication services be available simultaneously. If the backend service experiences unexpected load, client applications may fail with timeout errors, affecting overall performance.

Network Quality Impact

Network quality can directly impact the performance of synchronous communications, including available bandwidth and the duration required for responses to traverse between service backend services.

Despite these challenges, synchronous communication can be invaluable in certain scenarios. Let's explore some use cases where synchronous communication might be a better choice in the next section.

When to use synchronous communication

In some cases, using synchronous communication may be a better choice.

Real-time data access or guaranteed results

Synchronous communications can increase efficiency when immediate or real-time feedback is required. For example, when a customer places an order on an e-commerce website, the e-commerce front-end needs to check the inventory system to ensure that the item is in stock. This is a synchronous operation because the application needs to wait for a response from the inventory system before it can continue processing the order.

Orchestration of related tasks

In situations where a service must perform a sequence of tasks, each of which depends on the previous task, synchronous communication can maintain the order. . It's particularly suitable for workflows where the order of tasks is critical.

Maintaining Transaction Integrity

When maintaining data consistency between multiple components is critical, synchronous communication can help maintain atomic transactions. It is relevant for scenarios such as financial transactions where data integrity is critical.

Synchronous communication is a powerful tool, but it also comes with challenges. The good news is that we also have the option of asynchronous communication - a complementary style that can work with synchronous methods. Let's explore this further in the next section.

What is asynchronous communication?

The asynchronous communication mode provides a dynamic and efficient method for communication between services. Unlike synchronous communication, asynchronous communication allows a service to initiate a request without waiting for an immediate response. In this model, responses may not be immediate or arrive asynchronously on a separate channel (such as a callback queue). This communication model relies on protocols such as Advanced Message Queuing Protocol (AMQP) and messaging middleware, including message brokers or event brokers.

This messaging middleware acts as an intermediary with minimal business logic. It receives messages from a source or producer service and delivers them to the intended consumer service. Integrating messaging middleware can significantly improve the resiliency and fault tolerance of this decoupled approach. Asynchronous communication encompasses various implementations. Let’s explore these further.

One-to-one communication

In one-to-one message communication, the producer uses a message broker to dispatch the message specifically to the receiver. Typically, message brokers rely on queues to ensure reliable communication and provide delivery guarantees, such as at-least-once. The implementation is similar to the command pattern, where the passed message acts as a command used by the subscriber service to trigger actions.

Let’s consider an example from an online retail store to illustrate its use. An online business depends largely on the reliability of its website. This model provides fault tolerance and message guarantees, ensuring that once a customer places an order on the website, the backend fulfillment system receives the order to process. The message broker retains messages even if the back-end system is shut down and delivers them when they can be processed. For example, in an e-commerce application, when a customer places an order, a message broker can be used to send the order details as a message from the order service (producer) to the fulfillment service (consumer). This is an example of one-to-one communication.

Asynchronous one-to-one communication in the cloud

The extension of the one-to-one message mode is the asynchronous request-response mode. In this case, the dispatcher sends the message without expecting a response. But in some specific scenarios, consumers must utilize queues in the same message broker infrastructure queue to respond to production services. Responses from consumers may contain additional metadata, such as an ID associated with the initial request or response address. Since producers do not expect immediate responses, a separate producer workflow manages these replies. Once an order is placed, the fulfillment service (consumer) responds to the front-end order service (producer) so that customers can update on the website.

Asynchronous one-to-one request-reply communication in the cloud

Single consumer communication comes in handy when two services communicate point-to-point. However, there are situations where a publisher must send a specific event to multiple subscribers, which leads us to the following pattern.

One-to-many communication

This communication method is very useful when a single component (publisher) needs to broadcast events to multiple components and services (subscribers) valuable. One-to-many communication uses the concept of topics, similar to online forums.

It is like an online forum where multiple users can post articles that their followers can read in their own time and respond as needed. Likewise, an application can have topics that producer services can write to and consumer services can read from. It is one of the most popular patterns in real-world applications.

Consider again that the e-commerce platform has a service that updates product prices, and multiple services require this information (such as subscription services, recommendation services, etc.), price updates can be sent as messages to topics in the message broker. All interested services (subscribers) can listen to the topic and receive price updates. This is an example of one-to-many communication. There are several tools available to implement this pattern, with Apache Kafka, Redis Pub/Sub, Amazon SNS, and Azure Event Grid being some of the most popular choices.

Asynchronous one-to-many communication in the cloud

Challenges of asynchronous communication

Although asynchronous communication provides many benefits, it It also brings its own set of challenges.

Resilience and Fault Tolerance

With a large number of microservices and serverless components, each with multiple instances, failures are inevitable. Instances can crash, become overwhelmed, or experience temporary failures. Additionally, the sender does not wait for the message to be processed, so if an error occurs, it may not be immediately aware of it. We must adopt the following strategies:

Retry mechanism: retry failed network calls for temporary failures

Circuit breaker mode: prevent repeated calls to failed services to avoid resource bottlenecks

Distributed Tracing

Asynchronous communications can span multiple services, making monitoring overall system performance challenging. Implementing distributed tracing helps tie logs and metrics together to understand transaction flow.

Complex Debugging and Monitoring

Asynchronous communications can be more difficult to debug and monitor because operations do not follow a linear flow. Specialized tools and techniques are often required to effectively debug and monitor these systems.

Resource Management

Asynchronous systems often involve long-lived connections and background processing, which can lead to resource management challenges. Care must be taken to manage resources efficiently to prevent memory leaks or CPU overuse.

Understanding these challenges can help design more robust and resilient asynchronous communication systems in cloud-native applications.

Final Words

The choice between synchronous and asynchronous communication modes is not binary, but a strategic decision based on the specific requirements of the application.

Synchronous communication is easy to implement and provides instant feedback, making it suitable for real-time data access, orchestration of related tasks, and maintaining transaction integrity. However, it also faces challenges such as temporal coupling, availability dependence, and network quality impact.

On the other hand, asynchronous communication allows services to initiate requests without waiting for an immediate response, thereby enhancing the responsiveness and scalability of the system. It provides flexibility and is ideal for scenarios where immediate feedback is not required. However, it introduces complexities in terms of resiliency, fault tolerance, distributed tracing, debugging, monitoring, and resource management.

In summary, designing powerful and resilient communication systems for cloud-native applications requires a deep understanding of synchronous and asynchronous communication patterns. By carefully considering the advantages and disadvantages of each pattern and aligning them with requirements, architects can design systems that effectively orchestrate independent elements inside and outside the application boundary to deliver high-performance, scalable, and reliable cloud-native applications.

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