The IT software development industry is making a huge shift with monolithic architecture passing the torch to the distributed power of microservices. Monoliths, providing the simplicity of direct method calls, paved the way for microservices & their efficient communication throughout independent services.

This distributed nature facilitates a move away from conventional technologies. With message queues & RESTful APIs, they allow seamless data exchange & coordinated actions across & between microservices.

This shift demands a re-evaluation of overall communication strategies fr a well-orchestrated flow of information across systems.

To explore the mere difference between synchronous communication and asynchronous communication, keep reading below:

This sort of communication allows the creation of a call-and-wait scenario between service endpoints.

For example, if a client is making an HTTP request, a synchronous approach blocks the client thread & waits for a response before proceeding. This wait time can range from anywhere between milliseconds to seconds.

This time is dependent on the service’s processing needs. The client, then, must be tied up in this interaction until any response has gone through-putting other tasks on hold.

Synchronous Communication gives developers a well-defined execution path. It establishes a clear request-response pattern within systems. This linear model is easy to reason with and makes debugging & troubleshooting simpler.

Dedicated developers can trace the path of a request & pinpoint any issues within the calls quite easily.

The synchronous nature of the system ensures that the responses are received promptly, allowing real-time interactions between developers and clients.

This is perfect for moments where immediate feedback is needed, like in user-based applications where instant confirmation or updates are appreciated, such as in payment gateways.

Here, clients have the opportunity to react to the server’s responses immediately, allowing for a highly responsive UX.

Having a system with synchronous communication brings forth a certain blocking behavior for the requested service. Sometimes the client’s request remains idle, making it impossible to process it further until a response comes from the server side.

This can heavily affect performance, especially if the server is undergoing delays or extensive processing.

This occurs due to the heavy reliance on real-time processing between services. Any changes or scaling efforts can have cascading effects on other services.

This happens because of the synchronous dependencies and can affect long-term easy maintainability & flexibility.

This type of communication in microservices works as a live conversation amongst two or more services. Here, instead of trained or pre-recorded responses, services share information on a real-time basis, facilitating immediate interactions.

Try imagining a dedicated user needing help while shopping online. They use the chatbot to enter their query.

Within, the system routes it to a microservice that is dedicatedly used for chat support. This service, then, acts as the platform’s agent, reading and replying to messages directly to the user in the present time of the query being raised.

Such interactions create smooth experiences for the user, bringing in quick clarification and problem-solving to the mix.

• – Users receive immediate responses, allowing for higher trust and quicker resolutions.
• – Real-time chatbots let businesses develop personal connections, making the user’s experience better and stronger.

A user while checking out on a shopping site like Myntra, the cart service acts as the initiator. This sends a request with the order details & connects it further to the payment service.

Here, the synchronous communication makes sure that the payment service receives real-time, facilitating immediate authorization for the same. The user, then, receives hard confirmation that the payment is being processed before confirming the order from the server side.

• – Users get instant confirmation about payments, stopping further confusion or delays.
• – This communication cycle ensures smooth processing across steps of ultimately finalizing the order.

Synchronous communication, as mentioned, works brilliantly when real-time information sharing, and immediate responses are concerned:

• – Instant feedback & interaction: Like in real-time chats and multiplayer games.
• – Quick decisions & execution: Allowing services to have instant reactions to changes in conditions, making room for on-the-spot analysis & implementation.
• – Interconnected workflows: When different stages or services have cascading dependencies, synchronous communication allows a coupled and seamless workflow.

Now that we’ve gauged the benefits and disadvantages of synchronous communication, let’s try to understand asynchronous communication in-depth.

The base difference between synchronous communication and asynchronous communication is explained next:

• – Synchronous communication in microservices provides immediate feedback, but also introduces bottlenecks like wait-time for responses.
• – Asynchronous communication, on the other hand, presents itself as a compelling alternative- building a loosely couple, highly scalable architecture.

Let’s take a look at its technicalities.

The main consideration of asynchronous communication is the features of being a message broker. This service looks like an intermediary, allowing for message exchanges between microservices.

Here, dedicated developers may choose between Apache Kafka, RabbitMQ, or Apache ActiveMQ.

In such microservices, messages, like tasks or notifications, flow from the producer services to this message broker. A middleman, like this, ensures that the message delivery is reliable even if the receiving service is unreachable.

The user-end services then manually pick-and-choose these messages, leveraging loose coupling and fault tolerances in the system.

As central hubs, these message brokers allow for asynchronous message exchanges between services, allowing scalability; and decoupling for higher flexibility & fault tolerance.

This kind of communication doesn’t block the requesting service while waiting for response. Such functionality allows the service to continue with other tasks simultaneously, while increasing overall output & optimizing resources used.

Services, here, are loosely coupled, or don’t rely on others for immediate responses. This heavily simplifies the system’s maintenance & further development, making it scalable.

Changes in a single service don’t have cascading effects on the other, allowing independent scalability & flexibility.

To facilitate this, message broker systems are employed within the system. This delivers the messages even when the receiving service is unavailable in real time. With this, the system handles undelivered messages too.

Having such fewer system disruptions enhances the overall resilience.

Asynchronous communication also brings forth additional complexities. The message queues include designing message formats, implementing reliable mechanisms, error handling, and monitoring message queues, which increases the development load.

Asynchronous types of communication can delay the resulting results. This might not work for situations where real time updates or immediate responses are crucial, especially in high-sensitivity data feeding sites like payment gateways.

Let’s look at some examples through a technical lens.

Here, the user triggers any action like registration. The user service, or the initiator, starts the message flow with the relevant details, to a dedicated message queue.

• – The user & email service work independently while communicating asynchronously. So, any triggered action will be completed even if the email service isn’t available.
• – The utilized message queue may buffer the emails, allowing the service to handle the number of messages efficiently.
• – Since the communication is asynchronous, the message queue works independently to attempt delivery retries.

Here, the receiving service, or primary application, deals with huge datasets or complex computations. The communication stems from the primary to a message processing queue.

• – Through asynchronous communication, the initiator doesn’t get blocked for a task to be completed, enhancing user experience.
• – Background processing occurs independently, freeing up necessary resources for the primary application’s tasks.
• – The system can be scaled using such asynchronous communication to handle a high volume of tasks.

An action is started when a user utilizes platform features like posting, liking or interacting with the content. Here, the ‘post’ service sends a message with all the data such as post image or caption, to a dedicated queue, or the feed of a social media platform.

• – The feed service can properly process updates and refresh the feeds in batches.
• – Real-time updates are avoided, to prevent overloading the UI.
• – Batched messages, or posts, optimizes databases & enhances performance.

• – For developing applications with non-critical and demanding feedback loops.
• – To handle long-running tasks like background processing, with tasks at varied execution times.
• – While prioritizing independent and scalable services.

The above examples can clearly showcase how asynchronous communication powers the architecture for microservices. This communication gives:

• 1. Independently operating services with minimal dependencies on others. Thus, simplifying development, deployment & maintenance.
• 2. Buffered message queues to allow services to handle a huge volume of requests without any issues. This results in easy scaling of independent services.
• 3. With asynchronous communication, user interactions aren’t affected while processing background & heavy-load tasks. This improves the system’s overall responsiveness.

By leveraging message brokers & loose coupling through asynchronous communication, we get scalability, resilience, and independent development cycles. At the same time, synchronous communication allows for less wait time & higher user responsiveness.

The first step to this is to explore the difference between synchronous communication and asynchronous communication. By carefully considering both the methods’ trade-offs, dedicated developers may leverage either, or both, communication patterns to design efficient systems.