when we talk about real-time distributed systems, the first thing to understand is that it's not just about sending data from one place to another. There are several key factors to consider to ensure these systems work correctly in real-time.
Clock Synchronization:
In a distributed system, the different nodes need to be synchronized in terms of time. This is typically done with protocols like NTP (Network Time Protocol). That way, even though the nodes might be in different locations, they all "sync up" to avoid any time mismatches in the data being processed and transmitted.
Data Consistency:
Consistency is another important aspect. You need to make sure that the data being generated and consumed is up-to-date and correct. In distributed systems, consistency is often handled as eventual consistency, meaning the data will eventually sync across all nodes, but not at the same time.
Latency Management:
Latency is the delay between when an event happens and when it reflects on the user interface. To keep latency low, techniques like buffering or message queues can be used. As you mentioned, the Producer/Consumer pattern is useful, but it's also key for the backend to be optimized for sending data with minimal latency.
Communication Patterns:
To display data in almost real-time on the UI, the backend can use patterns like pub/sub or push notifications to send updates to the user interface. Systems like WebSockets or Server-Sent Events are quite common in these types of applications, as they allow real-time communication between the client and server.
Scalability and Fault Tolerance:
In a distributed system, it's crucial that it can scale as the workload increases. Additionally, it needs to be fault-tolerant, meaning it continues to function even if some of the nodes fail. This can be achieved through data replication and implementing strategies like circuit breakers.
Real-Time Guarantees:
Depending on the type of system, you might need to meet strict real-time guarantees. This means that certain tasks must be completed within a specified time frame, with no exceptions. To achieve this, it's necessary to use scheduling techniques like EDF (Earliest Deadline First) or RMS (Rate-Monotonic Scheduling).
As for the interview, what they're asking you to do is a good starting point. The Producer/Consumer pattern is helpful, but it's also important for the backend to use a messaging system like Kafka or RabbitMQ, where data generated by the producer is sent to the consumer, which handles processing and updates the UI. When it comes to displaying this data in real-time, the backend can use WebSockets to send updates directly to the frontend.
If you have time, I recommend reading more about WebSockets and Kafka, as these are tools commonly used in real-time distributed systems. Also, it's a good idea to understand a bit about how errors and failures are handled in these systems, like retry mechanisms.