Low latency in a distributed system is crucial for delivering responsive and efficient user services. Here are ten strategies to help you minimise latency:

Use Content Delivery Networks (CDNs): Employ CDNs to cache and deliver content from servers located geographically closer to end-users, reducing the round-trip time for data.

Load Balancing: Implement intelligent load balancing to distribute traffic evenly across servers, preventing any single server from becoming a bottleneck.

Edge Computing: Leverage edge computing to process data closer to the source or user, reducing the data's round-trip journey to a centralised data centre.

Caching: Utilize caching mechanisms, such as in-memory or distributed caches like Redis, to store frequently accessed data and serve it quickly.

Compression: Compress data before transmitting it over the network to reduce the data sent, decreasing transfer times.

Asynchronous Processing: Use asynchronous communication and processing, such as message queues and event-driven architectures, to decouple components and reduce wait times.

Content Prioritization: Prioritize critical content or tasks to ensure they receive preferential treatment and are processed more quickly.

Predictive Scaling: Implement auto-scaling mechanisms that dynamically allocate resources based on traffic patterns and demand, preventing resource saturation.

Reduce Chatty Communication: Minimize the number of network requests and reduce chattiness by aggregating data or batch processing when possible.

Optimise Network Communication: Optimize protocols and use technologies like HTTP/2 or WebSockets to reduce the overhead of setting up and tearing down connections.

These strategies should be tailored to your specific distributed system's architecture and requirements. Additionally, ongoing monitoring and performance testing are crucial to identifying and addressing latency bottlenecks as your design evolves. 

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