Apply a technique which I would call "critical path optimization". Identify the system's critical path—the sequence of processes that directly impacts overall performance—and focus on optimizing the bottleneck that has the highest impact on that path first. This approach ensures that improvements in this area will yield the most significant gains in system performance, allowing you to quickly enhance efficiency without wasting time on less critical areas. By prioritizing the critical path, you can systematically tackle the most impactful bottlenecks first.

In a distributed system, tackling performance bottlenecks requires a strategic approach. I prioritize the "Critical Path Bottleneck" first—the component directly impacting the end-to-end response time. Why? Because improving this area yields the most significant impact on overall performance. Other bottlenecks, like resource constraints or data inconsistency, can be addressed subsequently. By focusing on the critical path, we ensure that the most pressing issues are resolved, optimizing user experience and system stability. Prioritizing this way keeps the system scalable and efficient under heavy load.

We should identify the most impacted bottleneck components using monitoring tools and prioritize the components that the team should work on first. These measurements can depend on multiple factors, such as latency, throughput, resource usage, and error rate etc.

In a distributed system, I would prioritize addressing network latency first. As the backbone of communication between services, delays in network latency can cascade, impacting overall system performance. Improving bandwidth, optimizing routing, or reducing round-trip times can lead to significant performance gains. Next, I'd focus on database performance, as slow queries or inefficient indexing can create bottlenecks across services relying on timely data access. Lastly, resource contention due to CPU, memory, or disk usage needs attention, ensuring that each service gets adequate compute resources for optimal performance.

I would prioritise distributed system health first, Any distributed system will have two of the capabilities from Consistency, Availability, Partition Tolerance. To honour this systems typically maintain state at a central place. It's important to ensure this is unaffected. For in case of Systems like Opensearch having cluster state healthy should be most important for this you might need to work on reducing overall load on cluster or boiling down to specific node etc. for Systems uses Zookeeper maintaining it's health and responsiveness are important, so that all nodes using zookeeper can operate effectively. Few strategies might help is reducing ingress load i.e read/write requests, removing a problematic node to reduce overall load.