reame

README.md

@@ -70,13 +70,13 @@ Watch the video presentation [here](https://youtu.be/KZIzitQN4ss)
 
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-### Pending Work - Scaling Beyond 10,000 Requests per Second
-- The microservice currently achieves ~2000 RPS locally due to hardware limits.
-- Recommended Next Steps:
-  - Scale App Runner instances to handle higher traffic.
-  - Implement additional caching (e.g., Redis) for frequent queries.
-  - Use database replication or partitioning to distribute the load.
-  - Integrate a load balancer to manage traffic across multiple instances.
+### Load Test
+
+![load_test][total_requests_per_second_1734060700.608.png]
+
+- Performance under Load: The system handles initial load increases well, but begins to struggle as the number of requests per second and concurrent users grow drastically. 
+- Potential Issues: The spike in response times and growing failures suggest bottlenecks, possibly in CPU, memory, or I/O capacity. 
+-	Next Steps: Investigate system resource utilization during this test and identify the bottleneck. Consider optimizing code, scaling infrastructure, or implementing load-balancing techniques to improve system performance. The switch to AWS EC2 does not aid the situation. Due to budget limit, we might try to move our database to AWS Postgre SQL to enable transcational query optimization.
 
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