Home Web Front-end JS Tutorial The impact of excessive tomcat concurrency

The impact of excessive tomcat concurrency

Apr 21, 2024 am 06:49 AM
tomcat Concurrent requests

High concurrency in Tomcat causes performance degradation and stability issues, including thread pool exhaustion, resource contention, deadlocks, and memory leaks. Mitigation measures include: adjusting thread pool settings, optimizing resource usage, monitoring server metrics, performing load testing, and using a load balancer.

The impact of excessive tomcat concurrency

The impact of high concurrency on Tomcat

Tomcat is a widely used Java Servlet container. When the number of concurrent requests When it is too large, the following effects may occur:

Performance degradation

  • Thread pool exhaustion:Tomcat uses the thread pool for processing ask. High concurrency can cause the thread pool to be exhausted, thereby preventing new requests from being processed.
  • Resource contention: Multiple threads accessing the same resource (such as memory or database connection) at the same time can cause resource contention, which in turn reduces application performance.

Stability issues

  • Deadlock: When multiple threads wait for each other, deadlock may result. High concurrency increases the risk of deadlock.
  • Memory Leak: High concurrency may cause memory leaks, which may gradually reduce server performance.
  • Insufficient resources: When server resources are insufficient to handle all concurrent requests, service interruptions or errors may occur.

Poor user experience

  • Request delay: High concurrency will cause request delay, which will affect the user experience.
  • Page Error: Due to insufficient server resources, the request may fail and return an error page.
  • Website downtime: In extreme cases, high concurrency may cause website downtime.

Mitigation measures

In order to alleviate the impact of Tomcat’s high concurrency, the following measures can be taken:

  • Adjustment Thread pool settings: Increase the thread pool size to handle more concurrent requests.
  • Optimize resource usage: Use connection pooling, caching and asynchronous processing technology to optimize access to resources.
  • Monitor server metrics: Continuously monitor server metrics such as thread count, memory usage, and request latency to identify potential issues.
  • Conduct a load test: Perform a load test to determine the server's ability to handle high concurrency.
  • Use a load balancer: Distribute traffic to multiple servers to reduce the pressure on a single server.

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