Improve Monitoring Process

Oct 13, 2025 by leolavanderia.com.br 145 views

Introduction

Intermittent latency spikes can be a frustrating issue, especially when they occur on critical endpoints like the /metrics endpoint. In this article, we will delve into the world of intermittent latency spikes, exploring the possible causes and potential solutions. We will examine a real-world scenario where intermittent latency spikes occur approximately every 6 seconds, and discuss the efforts made to resolve this issue.

The Problem

The /metrics endpoint is experiencing intermittent latency spikes, with response times ranging from 0.0017 seconds to 3.4527 seconds. The latency spikes occur approximately every 6 seconds, as shown in the log snippet below:

2025-03-11 12:07:37 - Response Time: 3.3146 seconds   <<<<<<
2025-03-11 12:07:37 - Response Time: 0.0044 seconds
2025-03-11 12:07:37 - Response Time: 0.0042 seconds
...
2025-03-11 12:07:40 - Response Time: 0.0049 seconds
2025-03-11 12:07:40 - Response Time: 0.0017 seconds
2025-03-11 12:07:43 - Response Time: 3.4527 seconds   <<<<<<
2025-03-11 12:07:43 - Response Time: 0.0040 seconds
2025-03-11 12:07:43 - Response Time: 0.0034 seconds
...
2025-03-11 12:07:46 - Response Time: 0.0040 seconds
2025-03-11 12:07:46 - Response Time: 0.0035 seconds
2025-03-11 12:07:50 - Response Time: 3.4727 seconds  <<<<<<
2025-03-11 12:07:50 - Response Time: 0.0042 seconds
2025-03-11 12:07:50 - Response Time: 0.0023 seconds
2025-03-11 12:07:50 - Response Time: 0.0018 seconds

Analysis

The intermittent latency spikes occur when the /metrics endpoint is being monitored, but not when no streams are being monitored. This suggests that the issue is related to the monitoring process. The fact that reducing the mutex locks and updating the stream and variant checking to run async did not resolve the issue indicates that the problem may be more complex.

Possible Causes

Based on the analysis, the possible causes of the intermittent latency spikes are:

Mutex Locks: The mutex locks may be causing a bottleneck, preventing the HTTP responses from being sent in a timely manner.
Monitoring Process: The monitoring process may be interfering with the HTTP responses, causing the latency spikes.
Network IO: The network IO may be causing a delay in sending the HTTP responses.

Potential Solutions

To resolve the intermittent latency spikes, the following potential solutions can be explored:

Optimize Mutex Locks: The mutex locks can be optimized to reduce the time they hold the lock, allowing the HTTP responses to be sent in a timely manner.
Improve Monitoring Process: The monitoring process can be improved to reduce its impact on the HTTP responses.
Reduce Network IO: The network IO can be reduced to minimize the delay in sending the HTTP responses.

Conclusion

Intermittent latency spikes can be a frustrating issue, but by analyzing the problem and exploring potential solutions, it is possible to resolve the issue. In this article, we have examined a real-world scenario where intermittent latency spikes occur approximately every 6 seconds, and discussed the possible causes and potential solutions. By optimizing the mutex locks, improving the monitoring process, and reducing network IO, it is possible to resolve the intermittent latency spikes and ensure that the /metrics endpoint responds in a timely manner.

Recommendations

Based on the analysis and potential solutions, the following recommendations can be made:

Optimize Mutex Locks: The mutex locks should be optimized to reduce the time they hold the lock, allowing the HTTP responses to be sent in a timely manner.
Improve Monitoring Process: The monitoring process should be improved to reduce its impact on the HTTP responses.
Reduce Network IO: The network IO should be reduced to minimize the delay in sending the HTTP responses.

Future Work

To further resolve the intermittent latency spikes, the following future work can be done:

Implement Load Testing: Load testing can be implemented to simulate a large number of requests to the /metrics endpoint, allowing the issue to be reproduced and analyzed.
Analyze Network IO: The network IO can be analyzed to identify any bottlenecks or delays that may be contributing to the intermittent latency spikes.
Optimize Monitoring Process: The monitoring process can be optimized to reduce its impact on the HTTP responses.

Introduction

In our previous article, we explored the issue of intermittent latency spikes on the /metrics endpoint. We analyzed the problem, discussed possible causes, and presented potential solutions. In this article, we will answer some of the most frequently asked questions related to intermittent latency spikes.

Q: What are intermittent latency spikes?

A: Intermittent latency spikes refer to a situation where a system or application experiences sudden and unpredictable delays in responding to requests. In the case of the /metrics endpoint, intermittent latency spikes result in response times ranging from 0.0017 seconds to 3.4527 seconds.

Q: What causes intermittent latency spikes?

A: Intermittent latency spikes can be caused by a variety of factors, including:

Mutex Locks: Mutex locks can cause a bottleneck, preventing the HTTP responses from being sent in a timely manner.
Monitoring Process: The monitoring process can interfere with the HTTP responses, causing latency spikes.
Network IO: Network IO can cause a delay in sending the HTTP responses.

Q: How can I identify intermittent latency spikes?

A: To identify intermittent latency spikes, you can use tools such as:

Logging: Logging can help you track the response times of the /metrics endpoint.
Monitoring Tools: Monitoring tools can help you identify patterns and anomalies in the response times.
Load Testing: Load testing can help you simulate a large number of requests to the /metrics endpoint, allowing you to identify any issues.

Q: How can I resolve intermittent latency spikes?

A: To resolve intermittent latency spikes, you can try the following:

Optimize Mutex Locks: Optimizing mutex locks can help reduce the time they hold the lock, allowing the HTTP responses to be sent in a timely manner.
Improve Monitoring Process: Improving the monitoring process can help reduce its impact on the HTTP responses.
Reduce Network IO: Reducing network IO can help minimize the delay in sending the HTTP responses.

Q: What are some best practices for preventing intermittent latency spikes?

A: Some best practices for preventing intermittent latency spikes include:

Optimize Code: Optimizing code can help reduce the time it takes to execute, minimizing the likelihood of latency spikes.
Use Asynchronous Programming: Using asynchronous programming can help reduce the time it takes to execute tasks, minimizing the likelihood of latency spikes.
Monitor System Resources: Monitoring system resources can help identify any issues that may be contributing to latency spikes.

Q: What are some common mistakes that can lead to intermittent latency spikes?

A: Some common mistakes that can lead to intermittent latency spikes include:

Not Optimizing Code: Not optimizing code can lead to slow execution times, increasing the likelihood of latency spikes.
Not Using Asynchronous Programming: Not using asynchronous programming can lead to slow execution times, increasing the likelihood of latency spikes.
Not Monitoring System Resources: Not monitoring system resources can lead to issues going undetected, increasing the likelihood of latency spikes.

Conclusion

Intermittent latency spikes can be a frustrating issue, but by understanding the causes and taking steps to prevent them, you can ensure that your system or application responds in a timely manner. By following the best practices and avoiding common mistakes, you can minimize the likelihood of intermittent latency spikes and ensure that your system or application runs smoothly.