UapiPro API Alert: /api/v1/network/dns Issues Detected

Attention AxT-Team and UapiPro-Issue! A critical system alert has been triggered for the /api/v1/network/dns API endpoint. This alert indicates a severe anomaly detected on 2025-12-03 at 15:05:56, characterized by a high error rate, high latency, and low success rate. The severity score for this issue is 54.9/100, highlighting the urgency of addressing this problem.

Understanding the API Exception

In this section, we'll dive into the specifics of the API exception, breaking down the key metrics that triggered the alert and their implications for system performance. Understanding the root causes behind issues like high error rates and latency is critical for maintaining a stable and responsive application environment. Let's explore the data and gain a clearer picture of what's happening with the /api/v1/network/dns endpoint.

Key Performance Indicators (KPIs) Breakdown

The core of this alert revolves around three primary metrics that have deviated significantly from their Service Level Objectives (SLOs):

• Error Rate: The current error rate has spiked to 8.00%, exceeding the established SLO threshold of ≤5.00%. This +60% deviation indicates a substantial increase in failed requests, potentially disrupting user experience and system functionality. High error rates can stem from various underlying issues, such as code defects, server overloads, or network connectivity problems. Identifying the root cause of this elevated error rate is crucial for restoring the API's reliability.
• Success Rate: Simultaneously, the success rate has plummeted to 92.00%, falling short of the target SLO of ≥95.00%. This -3% variance underscores the impact of the elevated error rate on the API's ability to serve requests successfully. A low success rate directly translates to a reduced number of successful transactions, potentially affecting key business operations. Investigating the relationship between the error rate and success rate can provide valuable insights into the nature of the problem.
• P95 Latency: The 95th percentile latency (P95 latency) has surged to 1.10s, far surpassing the acceptable limit of ≤500.0ms. This +120% deviation signifies a significant slowdown in response times for a large portion of requests. High latency can severely degrade user experience, leading to frustration and abandonment. Optimizing the API's performance to reduce latency is essential for ensuring a smooth and responsive user experience. The P95 latency metric is particularly important as it reflects the experience of the majority of users, excluding extreme outliers.

These three indicators paint a clear picture of the distress affecting the /api/v1/network/dns API. The combined effect of high error rates, low success rates, and increased latency suggests a systemic issue that requires immediate attention.

Detailed Metrics Comparison

To provide a clearer view of the situation, here's a comparison table highlighting the deviation between the actual values and the defined SLOs:

This table clearly illustrates the extent to which each metric has strayed from its target SLO. The red "❌" symbols emphasize the severity of the deviations and the urgent need for corrective action. While the request volume is relatively low at 25, the disproportionate impact on error rate, success rate, and latency suggests that the underlying issue may be resource-intensive or related to specific types of requests.

API Identification and Status

Identifying the specific API and its status is crucial for targeted troubleshooting and resolution. The following details provide essential context:

• API: /api/v1/network/dns
• Classification: Other
• Fingerprint: 46515a05c53a3229
• Status: View Details

The classification as "Other" suggests that this API may not fall under a standard category, potentially indicating a custom or less frequently used endpoint. The fingerprint serves as a unique identifier for the API, aiding in tracking and debugging. The link to the status page (https://uapis.cn/status) provides access to real-time information and potential updates on the API's health and ongoing investigations.

Understanding these core metrics and API details is the first step in diagnosing and resolving the issue. The following sections will delve deeper into the collected monitoring data and provide insights into potential causes and troubleshooting steps.

Detailed Monitoring Data

To gain a more granular understanding of the issue, let's examine the detailed monitoring data collected during the period when the exception was triggered. This data provides a comprehensive view of the API's performance, including various latency percentiles, request volumes, and error specifics. Analyzing these metrics can help pinpoint the root cause of the problems and guide effective troubleshooting efforts. Remember, having detailed data is like having a high-resolution map of the problem area; it helps you navigate directly to the source of the issue.

Current Cycle Complete Metrics

The following table presents a snapshot of the API's performance during the current monitoring cycle:

This data reveals several critical insights:

• Latency Distribution: The P50 latency of 544.0ms already exceeds the SLO for P95 latency (≤500.0ms), indicating that even the median request is experiencing significant delays. The P99 latency of 3.55s and the maximum latency of 3.55s highlight the presence of extreme outliers, further degrading the overall user experience. A wide disparity between latency percentiles often suggests intermittent issues or resource contention.
• Failed Requests: The 2 failed requests out of a total of 25 contribute to the high error rate. Examining the specific details of these failed requests is crucial for identifying common failure patterns and potential root causes.
• Low Throughput: The throughput of 0.42 RPS (requests per second) is relatively low, which could be a consequence of the high latency and error rates. If the API is struggling to process requests efficiently, it may be indicative of resource bottlenecks or performance inefficiencies.

Request Sample for Troubleshooting

To aid in debugging, a sample request is provided:

GET /api/v1/network/dns?domain=ko-fu.net&type=A
User-Agent: Python-urllib/3.13

This sample request can be used to reproduce the issue in a controlled environment and to test potential fixes. The request targets the /api/v1/network/dns endpoint with specific parameters (domain=ko-fu.net&type=A), making it easier to isolate the problem. The User-Agent string (Python-urllib/3.13) indicates the client making the request, which can be helpful in identifying client-specific issues.

Response Information Analysis

The response information for the sample request is critical for understanding the nature of the failure:

• Status Code: 500
• Latency: 953ms
• Error: {"code":"INTERNAL_SERVER_ERROR","message":"服务器内部错误"}

The 500 Internal Server Error status code indicates a server-side problem, suggesting that the issue lies within the API's code, dependencies, or infrastructure. The latency of 953ms confirms the slow response times observed in the overall metrics. The error message {"code":"INTERNAL_SERVER_ERROR","message":"服务器内部错误"} provides a general description of the problem but lacks specific details. Further investigation, such as examining server logs and debugging the code, is necessary to pinpoint the exact cause of the error.

SLO Configuration

Understanding the SLO configuration helps put the current situation into perspective:

These SLOs define the acceptable performance boundaries for the API. The fact that the current metrics have breached these thresholds underscores the severity of the issue and the importance of restoring the API's performance to within acceptable limits.

By analyzing this detailed monitoring data, we can start to formulate hypotheses about the potential root causes of the problem. The next step is to leverage this information to guide troubleshooting efforts and implement effective solutions.

Potential Causes and Troubleshooting Steps

Based on the information gathered, several potential causes could be contributing to the high error rate, high latency, and low success rate of the /api/v1/network/dns API. It's essential to systematically investigate each possibility to identify the root cause and implement appropriate solutions. Remember, effective troubleshooting is like detective work; you gather clues, form hypotheses, and test them methodically until you find the culprit.

1. Server Overload or Resource Exhaustion

• Symptom: The 500 Internal Server Error, combined with high latency, suggests that the server hosting the API might be overloaded or experiencing resource exhaustion. This could manifest as high CPU usage, memory pressure, or disk I/O bottlenecks.
• Troubleshooting Steps:
  • Monitor Server Resources: Use system monitoring tools to track CPU usage, memory consumption, disk I/O, and network traffic on the server hosting the API. Look for any spikes or sustained high levels of resource utilization.
  • Check Server Logs: Examine the server logs for error messages or warnings related to resource exhaustion. Common indicators include "Out of Memory" errors, "CPU throttling" messages, or excessive disk I/O wait times.
  • Optimize Resource Allocation: If resource exhaustion is confirmed, consider increasing server resources (e.g., upgrading CPU, adding RAM) or optimizing resource allocation (e.g., adjusting memory limits, configuring connection pooling).

2. Network Connectivity Issues

• Symptom: High latency and potential intermittent errors could be caused by network connectivity problems between the client and the server or between the server and its dependencies (e.g., DNS servers, databases).
• Troubleshooting Steps:
  • Ping and Traceroute: Use ping and traceroute to test network connectivity and identify potential bottlenecks or packet loss along the network path.
  • DNS Resolution: Verify that the server can resolve DNS names correctly. DNS resolution issues can lead to slow response times and failed requests.
  • Firewall Configuration: Check firewall rules to ensure that traffic to and from the API server is not being blocked or filtered.

3. Code Defects or Bugs

• Symptom: A 500 Internal Server Error often indicates a bug or defect in the API's code. This could be a runtime exception, a logic error, or an unhandled condition.
• Troubleshooting Steps:
  • Code Review: Review the API's code for potential bugs, especially in the areas related to DNS resolution or network communication.
  • Debugging: Use a debugger to step through the code and identify the exact point where the error occurs. Examine variable values and call stacks to understand the context of the error.
  • Exception Handling: Ensure that the API has proper exception handling to catch and log errors gracefully. Unhandled exceptions can lead to 500 errors and obscure the root cause of the problem.

4. Dependency Issues

• Symptom: The API may rely on external services or databases. If these dependencies are experiencing issues, it can impact the API's performance and stability.
• Troubleshooting Steps:
  • Monitor Dependencies: Monitor the health and performance of external services and databases that the API depends on. Look for any error messages or performance degradation.
  • Connection Pooling: Implement connection pooling to optimize database connections and reduce the overhead of establishing new connections.
  • Timeout Configuration: Configure appropriate timeouts for requests to external services to prevent the API from hanging indefinitely if a dependency is unavailable.

5. DNS Server Problems

• Symptom: Since the API is related to network DNS, issues with DNS servers themselves could be the root cause. This might involve slow DNS resolution, DNS server unavailability, or incorrect DNS records.
• Troubleshooting Steps:
  • DNS Server Health Check: Check the health and responsiveness of the DNS servers being used by the system. Tools like dig or nslookup can help diagnose DNS issues.
  • DNS Record Verification: Verify that DNS records for the relevant domains are correctly configured. Incorrect DNS records can lead to resolution failures and connection problems.
  • DNS Caching: Investigate DNS caching mechanisms to ensure they are functioning correctly. Caching issues can sometimes lead to stale or incorrect DNS information being used.

Conclusion

The alert for the /api/v1/network/dns API endpoint signals a critical issue requiring immediate attention. The combination of high error rates, high latency, and low success rates points to a significant disruption in service. By systematically analyzing the detailed monitoring data and following the troubleshooting steps outlined above, the AxT-Team and UapiPro-Issue can effectively diagnose and resolve the problem. Remember, a proactive approach to monitoring and troubleshooting is essential for maintaining the stability and reliability of any API. Always prioritize a methodical approach, and don't hesitate to leverage all available tools and resources to pinpoint the root cause. For further reading on API monitoring and troubleshooting, check out this comprehensive guide to API monitoring best practices.