tencentcloud-cls

What problem does it solve?

When you need to find the root cause of errors, trace a failing request, or understand what happened in a Tencent Cloud service, searching and analyzing raw log streams is slow and hard to repeat.

Core Features & Use Cases

• Targeted log discovery with CQL/Lucene: Search Tencent Cloud CLS log topics using time ranges plus structured filters, including trace_id lookups.
• Run analytics on log data: Perform aggregation using CLS SQL-on-logs by appending a SELECT/GROUP BY clause to your CQL query.
• Fields extraction for structured debugging: Decode indexed LogJson per record to surface key attributes like status_code, api_name, or custom fields.
• Typical scenarios: Locate recent 5xx errors, trace a request lifecycle by trace ID across topics, and summarize which APIs produce the most failures.

Quick Start

Ask the AI to search your CLS topic for recent errors by running an indexed CQL query over the last hour and returning matching records with extracted fields.