Best practices

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You can follow the best practices to write effective queries and obtain the most accurate results.

Writing effective queries

You can write effective queries as shown in the following examples:

  • Be specific about time ranges
    • Good: Show me errors in the last 2 hours.
    • Less effective: Show me recent errors.
  • Include relevant filters
    • Good: List Kubernetes pods in the production namespace with high memory usage.
    • Less effective: Show me pods.
  • Specify thresholds when relevant
    • Good: Find application calls with response time greater than 500ms.
    • Less effective: Show me slow calls.
  • Use technology names clearly
    • Good: Show me the IBM MQ queue depth for order-queue.
    • Less effective: Show me queue information.

Query refinement

You can begin by starting with a broad query to obtain an initial understanding of the available data. Based on the results, you can then refine your query with additional filters to narrow the scope and focus on specific details. For more complex requests, you might also use the prompt library as a starting point, leveraging predefined examples to guide the creation of more advanced queries.

Leveraging default values

The AI assistant applies sensible defaults when information is missing:

  • Time range: 30 minutes (if not specified)
  • Thresholds: Industry-standard values for high, low, slow, and so on.
  • Sorting: Most relevant or recent items first

You can override these defaults by specifying your preferences in the query.