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Advanced Log Queries

This document provides advanced examples of querying logs using the groundcover API with complex filtering conditions.

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Overview

The group parameter supports various filter operations and combinations. This page demonstrates advanced patterns including:

  • OR conditions within a single field

  • NOT conditions (excluding values)

  • Wildcard matching

  • Free text search

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OR Conditions on a Single Field

To match multiple values for the same field (OR condition), include multiple filters in the same condition:

Example: Match logs where env is either "prod" OR "dev" AND level is "error"

curl 'https://app.groundcover.com/api/logs/v2/query' \
  -H 'accept: application/json' \
  -H 'authorization: Bearer <YOUR_API_KEY>' \
  -H 'Content-Type: application/json' \
  --data-raw '{
    "start": "2025-12-24T13:36:49.143Z",
    "end": "2025-12-24T19:36:49.143Z",
    "group": {
      "operator": "and",
      "conditions": [
        {
          "filters": [{"op": "match", "value": "error"}],
          "key": "level",
          "origin": "root",
          "type": "string"
        },
        {
          "filters": [
            {"op": "match", "value": "prod"},
            {"op": "match", "value": "dev"}
          ],
          "key": "env",
          "origin": "root",
          "type": "string"
        }
      ]
    },
    "limit": 200,
    "skip": 0,
    "sortBy": "timestamp",
    "sortOrder": "desc",
    "selectors": [],
    "optimizeSearch": true
  }'

Structure:

  • Multiple filters in the same conditions entry create an OR relationship

  • In this example, the env field matches if it equals "prod" OR "dev"

  • The overall operator: "and" means both conditions must be satisfied (level=error AND (env=prod OR env=dev))

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NOT Conditions (Excluding Values)

To exclude specific values, use the "op": "not_match" operation:

Example: Match logs where level is NOT "error" AND env is "prod"

Structure:

  • Use "op": "not_match" to exclude values

  • This example returns logs where level is anything except "error" AND env is "prod"

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Wildcard Matching

To match values that start with, end with, or contain a pattern, use wildcard characters:

Example: Match logs where workload starts with "groundcover" AND level is NOT "error"

Structure:

  • Use * as a wildcard character

  • "groundcover*" matches any value starting with "groundcover" (e.g., "groundcover-backend", "groundcover-frontend")

  • Wildcards can be used with both match and not_match operations

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Free Text Search

To search for specific text or phrases within log content (not limited to specific fields), use free text search with phrase_search:

Example: Search for logs containing the phrase "POST /ingest" with additional fields

Structure:

  • Use "op": "phrase_search" for free text search

  • Set "type": "freetext" (instead of "type": "string")

  • Do not include a "key" field - free text search searches across all log content

  • The value can be a single word or a phrase (e.g., "POST /ingest")

  • Free text search searches within the log line content, not specific fields

  • Use selectors to request additional fields. Format: [{"key": "request.method"}, {"key": "cluster"}, {"key": "host.id"}]

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Filter Operations

The following filter operations are supported:

Operation
Description
Example

match

Matches the exact value or pattern

{"op": "match", "value": "error"}

not_match

Excludes the exact value or pattern

{"op": "not_match", "value": "error"}

phrase_search

Searches for a phrase in log content (free text)

{"op": "phrase_search", "value": "POST /ingest"}

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Combining Conditions

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AND Operator

When using "operator": "and", all conditions must be satisfied:

This means: level condition AND env condition must both be true.

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OR Within a Field

Multiple filters in the same condition create an OR relationship:

This means: env equals "prod" OR env equals "dev".

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Complex Combinations

You can combine AND and OR operations:

This means: level equals "error" AND (env equals "prod" OR env equals "dev").

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Best Practices

  1. Wildcard Performance: Use wildcards judiciously as they can impact query performance on large datasets.

  2. NOT Operations: not_match operations can be slower than match operations. Consider if you can achieve the same result with positive matches.

  3. Multiple Filters: When using multiple filters in a single condition (OR), ensure they all apply to the same field.

  4. Consistent Structure: Always include origin: "root" and the appropriate type for each condition.

  5. Testing: Test complex queries with small time ranges first to verify the results before querying large datasets.

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