Pattern analysis - Amazon CloudWatch Logs
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Pattern analysis

CloudWatch Logs Insights uses machine learning algorithms to find patterns when you query your logs. A pattern is a shared text structure that recurs among your log fields. When you view the results of a query, you can choose the Patterns tab to see the patterns that CloudWatch Logs found based on a sample of your results. Alternatively, you can append the pattern command to your query to analyze the patterns in the entire set of matching log events.

Patterns are useful for analyzing large log sets because a large number of log events can often be compressed into a few patterns.

Consider the following sample of three log events.

2023-01-01 19:00:01 [INFO] Calling DynamoDB to store for resource id 12342342k124-12345 2023-01-01 19:00:02 [INFO] Calling DynamoDB to store for resource id 324892398123-12345 2023-01-01 19:00:03 [INFO] Calling DynamoDB to store for resource id 3ff231242342-12345

In the previous sample, all three log events follow one pattern:

<*> <*> [INFO] Calling DynamoDB to store for resource id <*>

Fields within a pattern are called tokens. Fields that vary within a pattern, such as a request ID or timestamp, are dynamic tokens. Each dynamic token is represented by <*> when CloudWatch Logs displays it.

Common examples of dynamic tokens include error codes, timestamps, and request IDs. A token value represents a particular value of a dynamic token. For example, if a dynamic token represents an HTTP error code, then a token value could be 501.

Pattern detection is also used in the CloudWatch Logs anomaly detector and compare features. For more information, see Log anomaly detection and Compare (diff) with previous time ranges.

Getting started with pattern analysis

Pattern detection is automatically performed in any CloudWatch Logs Insights query. Queries that don't include the pattern command get both log events and patterns in the results.

If you include the pattern command in your query, pattern analysis is performed on the entire matched set of log events. This gives you more accurate pattern results, but the raw log events are not returned when you use the pattern command. When a query doesn't include pattern, the pattern results are based either on the first 1000 returned log events, or on the limit value you used in your query. If you include pattern in the query, then the results displayed in the Patterns tab are derived from all log events matched by the query.

To get started with pattern analysis in CloudWatch Logs Insights
  1. Open the CloudWatch console at

  2. In the navigation pane, choose Logs, Logs Insights.

    On the Logs Insights page, the query editor contains a default query that returns the 20 most recent log events.

  3. Remove the | limit 20 line in the query box, so that the query looks like the following:

    fields @timestamp, @message, @logStream, @log | sort @timestamp desc
  4. In the Select log group(s) drop-down, choose one or more log groups to query.

  5. (Optional) Use the time interval selector to select a time period that you want to query.

    You can choose between 5-minute and 30-minute intervals; 1-hour, 3-hour, and 12-hour intervals; or a custom time frame.

  6. Choose Run query to start the query.

    When the query finishes running, the Logs tab displays a table of log events returned by the query. Above the table is a message about how many records matched the query, similar to Showing 1000 of 71,101 records matched.

  7. Choose the Patterns tab.

  8. The table now displays the patterns found in the query. Because the query did not include the pattern command, this tab displays only the patterns discovered among the 1000 log events that were shown in the table in the Logs tab.

    For each pattern, the following information is displayed:

    • The Pattern, with each dynamic token displayed as <*>.

    • The Event count, which is the number of times that the pattern appeared in the queried log events. Choose the Event count column heading to sort the patterns by frequency.

    • The Event ratio, which is the percentage of the queried log events that contain this pattern.

    • The Severity type, which will be one of the following:

      • ERROR if the pattern contains the word Error.

      • WARN if the pattern contains the word Warn but doesn't contain Error.

      • INFO if the pattern doesn't contain either Warn or Error.

      Choose the Severity info column heading to sort the patterns by severity.

  9. Now change the query. Replace the | sort @timestamp desc line in the query with | pattern @message, so that the complete query is as follows:

    fields @timestamp, @message, @logStream, @log | pattern @message
  10. Choose Run query.

    When the query finishes, there are no results in the Logs tab. However, the Patterns tab likely has a larger number of patterns listed, depending on the total number of log events that were queried.

  11. Regardless of whether you included pattern in your query, you can further inspect the patterns that the query returns. To do so, choose the icon in the Inspect column for one of the patterns.

    The Pattern inspect pane appears and displays the following:

    • The Pattern. Select a token within the pattern to analyze that token's values.

    • A histogram showing the number of occurrences of the pattern over the queried time range. This can help you to identify interesting trends such as a sudden increase in occurrence of a pattern.

    • The Log samples tab displays a few of the log events that match the selected pattern.

    • The Token Values tab displays the values of the selected dynamic token, if you have selected one.


      A maximum of 10 token values is captured for each token. Token counts might not be precise. CloudWatch Logs uses a probabilistic counter to generate the token count, not the absolute value.

    • The Related patterns tab displays other patterns that frequently occurred near the same time as the pattern that you are inspecting. For example, if a pattern for an ERROR message was usually accompanied by another log event marked as INFO with additional details, that pattern is displayed here.

Details about the pattern command

This section contains more details about the pattern command and its uses.

  • In the previous tutorial, we removed the sort command when we added pattern because a query is not valid if it includes a pattern command after a sort command. It is valid to have a pattern before a sort.

    For more details about pattern syntax, see pattern.

  • When you use pattern in a query, @message must be one of the fields selected in the pattern command.

  • You can include the filter command before a pattern command to cause only the filtered set of log events to be used as input for pattern analysis.

  • To see pattern results for a particular field, such as a field derived from the parse command, use pattern @fieldname.

  • Queries with non-log output, such as queries with the stats command, do not return pattern results.