Creating log metric

Dynatrace Log Management and Analytics gives you the ability not only to view and analyze logs but also to create metrics based on log data and use them throughout Dynatrace like any other metric. You can add them to your dashboard, include them in an analysis, and even create custom alerts.

Create connections refused metric

You need to count how many refused connections are recorded in your log data. For that, filter the correct logs and turn the number of occurrences into a log metric. By tracking the metric, you can track possible firewall, network connectivity or server configuration issues.

Build DQL query

To build and run your query:

In the Dynatrace menu, go to Logs.
On the Logs and events page, turn on Advanced mode.

Select

copy for the code sample below.

1fetch logs
2| filter matchesPhrase(content, "Connection refused")
3| sort timestamp desc

Paste the query into the query edit box and select Run query.

This query performs the following actions:

Retrieves logs with the Connection refused phrase found in the log content.
Sorts the result in descending order according to the timestamp.

Create metric

Go to Settings > Log Monitoring > Metrics extraction and select Add log metric.
In Key, append the metric name to the log. metric key: log.conn_refused_count
Add Matcher.
Use the DQL function for matching phrases, which is part of the Dynatrace Query Language (DQL):
```
1matchesPhrase(content, "Connection refused")
```
This will filter the log data containing the phrase Connection refused.
For the Metrc measurement option, select Occurrence of log records.
The metric will represent the count of occurrences of log records that contain Connection refused phrase.
Select Save changes to create the log metric.

View metric

View the result in data explorer:

In the Dynatrace menu, go to Data explorer.
Select log.conn_refused_count log key.
Select Run query.

Create log attribute metric

You need to monitor an attribute of your logs, and you need to keep an eye on the error levels reported in your logs from your K8s cluster. Find the correct logs from Grail, and use the filters to create a new metric for these. Turn your attention to add log status (error/warning/info) to your metric, which makes it easy to track these with metrics.