Formatting timeslice sumologic5/19/2023 See how to Parse JSON Formatted Logs for details. This includes any value from the tags field by using the field option with the JSON operator, for example, | json field=tags. You can parse your spans in the same way you parse log data. The _any option is not supported outside of the scope of a query. This is supported for the Security and Tracing tiers. For example, to search for data with any field that has a value of success you would put _any=success in the scope of your query. In scenarios where users are not familiar with the schema and would like to search across all the fields, _any modifier provides a means to search for a specified value from all of the Ingest Time Fields in your data. ![]() You need to specify _index=_trace_spans in the scope to reference your trace data. Choose a time range up to seven days ago that you'd like to review.Ī Keyword Search Expression defines the scope of data for the query. ![]() On the Search page, enter the following in the text box: _index=_trace_spans.Click the + New button in the tab bar and select Log Search.To search your tracing data do the following: You just need to specify the _index metadata field with the value _trace_spans in the (/build-search/Keyword-Search-Expression (also called the scope) of your query. Searching span data is the same as running a log search. Field extraction rules are not supported as the index has well defined schema.Contact your Sumo Logic representative for paid subscription service options for volume requirements exceeding 200x of your tracing ingest. Adding to Dashboard is supported as long as your total dashboard-originated _trace_spans read volume does not exceed 200x of your tracing ingest._index and _view are not supported other than when specified as _trace_spans.Logreduce without a field, value, or key suffices.The following operators are not supported when searching trace span data:.Tracing data retention in _trace_spans index is the same as default log index retention. The frustrated queries are everything not captured by these two counters, so count as total_logs gives us everything else we need, assuming our log source only contains access logs.You can use our Search Query Language in a log search to query raw spans from tracing data for the same period as the default partition. This simply creates a counter for satisfied and tolerating using nested if functions with the matches operator. We use structured logging, so our logs are JSON formatted, but you could do this just as easily via a regex capture on apache style access logs to extract the status code and response time. | ((satisfied +tolerating / 2) /total_logs) as apdex | count as total_logs, sum(satisfied_counter) as satisfied, sum(tolerating_counter) as tolerating by _timeslice | if(statusCode matches "2*", if(responseTime, 1, 0), 0) as tolerating_counter So how can we build this measure in SumoLogic? Let's take a look | json auto field =raw_log 2xx or 3xx status codes.Ī tolerating request is successful in more than T, and less than 4T.įrustrated requests exceed 4T or fail, e.g. ![]() It divides all served requests into three categories: satisfied, tolerating, and frustrated.Ī user's request is said to be satisfied when it occurs within some T value, such as 400ms, and is successful, e.g. Application Performance Index (Apdex) is a standardised method for calculating the perceived satisfaction of a user accessing your service.
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