LM Logs multiple capture group parsing
Ok, this is cool. I have some log data that has structured data in it (some text, then a python list of strings). I had started building out a parse statement for each member of the list, then thought I’d try just making multiple capture groups and naming multiple variables after the as fanboy. Turns out it completely works. It parses each capture group into the corresponding column with a single parse statement. I was halfway through writing out a feature request when I figured I’d give it a try only to discover that it completely works. Nice job LM Logs guys.LM Logs parser conditional formatting operator
Submitted to LM Feedback under the title “LM Logs parser colorization based on criteria” As an engineer who is trying to see how certain logs relate to other logs, it would be helpful if I could highlight specific logs in context with other logs by using an advanced search operator to colorize certain logs that meet a certain criterion. For example, I run this query often: "PagerDuty Ticket Creation" | parse /(.*) (SUMMARY|ERROR|INFO|DEBUG): (.*)/ as Script, Severity, Msg One of the fields I parse is the Severity, which as you can see can have values of SUMMARY, ERROR, INFO, or DEBUG. It would be nice if I could add an operator to the query that would let me colorize rows based on the value of the parsed Severity column (Severity just in this case; for the general case, any expression on any column). For example, I'd like to run the query: "PagerDuty Ticket Creation" | parse /(.*) (SUMMARY|ERROR|INFO|DEBUG): (.*)/ as Script, Severity, Msg | colorize Severity == "ERROR" as orange | colorize Severity ~ /SUMMARY|INFO/ as green The result would be that rows in the table that have a value of "ERROR" would have a background color of orange (a muted orange) and rows in the table that have a value of "SUMMARY" or "INFO" would be colored green. Since the DEBUG logs don't match any colorization operator, they would have the default color of white. It might be handy if one *or* two colors could be passed, allowing me to change the color of the text and the background, or just the background. It would be ok if I could only choose from a set list of colors, but it would be great if I could specify an RGBA color.
Getting started with Log analysis - useful queries
We at LogicMonitor want to make taking control of your log data easy for analysis, troubleshooting, and identifying trends. In this post, we will share a few helpful queries to get started with LM Logs - what devices are generating log data and easy ways to track overall usage. In future posts, we’ll share queries to dive deeper into specific log data types. What type of queries do you want to see? Reply to this post with areas of log analysis or best practices you want. Not up to date with LM Logs? Check out this blog post highlighting recent improvements and customer stories: A lookback at LM Logs NOTE: Some assumptions for these queries: Each queries results are bound to the time picker value, adjust according to your needs * is a wildcard value meaning ALL which can be replaced by a Resource, Resource Group, Sub-Group, Device by Type or Meta Data value You may need to modify specific queries to match your LM portal Devices Sending Logs- use this query to easily see which LM monitored devices are currently ingesting log data into your portal * | count by _resource.name | sort by _count desc Total Number of Devices Sending Logs-the previousquery showed which devices are generated logs, while this query identifies the overall number of devices * | count by _resource.name | count Total Volume by Resource Name -this query shows the total volume of log ingestion (as GB) by resource name, with the average, min, max size per message. The results are sorted by GB descending but you can modify the operators to identify your own trends. * | count(_size), sum(_size), max(_size), min(_size) by _resource.name | num(_sum/1000000000) as GB | num(_sum/_count) as avg_size | sort by GB desc Total Log Usage -This is a helpful query to run to see your overall log usage for the entire portal * | sum(_size) | num(_sum/1000000000) as GB | sort by GB desc And finally,Daily Usage in Buckets -run this query to see an aggregated view of your daily log usage * | beta:bucket(span=24h) | sum (_size) as size_in_bytes by_bucket | num(size_in_bytes/1000000000) as GB | sort by _bucket asc We hope these help you get started!
