Backtrace includes a custom database that allows you to ask interesting questions of your data. Software engineers experience the benefit of this design with improved query performance, flexibility to group and analyze by any custom field, and use of advanced operators to query based on first-seen dates, regex or contains expressions, or exclusion criteria for errors under management.
New Super Powers!
Now, users have a new feature to explore and triage their diagnostic data – we call it “aggregation filters”, and it’s an option in the query bar.
After choosing a field to filter on, a new operator option ‘Filter on aggregation results’ appears in the menu as the last choice. This operator allows you to apply an additional filter on the results based on an aggregation, such as a unique count, or a minimum or maximum from a series of values.
Using Aggregation Filters
Let’s take a look at some example questions you can ask with this new feature:
- “Show me crashes that have impacted at least 10 unique servers”
- “Show me crashes that were likely introduced in version 2.1.0 (minimum version of at least 2.1.0)”
- “Show me crashes that have occurred in at least 2 release channels (i.e. development, qa, staging, production)”
- “Show me crashes that have impacted at most 1 unique scene in the game, so we can hone in on specific scene impacting issues”
These examples all have something in common – they require the system to perform complex filtering operations over multiple iterations of the data set. An error itself doesn’t know how many servers or scenes it impacts – but the database has this metadata available, and this new aggregation filter feature allows you to exploit it, building more interesting queries that can filter based on aggregate values of indexed metadata, ultimately allowing you to fix the bugs that matter most.
Schedule a Demo!
If you’re looking to spend less time debugging and gain the confidence you need to develop at greater speed, schedule a demo with us today! We’ll show you how you can improve your detection and resolution times of software issues by up to 90%, allowing you to spend more time on new feature development.
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