Overview
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RUM Pro supports powerful data analysis capabilities, focusing on the following features:
Supports rich search fields with multiple matching rules, enabling users to flexibly and freely query specific data.
Supports flexible statistical analysis capabilities, enabling users to freely analyze trends and distributions under specific conditions.
Supports an efficient condition comparison feature, assisting users to locate new issues and degradation issues with one click and easily identify the causes of abnormal metrics.
Supports custom data analysis and feature integration, quickly correlating various abnormal issues to offer new approaches for solving complex problems.
Data Overview
The purpose of the Data Overview is to enable users to quickly understand the quality status of the application and its trends. The Data Overview includes Dashboard Metrics and Version metrics.
Dashboard Metrics: Filters data for App versions with DAU less than 1% to eliminate the impact of Debug version data. By default, displays the dashboard data for the last 30 days. Users can adjust the time range, with support for viewing data up to the last 180 days.
Version metrics: The platform determines the release date of application versions based on the number of connected devices, using the date when the number of connected devices for an application version first reaches or exceeds 500 as its release date. By default, it displays the metric data of the latest 5 released versions. Users can freely edit the application versions they wish to view, along with their corresponding release dates. Additionally, it provides three time range selection modes: Normal Mode, Release Mode, and Custom Mode.
Exception Overview
The crash, error, Android ANR, and OOM metric analysis page is an abnormal overview, aiming to provide users with general analysis capabilities for core quality metrics.
Abnormal Overview mainly includes: Today's Abnormalities, Abnormal Trend, Top3 Issues List, Abnormal Distribution, and Top20 Issues List. The following content uses the Crash Page as an example to introduce the display descriptions of Today's Abnormalities, Abnormal Trend, Top3 Issues List, Abnormal Distribution, and Top20 Issues List.
Today's Abnormalities: Displays today's abnormal data in real time.
Note:
Day-over-day comparison = (Today's current data - Same-period data from yesterday) / Same-period data from yesterday
Abnormal Trend: Displays the abnormal reporting trend at multiple aggregation granularities.
Supports three aggregation granularities: 5-minute aggregation, 1 Hour aggregation, and Aggregation by day.
Supports drill-down analysis and comparative analysis of App Versions.
Displays data across multiple statistical dimensions.
Supports viewing the Top3 issues of aggregated nodes at 5-minute aggregation and 1 Hour aggregation granularities.
Abnormal Distribution: Displays the statistical distribution of three key fields: Application Version, system version, and Model. By default, displays the Top5 distribution data. Users can click View More to view all distribution data.
Top20 Issues List: Displays the Top20 issues sorted by the number of affected devices on the statistical date. Users can click View More Top Issues to view additional Top issues in the issues list.
Note:
Fluctuation in the number of affected devices = Percentage of affected devices on the current day - Percentage of affected devices on the previous day
Fluctuation in occurrence count = Percentage of occurrences on the current day - Percentage of occurrences on the previous day
Metric Analysis
iOS ANR and FOOM, stutter, memory, and app launch time metrics analysis is primarily used to analyze the trend changes of corresponding module metrics.
Metric analysis includes trend analysis, comparative analysis, and multidimensional analysis. Using the ANR page as an example, the following describes the display descriptions for trend analysis, comparative analysis, and multidimensional analysis.
Trend Analysis: Aims to display the trend changes of monitored item metrics under specified conditions.
Comparative Analysis: Aims to compare the differences in changes between the trends of two sets of metrics.
Multidimensional Analysis: Compares differences in metric data by combining multiple dimensions.
Queries
Issue List
RUM Pro supports users in analyzing various metrics through the exception overview and metrics analysis pages. In addition to metrics, the platform provides issue analysis for each monitored item via the issue list page.
The issue list supports robust search criteria, allowing users to freely analyze exception reporting under various conditions. The features of the issue list are divided into two main categories: Statistical Analysis and Top Issue Analysis.
Statistical Analysis
Statistical analysis includes Trend analysis and Statistical distribution.
For crash, ANR, OOM, and error issues, the list currently supports statistical analysis capabilities.
The filter options for the issue list are grouped into two categories: one is individual case filters, which select cases meeting specific conditions such as reporting time, App version, user ID, error stack, etc.; the other is issue filters, such as issue tags, ticket status, assignee, processing status, etc.
Statistical analysis applies to individual case filters. By setting search criteria, you can view trend data for cases meeting these conditions, such as Occurrences, Number of affected devices, Affected Users, etc.
The connected device count is a special case, currently supporting only two filter criteria: time range and App version. For example: if a user selects the last 7 days, App version 4.5.6, and background state for crash cases, the occurrence count, affected user count, and affected device count all refer to cases meeting these three conditions simultaneously. However, for the connected device count, it only represents cases meeting both the last 7 days and App version 4.5.6 criteria, as it does not support foreground/background state filtering.
The deviceCrash rate, TimesCrash rate, and UserCrash rate in trend analysis refer to the number of abnormal cases meeting the criteria / the number of connected reports meeting the criteria. Note that the connected reports metric only supports two filter conditions: time range and App version.
Statistical analysis supports not only the Application Version, system version, and Model fields but also additional fields such as Foreground or background status, Error process, Error thread, Vendor, CPU architecture, ROOT or Not, etc.
Users can click to view the distribution details of a specific field, showing the percentage distribution of occurrence count, affected devices, and affected users.
Top Issue Analysis
Based on the search criteria set by users, the system searches for abnormal reporting cases that meet the conditions and displays aggregated Issues according to problem characteristics. Issues are shown by default sorted by most recently reported, while allowing users to switch to other sorting options.
Users can search for specific issues meeting the criteria based on the result list. When users do not need to search based on issues, they can collapse the issue filter options.
Supports users exporting the result list.
Allows users to freely customize the column headers of the result list.
Version Tag: Displays the version range in which the issue occurs. This result is derived from case data collected over the last 90 days.
Supports users adding custom tags to facilitate problem categorization. question tags are searchable.
By clicking the triangle button, users can view the detailed exception stack trace, or directly click the issue ID to go to the issue details for in-depth analysis.
Issue Details
On the issue list page, clicking the issue ID will go to the issue details. The issue details focus on providing a detailed analysis of a specific Issue.
Case Details
The core purpose of case details is to help users analyze the abnormal scene of a specific Issue. Users can query cases under specified conditions, which contain rich on-site information.
Drill-down analysis
Provides rich filter criteria, enabling users to analyze data under specified conditions.
Upward Trend: Supports multi-granularity aggregated data down to the minute level, enabling more real-time analysis.
Statistical Distribution: Provides statistical analysis capabilities for multiple fields, enabling more comprehensive analysis.
Error stack trace analysis supports user customization.
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