The Operational Insights not only gives your Operations and Customer Support teams insights into errors encountered by your users, but also provides a split between software generated errors (from the app), user generated errors (people using the service incorrectly) and service errors (network issues). We monitor all client errors from app and player and create error categories within the Insights console.
Key Metrics in the Operational Insights real-time dashboards
KPI | Description |
|---|---|
Active Users | Number of active users on the service |
Active Sessions |
Number of active sessions on the service
Peak Concurrent Sessions | Maximum number of concurrent sessions |
Peak Concurrent Devices | Maximum number of concurrent sessions |
Attempts to play | Number of attempts to play a video asset |
VSF | Number of Video start sessions affected by Service Errors -Available as Peak, Average, Typical which is median and Total |
EBVS | Exit Before Video Starts is the Number of Video start sessions abandoned by users - Available as Peak, Average, Typical which is median and Total |
Sessions affected by any error | While VSF and EBVS are the largest errors, this still captures the total impact on the sessions |
Number of plays as a % of attempts | It is important to understand what % of play backs are affected instead of just an absolute number |
Content most affected by Errors | Errors are contextual to the content where they are experienced |
Service Type most affected by Errors | Understanding whether the error is affecting Live versus VOD content is very important to understand its importance |
Rebuffering Duration | Available as Total, peak, Typical (Median) and Average across a time-period selection |
Play sessions affected by rebuffering | Number of play sessions that are impacted by buffering |
Profile of content affected by rebuffering | Filtering by content resolution in addition to the content itself is valuable |
Video Playback Errors | Number of errors faced in Video playback |
Playback errors as a % of total plays | Understanding impact of errors by measuring them as a % of total plays |
Peak Concurrent plays by Session type | Understanding number of peak concurrent plays by Session type (Live, VOD) to inform capacity planning |
Peak Concurrent plays by Device type | Understanding number of peak concurrent plays by device type (Smart TV, iOS) to inform capacity planning |
Peak Concurrent plays by Content | Understanding number of peak concurrent plays by content to inform capacity planning |
