Service exploration
This feature isn't available to all Chronosphere Observability Platform users and might not be visible in your app. For information about enabling this feature in your environment, contact Chronosphere Support.
The Services page provides efficient views into your services to help you discover ways of exploring your data. You can link directly to tracing data related to a specific service from the Services page. Chronosphere Observability Platform automatically generates these links to help you monitor services and connected telemetry.
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In the navigation menu select Services.
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In the list of services, your Deployer Service has a currently alerting monitor that exceeds the defined critical conditions.
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Select the Deployer Service to display its individual service page.
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In the Dependency map, in the Trends dropdown, select Errors.
You notice that the edge for this service has downstream errors.
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Click the more icon and select click Explore trace data to open Trace Explorer with the context defined in the service page.
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In the Trace Explorer page, in the Statistics section, select Leaf Errors in the Metric dropdown menu to highlight services that include error spans with no failing child spans.
These errors are the deepest errors within a request flow, and are often the reason why an entire trace fails.
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In the sparklines chart, you notice spikes in leaf errors for the
gatewayauth
service. -
In the Group by field, enter Operation so that you're grouping results by both Service and Operation.
In the Statistics table, you see that the
auth.Auth/Authenticate
operation of thegatewayauth
has the most leaf errors. -
Click the gatewayauth service to add it and the
auth.Auth/Authenticate
operation to your search filter. -
At the top of the page, click Copy link to copy a link with the defined filter criteria that you can share with team owning that owns the
gatewayauth
service.
You identified the service and operation with the most leaf errors and can send a contextual link to the team responsible for that service. By focusing on leaf errors, you located the root issue impacting related traces and can provide that context to the owning team.