Scenarios for troubleshooting errors and monitoring application performance using Splunk APM 🔗
Buttercup Games, a fictitious game company, recently refactored its e-commerce site to go cloud native. The site uses microservices for the application architecture and containers for the underlying infrastructure. The company uses Splunk APM for finding root causes of errors, monitoring system performance, and tracking business KPIs.
Site reliability engineers, service owners, engineering executives, and performance engineers at Buttercup Games use Splunk APM for the following troubleshooting scenarios:
Scenario: Kai investigates the root cause of an error with the Splunk APM service map
Scenario: Deepu finds the root cause of an error using Tag Spotlight
Scenario: Alex monitors service performance using endpoint performance
Scenario: Deepu accelerates troubleshooting using Business Workflows on Tag Spotlight
Scenario: Kai troubleshoots an edge case by searching for a specific trace
Scenario: Alex troubleshoots an issue to find the root cause using Trace Analyzer
Scenario: Alex troubleshoots slow traces using Trace Analyzer
Scenario: Sasha finds performance issues using AlwaysOn Profiling
Site reliability engineers, service owners, engineering executives, and performance engineers at Buttercup Games use Splunk APM for the following monitoring scenarios:
Scenario: Deepu monitors service performance using a built-in dashboard
Scenario: Wei configures Business Workflows to track business KPIs
Scenario: Wei monitors Business Workflows to measure business KPIs
Scenario: Kai monitors detector service latency for a group of customers
To learn the specific steps for setting up and using APM features, see Set up Splunk APM.