Causes of Transaction Count Mismatch

1. Sampling Rate: Applications Manager uses sampling to reduce overhead, capturing only a subset of transactions. Adjusting the sampling rate can help align the counts, potentially achieving a 99% to 100% match.
   
2. Configuration Issues: Misconfigurations in the agent configuration profile or application settings can lead to incorrect data collection. This includes filters, exclusions, and incorrect threshold settings.
3. Network Latency: Delays or losses in data transmission between the application and the APM Insight agent can affect transaction reporting.
4. Data/Time Aggregation: Differences in how data is aggregated and reported by our agent compared to the application can cause discrepancies. APM tools often use different time windows or aggregation methods, resulting in these differences. There could be maximum of 1 or 2 minutes difference between data collection and reporting times.
5. Calculation Differences: Custom time ranges set in Applications Manager may include an extra minute or use  different rounding rules, affecting the transaction counts.
   

Troubleshooting Steps

1. Verify APM Configuration: Ensure that the agent profiles are configured correctly to monitor all relevant transactions. For example, adjust the sampling rate to capture a higher percentage of transactions. Set it to 100% for a period to compare counts 
   
1. Note: For Java Agent, disable Smart Sampling as it may drop transactions. Add the following configuration to the agent's <agent_extracted_path>/apminsight.conf file: 
1. 

   smart.sampler.enabled=false

2. Compare Data Collection Methods: Understand the aggregation and filtering methods in both systems. For example, ensure that no transactions are being filtered out or preprocessed in a way that affects the counts.

3. Analyze Network Traffic: Monitor for packet loss and network latency.
4. Review Logs and Metrics: Look for discrepancies and missing entries.
5. Test with Controlled Transactions: Perform controlled tests to compare reported counts. For example, execute a known number of transactions and compare the counts reported by the agent and the application. This can help isolate the source of the mismatch.
6. Adjust for Time Aggregation and Calculation Differences: Ensure matching time aggregation settings and custom ranges. For example, be aware that custom time ranges in Applications Manager might include an extra minute or use different rounding rules. Adjust the custom ranges to match the application's reporting periods.
   

Additional Considerations

Conclusion

Transaction count mismatches can be resolved by adjusting configurations, ensuring complete instrumentation, and aligning data collection methods. By systematically troubleshooting and understanding time aggregation and calculation differences, a 99% to 100% match is achievable, ensuring accurate performance monitoring.