Application monitoring

Application Insight

Unique features of the WhaTap applications

Transaction performance Deep Dive

You can trace not only SQLs and HTTP calls but also the method level. With WhaTap's unique “Active Stack” feature, you can analyze the method level without cumbersome profile settings.

Analysis of the multi-project transaction linkage

It provides the integrated trace analysis feature that allows you to easily understand the transactions with complex call relationships.

Tracing and log-integrated analysis

You can check both the detailed profile of a transaction and the logs left while performing transactions at the same time, making it easier to identify problems.

Post analysis (Cube)

You can check various metrics at a time based on the time axis. Because it is possible to check the specific time zone where the response time, error count, or throughput is high, you can identify problematic factors in the same time zone or accurately view the service status.

Analysis of the AI-based response distribution pattern

It automatically detects specific patterns and generates the corresponding alerts. It also quickly notify you of issues that the administrator has not been aware of.

Asynchronous transaction profile

WhaTap's unique BCI (Byte Code Instrumentation) technology effectively traces the performance of asynchronous transactions. You can see the transaction profiles for applications that are using WebFlux, Reactor, Hystrix, and the like.

DASHBOARD

We provide efficient monitoring methods through the agent grouping by task and server according to your perspective. The WhaTap dashboard updates information for active and completed transactions in real time and provides visualized charts so you can intuitively perceive the current status of services and systems.

Transaction Analysis

It expresses the distribution of all transactions based on the response time and end time of individual transactions, allowing selective analysis of slow transactions. You can see the performance delay sections of the delayed applications at a glance, which allows you to tune the service performance and improve the service stability.

MSA call pattern analysis

It analyzes the call ratio between transactions collected through the multi-transaction trace. By checking the dependencies between microservices at the URL level instead of the instance level, you can manage application paths with complex call structures and maintain an optimal application performance.

Metrics Chart

You can systematically manage the transaction and service performance data by searching them by period and service. You can search for highly related performance metrics and compare individual performance metrics by merging them for analysis.