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Python Monitoring

WhaTap Python Application Monitoring provides the monitoring service for Python-based web application servers. It is the only product in Korea that monitors the Web frameworks, servers, and batches at once.

WhaTap Python Monitoring can be applied to major web frameworks, and it can also track DB queries and outbound calls to find which calls are being delayed. To trace data for a specific transaction other than HTTP or HTTPS, use the corresponding method.

WhaTap's Application Monitoring can monitor application in real time without reproducing failures.

Key features

  • Real-time transaction monitoring

    WhaTap displays the status of active transactions in real time. Any application issue manifests itself as an increase of active transactions. If you can immediately check SQLs, outbound calls, and method stacks being executed the very moment when transactions increase, you can recognize or analyze the problem very fast.

  • Transaction performance Deep Dive

    WhaTap can collect and analyze the performance history of all transactions. Transaction performance can be traced down to the method level as well as SQLs and HTTP calls.

    In particular, the active stack function enables you to analyze the method level without a cumbersome task of complicated method profile setting. With WhaTap's proprietary technology, called Active Stack, it provides improvement points to locate the source of problems from hidden areas that were not found in other products.

    Active Stack is supported only in Java and Python.

  • MSA call pattern analysis

    WhaTap visualizes the ratio of calls based on the transaction URL for the relationships between complex applications that have the MSA structure. This enables you to view the call relations and change of call ratios.

  • Analysis of AI-based response distribution patterns

    WhaTap automatically recognizes specific patterns through machine learning and sends alert notifications to operators. This can inform you of the issues that the operator did not recognize. (Please contact support for on-premise type)
    Application number: 10-2020-0037381

  • Analysis of the multi-project transaction linkage

    WhaTap provides the transaction-based tracing in the MSA environment. All transactions can be traced to determine which applications were delayed.

  • Stack statistics analysis

    Statistical analysis can find tuning points that are difficult to find in real-time monitoring or profile data. You can also select improvement targets through graphs and tables, or check response delays in specific time periods.

  • Post analysis (Cube)

    You can check various metrics at a time based on the time axis. Because it is possible to specify the 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.