Instrumentation Record Language (IRL)

Kieker offers a user-friendly domain specific language called the Instrumentation Record Language (IRL). It is used to define records in a language-independent way. The IRL compiler (as command line or as Eclipse plugin) is then able to generate these records in arbitrary programming languages. Currently, the compiler can produce records in Java, C, and Perl. The compiler is extensible for other languages. Therefore, we provide an API based on OSGI.

abstract entity AbstractExampleEntity {    int id    string label}template TemplateExample {    boolean templateActive}entity ExampleEntity extends AbstractEntity : TemplateExample {   byte byteValue   short shortValue   int intValue   long longvalue   double doubleValue   float floatValue   char characterValue   string stringValue   boolean boolValue}

Eclipse IDE Plug-In

Kieker provides an Eclipse-Plugin for monitoring and analyzing Java projects from within the Eclipse IDE.
The monitoring part allows to instrument and run Java-projects within Eclipse.
The analysis part allows to process a Kieker log folder by a user-defined Kieker analysis.

Kieker Trace Analysis Tool with GUI

Kieker’s Trace Analysis Tool allows to reconstruct and visualize architectural representations of the monitored systems from trace information collected at runtime. Currently supported architectural representations include

  • Software architectural diagrams
    • Sequence diagrams
    • Call trees (single traces, aggregation of trace sets)
    • Dependency graphs (container-, component-, and operation-level)
  • HTML output of the reconstructed system model
  • Textual trace and trace equivalence representations
    • Execution traces
    • Message traces

Diagrams can be exported into pixel and vector graphic formats (PDF, SVG, PNG, etc.).

The TraceAnalysisTool can be used via a command line interface and a dialog-based GUI.

Kieker Trace Diagnosis

The Kieker Trace Diagnosis is a JavaFX-based GUI which allows the user to analyze and interact with recorded traces.
It reads in the desired monitoring log, analyzes it, and finally visualizes it as filterable and sortable tables and tree views.
The provided views show operation calls, such as method invocations and SQL queries, (including type name, operation name, execution time etc.) and traces both aggregated and in detail.

Dynamic and adaptive monitoring

By default, instrumentation is static. This means, at runtime, once a method or resource is instrumented, the instrumentation cannot be removed, and if a method/resource is not instrumented, it cannot be instrumented.

Kieker includes functionality to change the instrumentation at runtime, which is denoted as dynamic instrumentation. Currently, the dynamic instrumentation can be configured via JMX and periodically polled configuration files. In this way, the monitoring can be enabled/disabled in parts or completely at runtime.

Dynamic instrumentation is a prerequisite for adaptive monitoring, which aims to plan and to execute the monitoring at runtime. This allows, for instance, to make the instrumentation more detailed when a performance problem should be analyzed.

Different monitoring outputs

The monitoring output can be persistently saved into logs, e.g.,

  • file system (async/sync)
  • database (async/sync)

or directly processed via streams using a custom or standard message protocol, e.g.,

  • TCP (sync)
  • JMS and JMX queues (async), with current support for
    • ActiveMQ
    • HornetQ
    • OpenJMS
  • AMQP writer and reader, with current support for
    • RabbitMQ

Predefined and customizable probes

Kieker provides several predefined and customizable probes to instrument and monitor your target application.
For example, there are probes which collect

  • the execution times of method invocations including their fully qualified name
  • the behavior of different threads
  • resource information, such as the CPU utilization and the memory footprint

Furthermore, it is easily possible to define custom probes, especially based on predefined probes.
For this purpose, Kieker offers a user-friendly domain specific language called the Record Instrumentation Language (see the tab “Tool Integration”).

Multiple ways of instrumentation

Kieker offers multiple ways of instrumentation for control flow tracing, e.g.,

  • Manual source code insertion
  • Automatic source code insertion via Aspect-Oriented Programming (AOP), e.g.
  • AspectJ. The insertion points can be defined
    • by annotations in the source code or via
    • pointcuts in an external configuration file (aop.xml) for better seperation of concerns.
  • Middleware interception, e.g., Spring
  • Servlet

and resource monitoring, e.g.,

  • Sigar or Servlet to monitor
    • CPU utilization
    • Memory usage