Java Application Instrumentation with Log4J
Application metrics, such as performance metrics, are key to understanding and improving application efficiency. Profiling and monitoring tools yield valuable information on CPU and resource usage, including OS
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Approaches to Metric Collection
You can extract application-centric metrics, including performance metrics, in many ways. However, no single approach provides a total end-to-end solution that covers all the aspects of an enterprise application. J2EE-centric tools typically leverage one or more of the following approaches:
Log/trace scrapping
Web server logs that conform to well known formats such as the Common
Log Format (CLF) can be processed for information on HTTP operations.
Verbose GC output from the JVM can be analyzed for GC bottlenecks.
JVM hooks
Profilers plug into the JVM itself using the Profiler Interface (JVMPI) (deprecated in 1.5) and Tool Interface (JVMTI) introduced in Java 1.5.
Java Management Extensions (JMX) to publish statistics and notify of state changes and error conditions
JDBC call interception to measure the efficiency and performance of SQL operations
External services
Operating system services such as ps, top, netstat, vmstat, and sar for resource information, and telnet, rsh, and ftp for executing commands to extract such information remotely
SNMP
Homegrown
Code interleaved with homegrown statistic collection and derivation functions, and typically reported via logs
The code instrumentation approach is commonly used to insert code that measures memory, threads, and timing at a very fine-grained level, usually the method level. Code instrumentation is done by either post-processing class files or substituting code on the fly inside the JVM using JVMPI/JVMTI. Once instrumented, metrics can be logged, cached, persisted, or in an agent architecture, forwarded onto to a separate server to manage. The advantage of an agent architecture is that metrics can be captured and collated across multiple sources or tiers.
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