I/O operations are notorious performance killers. An async logger has consistently lower latency than a synchronous logger and high throughput of logging messages at 6 – 68 times the rate of a synchronous logger.

The asynchronous logger in Log4J 2 does this by decoupling the logging overhead from the thread executing your code.

Throughput: The number of some actions executed or results produced per unit of time.įor increased logging performance, we want lower logging latency and higher throughput.

Time of a transaction, or service invocation.

Latency: Time required to perform some action or to produce some result.

If the service is getting invoked hundreds or even thousands of times per second, the overhead of logging can become significant. In such scenarios, two fundamental performance-related concepts are: However, enterprise services can see significant volume. In small programs with little volume, the overhead of logging is rarely an issue. Performance is critical for enterprise applications and nobody wants the underlying logging framework to become a bottleneck. In this post, we’ll take a look at asynchronous loggers (async loggers) introduced in Log4J 2.

Log4J 2 Configuration: Using Properties File.

I’ve written about the different Log4J 2 configuration options in the following posts: Log4J 2 introduces configuration support via JSON and YAML in addition to properties file and XML. If you are new to Log4J2, I suggest going through my introductory post on Log4J 2, Introducing Log4J 2 – Enterprise Class Logging. Log4J 2 is a logging framework designed to address the logging requirements of enterprise applications.

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