StackImpact is a production-grade performance profiler built for both production and development environments. It gives developers continuous and historical code-level view of application performance that is essential for locating CPU, memory allocation and I/O hot spots as well as latency bottlenecks. Included runtime metrics and error monitoring complement profiles for extensive performance analysis. Learn more at stackimpact.com.

• Continuous hot spot profiling of CPU usage and locks.
• Health monitoring including CPU, memory, garbage collection and other runtime metrics.
• Alerts on profile anomalies.
• Team access.

Learn more on the features page (with screenshots).

The StackImpact profiler agent is imported into a program and used as a normal package. When the program runs, various sampling profilers are started and stopped automatically by the agent. The agent periodically reports recorded profiles and metrics to the StackImpact Dashboard.

See full documentation for reference.

• Linux and macOS. Java 1.7 or higher.

Sign up for a free trial account at stackimpact.com (also with GitHub login).

Download the stackimpact.jar file.

Add -javaagent:/path/to/stackimpact.jar Java option.

Configure the agent using environment variables:

• SI_AGENT_KEY (Required) The API key for communication with the StackImpact servers.
• SI_APP_NAME (Required) A name to identify and group application data. Typically, a single codebase, deployable unit or executable module corresponds to one application.
• SI_APP_VERSION (Optional) Sets application version, which can be used to associate profiling information with the source code release.
• SI_APP_ENVIRONMENT (Optional) Used to differentiate applications in different environments.
• SI_HOST_NAME (Optional) By default, host name will be the OS hostname.
• SI_DEBUG_MODE (Optional) Enables debug logging.
• SI_CPU_PROFILER_DISABLED, SI_LOCK_PROFILER_DISABLED (Optional) Disables respective profiler when true.

Alternatively, the agent can be configured using Java system properties, e.g. si.agent.key, si.app.name, etc.

Download the stackimpact.jar file.

Add the jar file to the classpath.

Import the agent in your application:

Start the agent when the application starts:

The agent can be configured by setting initialization options using the following methods prior to calling the start() method:

• StackImpact.setAppVersion(String appVersion) (Optional) Sets application version, which can be used to associate profiling information with the source code release.
• StackImpact.setAppEnvironment(String appEnvironment) (Optional) Used to differentiate applications in different environments.
• StackImpact.setHostName(String hostName) (Optional) By default, host name will be the OS hostname.
• StackImpact.setAutoProfilingMode(boolean isAutoProfilingMode) (Optional) If set to false, disables automatic profiling and reporting. Focused profiling should be used instead. Useful for environments without support for timers or background tasks.
• StackImpact.setDebugMode(boolean isDebugMode) (Optional) Enables debug logging.
• StackImpact.setCPUProfilerDisabled(boolean isDisabled), setLockProfilerDisabled(boolean isDisabled) (Optional) Disables respective profiler when true.

Use StackImpact.profile() to instruct the agent when to start and stop profiling. The agent decides if and which profiler is activated. Normally, this method should be used in repeating code, such as request or event handlers. Usage example:

Import ProfileSpan object from com.stackimpact.agent.ProfileSpan.

Optional

Use StackImpact.destroy() to stop the agent if necessary. This method is automatically called on JVM shutdown.

Once your application is restarted, you can start observing continuous CPU, memory, I/O, and other hot spot profiles, execution bottlenecks as well as process metrics in the Dashboard.

To enable debug logging, use StackImpact.setDebugMode(true) method. If the debug log doesn't give you any hints on how to fix a problem, please report it to our support team in your account's Support section.

The agent overhead is measured to be less than 1% for applications under high load.